When a pioneer like OpenAI invites users to create voice agents using its new audio models, it’s clear that voice agents are no longer futuristic.

But for growing businesses, the shift can be confusing.

How do you move beyond scripted bots? Which agent fits your use case? Do you need AI voice bots for customer support, appointment scheduling, or multilingual assistance? And most importantly, how do you ensure you're not overpaying for the best AI voice platforms giving bare-minimum performance? 

In this blog post, we break it down for you. We’ll explore the five best AI voice agents in the market, compare their pricing, highlight what makes each unique, and help you find the best fit for your business.

5 best AI voice agents: A quick overview 

Before exploring all five AI-powered voice assistants in detail, here’s a quick snapshot of their core strengths, pricing, and whether they’re built for real-time conversations.

Let’s closely examine each of these voice agents.

1. Plivo

Plivo’s AI Voice Agents do more than automate routine tasks. They help you build intelligent, customizable assistants. 

You can choose your preferred language model (LLM), text-to-speech (TTS) provider, and language to create voice agents customized to various communication needs.

From healthcare business requirements like sending real-time alerts and notifications or appointment reminders to offering 24/7 customer support, Plivo’s Voice AI for businesses handles varying touchpoints in the customer journey.

Plivo’s key features

• Real-time conversations: Plivo Voice Agents respond instantly due to ultra-low latency of under 30 milliseconds, so your customers don’t need to wait for a human agent and their queries are promptly answered.
• Custom-trained agents: You can personalize voice agents using your own knowledge base, FAQs, or business data to reflect your tone and customer needs.
• Reliable infrastructure: Since the bots are hosted on Plivo’s proven voice platform, these agents benefit from 99.99% uptime and scalable global coverage for high call quality. This makes it one of the best AI call center solutions.
• Plug-and-play integrations: Connecting to AI models and speech providers like OpenAI, Deepgram, and ElevenLabs is easy without a complex setup.
• Flexible use cases: You can use these agents to optimize any customer touchpoint of your customer’s journey, whether it’s making outbound calls, providing customer support, sending reminders, or converting a lead.

Plivo’s pros

• The API is well-documented and easy to use, enabling smooth integration. (Source)
• Plivo’s support team is highly responsive and well-informed. (Source)
• Pricing is competitive and designed to offer strong value for the features provided. (Source)
• Built on a global infrastructure with 99.99% uptime. (Source)

Plivo’s cons

• While functional, the dashboard could benefit from a more user-friendly interface. (Source)

Plivo’s pricing

$0.003 per min per stream

Note: You can save 40% with Plivo as other players charge > = $0.005 per min per stream.

Plivo is suitable for

Scaling businesses looking for a cost-friendly solution to optimize customer interactions and automate lead qualification and conversions through AI-powered voice bots.

2. Five9 Intelligent Virtual Agent (IVA)

Five9’s virtual agents use conversational AI to automate routine customer interactions, handle support calls, and assist live agents. So, if you want to boost efficiency, lower wait times, and scale support without increasing headcount, Five9 is a go-to option.

Five9’s key features

• Conversational AI: It employs advanced speech recognition and NLP in AI agents to understand and respond to customer inquiries across voice and digital channels.​
• Omnichannel support: Five9 provides consistent customer experiences across multiple channels, including voice, chat, SMS, and social media.​
• Integration capabilities: You can integrate it with popular CRM systems like Salesforce, ServiceNow, Microsoft, Oracle, and Zendesk to improve agent efficiency.

Five9’s pros

• Reliable platform with geographic failover for uninterrupted service. (Source)
• The outbound dialer is feature-rich, easy to set up, and simple to monitor. (Source)
• List Sync Plus automatically syncs records into the Five9 dialer for simplified list management. (Source)
• Accessible from anywhere, including mobile devices. (Source)

Five9’s cons

• Inconsistent call quality makes conversations difficult to hear. (Source)
• Its interface lacks appeal or text functionality. (Source)
• Initial tool deployment and setup can be challenging. (Source)

Five9’s pricing

$119/month for voice-only  

Five9 is suitable for

Enterprises aiming to improve customer support and automate lead qualification.

3. Tabbly.io

Tabbly.io is an AI-powered platform that helps businesses build custom voice agents for sales, support, and lead management without writing a single line of code. With multilingual support and CRM integration, the platform makes it easy for teams to automate conversations, qualify leads, and respond to customer queries in real time.

Tabbly’s key features

• Multilingual voice support: It offers over 50 language voices so businesses can interact with a diverse customer base in their preferred language. 
• No-code agent builder: Users can create custom AI voice agents without advanced coding skills by defining prompts, selecting voices, and setting output instructions.

Tabbly’s pros

• Engages customers naturally in over 50 languages
• Handles multilingual communication with regional accent support
• Works across use cases like sales, customer support, hiring, and collections

Tabbly’s cons

As a relatively new platform, businesses with large-scale operations may find scalability to be a concern.

Tabbly’s pricing

$0.08 per minute 

$0.06 per minute for large committed volumes

Tabbly is suitable for

Startups and SMBs looking for a quick way to scale communication through voice.

4. Talkdesk

​Talkdesk AI-driven call automation is built on the Talkdesk Ascend AI platform so that you can deploy them with a simple natural-language prompt. It also integrates with customer relationship management (CRM) and electronic health records (EHR) systems.

They analyze customer speech in real time with AI-driven speech recognition tools, adapt to nuances such as slang and idioms, and take appropriate actions without complex scripting or extensive training. ​

Talkdesk’s key features 

• Natural language deployment: You can create and deploy AI agents using simple prompts, eliminating the need for coding. 
• Real-time speech analysis: It understands and responds to customer conversations dynamically to handle variations in speech and context.
• Multi-language support: You can engage with customers in 59 languages without requiring translation, which lets you reach a global customer base.

Talkdesk’s pros

• Highly customizable through both native features and robust APIs. (Source)
• Flexible tools and customization options for both agent operations and admin management. (Source)
• Status settings like available or busy help control call flow, ensuring agents only receive calls when ready. (Source)

Talkdesk’s cons

• Customization options can make troubleshooting and support responses more challenging. (Source)
• The feature set may lack the depth and stability of specialized AI solutions. (Source)
• Occasional technical issues, including the inability to pause call recordings, may disrupt certain workflows. (Source)

Talkdesk’s pricing

$110/month per user for CX cloud voice services 

Talkdesk is suitable for 

Enterprises and global businesses needing scalable, multichannel, AI-powered voice automation.

5. Cognigy

Cognigy helps you automate and improve customer and employee interactions. Its flagship product, Cognigy.AI, empowers businesses to create virtual agents that deliver personalized, multilingual, and real-time customer experiences.

Cognigy’s key features 

• Multilingual capabilities: It supports over 100 languages with real-time translation, allowing businesses to engage with a global customer base.
• Low-code development: Cognigy.AI offers a user-friendly, low-code interface, making it accessible for technical and non-technical users to design and deploy conversational agents. 
• Real-time agent assistance: The tool provides real-time agent support and features like sentiment analysis, live translation, and automated recommendations, improving agent efficiency.

Cognigy’s pros

• Easy to use, web-based graphical user interface. (Source)
• The platform requires no coding expertise, making it an efficient option. (Source)
• Offers a robust library of out-of-the-box integrations for seamless connectivity with other tools. (Source)

Cognigy’s cons

• Building custom extensions can be difficult for non-technical persons. (Source)
• A few parts of the implementation documentation to implement new features are hard to find. (Source) 
• The reporting dashboard is a little outdated. (Source)

Cognigy’s pricing 

Custom pricing is available on reaching out to their sales team.

Cognigy is suitable for

Enterprises looking for advanced conversational AI to automate customer service, streamline support processes, and integrate with existing systems.

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Use cases of AI voice agents

Thinking about using AI phone agents for healthcare, finance, or just better customer service overall? Let’s explore how businesses across industries are already putting them to work.

1. Customer service

With 71% of Gen Z preferring live phone support, businesses can’t afford long wait times or robotic responses. 

Verizon tackled this by integrating Google AI voice agents trained on over 15,000 internal documents to assist human reps. This resulted in a 40% increase in sales. (An example of how you can use AI voice assistants for sales too!)

You can do the same (and more) with Plivo’s AI voice agents. Plug in your CRM or knowledge base and your agents will deliver personalized, context-rich conversations that convert.

Alt text: An image showing the Plivo AI voice agent assisting a customer

They can become your customers’ digital shopping assistant recommending products or a financial guide helping them invest wisely.

2. Finance

Finance is among the most highly-regulated industries. That’s why AI voice agents are increasingly being used not just for handling loan applications, eligibility checks, and routine queries but also for improving security.

JPMorgan Chase introduced AI voice assistants in 2024 to help verify callers and flag suspicious transactions, cutting down manual verification time and improving security during inbound calls.

If you’re a growing business without the budget or bandwidth of a bank, Plivo makes it easy to get started. You can build and launch without complex dev cycles and automate everything from loan eligibility flows to fraud detection triggers.

3. Healthcare

Agentic AI is shaping patient care by sending appointment reminders, monitoring patient health, and prescribing treatments. 

In 2024, MUSC Health launched “Emily,” an AI voice agent powered by SoundHound’s Amelia to handle appointment scheduling and patient inquiries. It reduced wait times and improved the experience for both patients and staff.

While many AI voice agents can streamline patient care and provider care routines, they may miss out on compliance. 

With Plivo, you can easily build voice agents that manage patient scheduling, send follow-ups, and securely access EMR data. Since Plivo supports HIPAA-compliant workflows, you get automation and peace of mind.

It also helps healthcare providers who need specific information. They can simply ask the AI voice agents, ”What medications is this patient taking?”, and the agent retrieves precise and relevant details.

4. Operations and logistics

In logistics, delays, last-minute changes, and miscommunication can disrupt entire workflows and drive up costs. 

Take Uber Freight, for example. They use AI-driven platforms to optimize truck routing by factoring in traffic, weather, and road conditions, leading to better delivery times and guaranteed pricing.

AI voice agents can bring similar efficiency to your operations. From automating delivery confirmations and driver check-ins to sharing real-time route updates and notifying customers, voice automation can address the operational hiccups that eat into your margins.

Just pinpoint the friction points before investing in AI voice agents.

5. Travel and tourism

With the AI travel market projected to reach $13.38 billion by 2030, AI voice agents are transforming how customers plan and manage travel.

One of OpenAI’s seventeen use cases includes helping users plan an entire weekend getaway, from booking flights to recommending local experiences. It’s like having a personal travel agent available 24/7.

You can also build voice agents to handle high call volumes, reduce wait times, and provide travelers with instant, personalized support without adding pressure on human agents.

Here’s why Plivo’s AI voice agents stand out on top 

Unlike AI agents that answer FAQs, route calls, or perform specific tasks, Plivo's voice AI agents engage, convert, and delight customers across industries.

Think of them as digital coworkers: one handling support tickets, another qualifying leads, and a third nudging customers toward a sale, all at once.

Suppose a lead calls your business asking about loan eligibility; the voice agent checks their details in your CRM, walks them through the application criteria, and even books a callback with a human advisor if needed. You can connect them with your internal systems to move conversations toward specific business outcomes.

Plus, getting started with Plivo AI voice agents is super easy:

• Sign up on Plivo.
• Create your AI Agent for Voice, SMS, WhatsApp, Chat, or RCS.
• Plug in your knowledge base (FAQs, product info, support docs).
• Connect your platforms like Shopify, HubSpot, and Salesforce.
• Go live and let the agent start engaging.

As more businesses demand personalized, outcome-driven communication, Plivo represents the future of AI voice agents. Whether your business falls under finance, healthcare, e-commerce, or travel, they will support you at every step of the customer journey.

Contact us to learn how Plivo’s AI voice agents can support your voice automation needs.

Voice commerce is a $421.7 billion opportunity.

Yes, more than 27% of U.S. consumers made online payments with voice assistants instead of manually browsing multiple screens and navigating the checkout process. Devices like Amazon Echo, Google Home, and Samsung SmartThings now act as virtual shopping assistants.

With the number of voice search users anticipated to reach 157.1 million by 2026, voice commerce opens up a faster purchasing channel. For businesses, this means a higher conversion rate, stronger sales, and streamlined customer support.

In this blog post, we’ll explore voice commerce, how it works, and its benefits for your business.

What is voice commerce?

Voice commerce, or v-commerce, is a technology-driven shopping experience that allows customers to search for, purchase, and manage orders using voice commands. It reduces the reliance on screens and keyboards during the buying process.

The technology relies on two components: smart speakers that convert speech into digital commands and AI assistants that interpret these commands and take action. Customers can shop hands-free while cooking, driving, or multitasking.

How does voice commerce work?

The process starts when your customer speaks a command into voice-enabled devices. While it seems simple on the surface (the customer speaks and the device responds), the technology performs several steps to complete each task. These steps include:

• Converting speech to actionable data: Your customer's spoken command gets captured and converted to text through automatic speech recognition (ASR) algorithms. For example, when they say "buy new headphones," the system captures each word.
• Understanding customer intent: The system analyzes this text to understand what your customer wants. It breaks down the command to identify the action (buying) and the product (headphones). This involves natural language processing (NLP) to interpret the meaning behind the words.
• Finding the right products: Once the system understands the intent, it searches your product database or online store for relevant items. It pulls up matching products, prices, and availability.
• Creating the right response: Then, the system creates a response based on its findings. If multiple headphone options exist, it might ask for more specifics about the price range or features your customer wants.
• Completing transaction: The customer can then confirm their choice, and the system completes the transaction — adding headphones to the cart, processing payment, or scheduling the delivery.

When you implement voice commerce for your business, pay attention to the following:

• Speech recognition must handle different accents and background noise.
• Your product database needs clear categorization for accurate matching.
• Response systems should sound natural while providing accurate information.

Plivo’s AI voice agent makes integrating voice commerce simple. The platform combines three models: speech-to-text (STT) to convert customer voice to text, large language models (LLM) to understand customer intent, and text-to-speech (TTS) for natural responses.

Here's how an interaction with Plivo’s AI voice agent flows:

Customer: "I want to buy a new dress."

AI voice agent: "What style or color are you looking for?"

Customer: "A red cocktail dress."

AI voice agent: "We have red cocktail dresses in stock. What size do you need?"

Customer: "Medium."

AI voice agent: "Found a medium red cocktail dress. Ready to check out?"

Customer: "Yes."

AI voice agent: "Order confirmed. Delivery in three business days."

Each question narrows down options until the customer finds exactly what they want. The system handles real-time conversations with minimal latency and can process and respond to mid-speech interruptions.

Plus, you can train it on your product database and business rules to deliver relevant, contextual responses.

You also control the tech stack behind these interactions. Integrate Plivo with your preferred tools for speech recognition (like Deepgram), language processing (OpenAI), and voice generation (ElevenLabs).

Benefits of voice commerce for business

Let’s now look at what voice commerce means for your business.

Increased key sales metrics

Voice assistance commerce will claim nearly 30% of all e-commerce revenue by 2030. It directly impacts the sales metrics and drives growth through:

• Increased conversion rates: Instead of manually searching for items, customers have to speak to get instant tailored recommendations. This makes shopping more intuitive and reduces drop-offs, leading to a higher conversion rate.
• Reduced cart abandonment rates: Many customers abandon carts due to lengthy or complex checkout processes. Commands like “Buy this now” or “Complete my order” will reduce friction and promote seamless shopping experiences.
• Improved customer lifetime value (CLV): Simplified reordering of previous purchases increases sales frequency and long-term customer retention. Customers can simply say, “Reorder my protein powder” or “Buy the same shampoo as last time.”
  
  • Impact:
    
    • Reduces effort, making repurchasing quick and effortless
    • Customers stick with the brand due to convenience
    • More frequent purchases → Higher CLV

For example, Starbucks integrated voice ordering through Amazon's Alexa for customers to place orders via voice commands. This led to a 16% higher monthly revenue per user from customers who used the feature.

Reduced support cost

Voice commerce reduces support costs as it handles routine customer inquiries with ease. Your support team can focus on complex issues while the voice system manages common questions about order tracking, store hours, and product information.

The system operates 24/7, so customers get immediate answers without waiting for support staff. This self-service approach cuts call volumes and support queue times. Plus, voice assistants can manage multiple customer conversations simultaneously, eliminating additional staffing costs.

Improved customer experience

82% of customers report that personalization drives brand choice. With tailored recommendations and natural conversations, voice agents let customers connect with your brand on their terms.

For example, Domino's virtual voice ordering assistant, Dom, handles customized orders, suggests additions, and finds the best deals.

Beyond convenience, voice commerce helps collect direct customer feedback to improve your service. Customers can quickly share their thoughts through simple voice commands, helping you understand and address customer needs faster.

Challenges of voice commerce

Voice commerce brings three core challenges you need to consider.

Technological complexity

Voice commerce relies on expertise in NLP and voice recognition technology to get started. The system must accurately capture and convert voice commands to text, even with different accents and noisy backgrounds. Misinterpretations of customer queries can affect the entire brand's reputation and reduce customer satisfaction.

Invest in advanced NLP and machine learning algorithms to improve performance. Partnering with a voice-first vendor like Plivo gets the task done through high-quality, low-latency audio and context-aware interactions without a hitch.

Security concerns

Voice commerce shoppers often worry about their data being recorded, stored, and potentially shared with third parties since AI handles sensitive customer data.

This system requires extra security layers for data protection and purchase verification. Businesses must address potential vulnerabilities to prevent fraud or unauthorized access through sophisticated encryption techniques.

Integration challenges

Your voice platform must connect with your e-commerce infrastructure, inventory management, payment processing, and customer data systems. The system should also sync with your product database for accurate pricing, availability, and descriptions.

While platforms like PayPal support voice transactions, many payment systems and banks don't offer voice commerce capabilities yet.  This can slow implementation and limit your growth potential until more providers adopt voice technology.

Measures to make voice commerce the next big thing

Voice commerce relies on advanced technology, but making it right doesn’t have to be complicated. Let’s look at measures to ensure its success and drive customer engagement.

Boost discoverability with voice search SEO

Voice search behavior differs from text — your customers speak in full sentences of 6-10 words. They ask, "Show me high-performance running shoes under $100" instead of "running shoes." So, connect your catalog with search engines and optimize product descriptions for these longer, conversational searches.

With 18% of global consumers using voice shopping weekly, discoverability improves when you optimize for natural speech patterns.

Streamline purchases with voice-activated shopping

Set up quick voice checkout flows and minimize steps between product discovery and purchase.

Nike launched Adapt BB shoes through Google Assistant. Fans bought the entire stock in six minutes using voice commands during an NBA game halftime. The launch proved voice shopping can drive quick sales when you make purchasing effortless.

Deliver hassle-free support with voice AI

Train your voice AI on common customer issues. Build responses for tracking, returns, product specs, and shipping questions. Update the system with new products and policies. For example, 1-800-Flowers runs voice self-service for customers to track orders, change delivery details, and check FAQs. This support channel works 24/7, letting customers get help when they need it.

Track voice commerce performance

Set clear metrics for your voice channel and use insights to refine your strategy. Track voice-activated sales, search volume, and support requests. Monitor how voice affects customer behavior. Do they order more often? Place bigger orders? Buy different products?

Analyze patterns and optimize voice interactions to improve customer engagement and maximize ROI. Voice support cuts operational expenses, and self-service options reduce agent workload. This automated ordering speeds up sales processing.

Turn customer insights into smarter strategies

Update your voice features based on user needs. Fix common pain points, add requested features, and remove unused options.

Estée Lauder's voice-enabled makeup assistant (VMA) collects user input during key moments of the experience. Customers share thoughts through voice commands or the feedback menu. Their app updates reflect direct user feedback.

Voice commerce then, now, and beyond

From basic speech recognition to sophisticated shopping systems, voice commerce has evolved so much. Here’s a timeline of the evolution:

• IBM's 1961 "Shoebox" could understand just 16 spoken words.
• In 1971, Carnegie Mellon's "Harpy" system processed 1,000 words through DARPA funding.
• The real breakthrough came in the 1980s when Dragon Systems brought speech recognition to personal computers.
• The 2010s marked the shift to mainstream voice commerce adoption:
  
  • Apple's Siri (2011) introduced voice assistance to millions of iPhone users.
  • Amazon's Alexa voice assistant (2014) transformed voice shopping by connecting speech recognition with e-commerce.
  • Google Assistant (2016) joined the voice commerce market, driving competition and innovation.

Today, voice commerce is no longer used just for single-store transactions. Businesses can now integrate with multiple voice platforms — Alexa supports transactions for Walmart, Best Buy, 1-800-FLOWERS, and Starbucks. Customers only need to link their retail accounts to start voice shopping.

REI Co-op, Redbox, and eBags also use the platform to distribute deals and track orders.

Apple Store handles peer-to-peer payments through Siri. Walmart's mobile app tests hands-free shopping, order scheduling, and voice-based customer support.

The market shows strong growth potential. Research projects voice commerce to grow at a CAGR of 24.34% annually from 2024 to 2030. That means v-commerce is slowly becoming a necessity to stay competitive for businesses.

Explore voice commerce with Plivo’s AI voice agent

Launch, scale, and manage voice commerce through Plivo’s AI voice agent, which offers 99.99% uptime and 16kHz audio quality for clear conversations along with:

• Human-like interactions: Keep emotion and accent in conversations. Voice detection creates a natural conversation flow
• Context-aware responses: Provide relevant answers with AI that learns from your business knowledge base
• Flexible tech stack: Connect any STT, LLM, or TTS system
• Low-latency audio: Process conversations in real time with minimal delays
• Backup protection: Reroute networks reroute in under 2 seconds during outages
• Voice activity detection: Track speech onset and end for smooth conversations

Guide your customers through product selections, deliver personalized recommendations, and close sales on auto-pilot. Contact us to get started.

Natural language processing (NLP) works behind the scenes in places you might not even notice — filtering spam emails, customer service chatbots, and even accurate Netflix recommendations. It’s woven across industries and is rapidly evolving, with the market projected to hit 156.76 billion by 2030.

It's natural to wonder whether NLP is too complex or worth integrating into your systems. This guide offers five digestible NLP steps so you can understand how the technology works and whether it’s a good fit for your business.

What is NLP?

Simply put, NLP lets a machine understand, interpret, and respond to human language, written or spoken. It's the reason voice assistants listen to your commands, chatbots answer your queries, and search engines predict what you’re looking for even before you finish typing.

The NLP process is powered by two key components.

Natural language understanding (NLU) helps machines decode what humans mean, even if the content isn't totally clear. For example, customer support chatbots use NLU to recognize when a user is frustrated (based on words like “poor service” or “I need help now”) and escalate the issue appropriately.

Once the machine understands what the user is saying, natural language generation (NLG) generates a response in a way that sounds natural. Instead of just responding with pre-set phrases, the system personalizes the response based on the user’s request, offering logical next steps, similar to how a human agent would.

Here’s a quick rundown of the stages of NLP:

• Splits sentences into smaller chunks (tokenization in NLP) for easier processing.
• Identifies keywords, grammar, and structure to understand context.
• Detects names, dates, locations, and brands (e.g., virtual assistants retrieving order details).
• Determines if a message is a question, request, or complaint for accurate chatbot/voice assistant responses.
• Assesses tone and emotions to gauge customer satisfaction in chats.

To better understand NLP techniques, let’s go through the most common everyday NLP applications.

Most common everyday NLP applications

Along with autocorrecting and filtering spam emails, NLP is most commonly used in the following use cases:

• Chatbots and virtual assistants: NLP enables AI chatbots in customer service to understand and respond to human language, improving customer support and user engagement. These virtual assistants handle tasks like answering FAQs, scheduling appointments, and providing 24/7 customer service, mimicking human interactions to improve efficiency.
• Language translation: Tools like Google Translate use NLP to provide real-time multilingual support. You use this to communicate with global customers and break language barriers in customer service.
• Sentiment analysis: How does a machine know when a caller is frustrated, angry, or simply uninterested in your product? Sentiment analysis scans customer reviews, support tickets, or even social media mentions to determine if the feedback is positive, negative, or neutral. You can use it to gauge customer opinions.
• Speech recognition and voice AI: Speech recognition converts spoken words into text which helps businesses with real-time transcription, AI-driven interactive voice response (IVR) responses, and improved call routing. An advanced ASR (automatic speech recognition) tool like Plivo also masks inappropriate content in transcriptions and improves speech recognition accuracy by providing a list of hint words expected from the caller.

Now that we know about the most basic everyday NLP applications, let’s understand the five NLP steps in detail. 

5 steps in natural language processing

Let’s go through the five steps in NLP with examples.

Step #1: Lexical analysis

Text preprocessing in NLP precedes lexical analysis as it undergoes cleaning, tokenizing, and structuring raw data to make it readable for NLP models.

A study emphasizes that understanding grammatical structures and keywords is vital for chatbots to provide coherent and relevant responses in real-world situations. Lexical analysis helps NLP do so, making it one of the most important natural language processing steps.

It converts a sequence of characters into a sequence of tokens. This tokenization in NLP deciphers and segments languages into units (lexemes), such as sentences, phrases, and words.

Some words can stand alone, like “cat” or “jump”. These are free morphemes because they don’t need any extra help to be complete words. However, then there are bound morphemes, which have to latch onto something else to make sense. For instance,  “replaying”:

• “re-” (a prefix meaning “again”)
• “play” (the root word that holds the meaning)
• “-ing” (a suffix showing it's happening right now)

Neither of these words can exist alone, they always need a root word to stick to.

Machine learning in AI plays an important role in lexical analysis by helping NLP systems continuously improve their ability to identify and segment words accurately. When NLP analyzes text, it goes through a process to understand these layers, which helps understand word meanings, grammatical structures, and even how words change depending on context.

Lexical analysis teaches AI to deconstruct language the way the human brain does, but faster.

Step #2: Syntactic analysis

Syntax is the foundation of language, it’s how words and phrases come together to form meaningful sentences. Syntactic analysis (or parsing) lets NLP systems understand sentence structure and relationships between words rather than analyzing them in isolation.

This ensures that AI-powered chatbots, smart IVR systems, and voice assistants interpret user queries correctly.

When NLP performs syntactic analysis, it:

• Identifies sentence structure: Breaks a sentence into subject, predicate, objects, clauses, etc.
• Determines relationships between words: Determines which words depend on or modify others.
• Checks for grammatical correctness: Ensures the sentence follows valid language rules.

Syntactic analysis is important for chatbots and virtual assistants to improve customer experience with smart IVR. When a customer says, “I need help to reset my password”, the system uses syntactic analysis to recognize:

• “I” as the subject
• “need help” as the action
• “resetting my password” as the specific request

This structured understanding helps the AI respond appropriately, directing users to the right solution without confusion or misinterpretation.

Step #3: Semantic analysis

Semantic analysis in NLP deciphers meaning based on context, intent, and sentiment. The same word or phrase can imply different things depending on how it's used, and semantic analysis ensures AI comprehends these nuances accurately.

For instance, if a caller says, "I need to cancel my order because I wasn’t happy with the last one," a basic AI might fixate on the keyword "cancel" and proceed with the request.

But a Plivo-powered voice agent with semantic analysis understands the full context. It detects dissatisfaction from "wasn’t happy with the last one" and responds empathetically:

• “I’m really sorry about your previous experience. Let’s make this right.”
• Apart from processing the query, it might offer a resolution: “How about a 20% discount on your current order as an apology?”

Semantic analysis helps voice agents understand natural conversations instead of just keywords. This context-aware approach makes customer interactions more human, but you can also use these voice transcriptions for customer analytics to make informed decisions.

Step #4: Disclosure integration

Discourse integration helps NLP models grasp the broader meaning of conversations by considering previous sentences for context. This ensures more accurate interpretations and reduces confusion in AI-driven interactions.

For example, in a customer support chat:

Caller: "I lost my credit card yesterday."

Bot: “I’m sorry to hear that. Would you like to report it as lost or request a replacement?"

Caller: “Cancel it.”

Without discourse integration, the AI might struggle to understand whether the user wants to cancel the report or the card itself. By analyzing the conversation history, it correctly determines that "cancel it" refers to the lost card and proceeds accordingly.

This is important for businesses to automate customer interactions, and ensure smarter, context-aware responses in finance, healthcare, and beyond.

Step #5: Pragmatic analysis

Pragmatic analysis interprets meaning based on context, tone, and real-world knowledge rather than just literal word definitions so that the conversations feel natural and relevant. For instance, when a user asks, "What's the price of your premium subscription plan?"

The bot responds with, "Sure, our premium starts at $50 per month.”

Now, if the user simply responds, "That's a little steep," the bot automatically suggests, "Would you like to explore our standard plan starting at $30?"

While the user doesn't explicitly mention they want to explore a lower-priced option, pragmatic analysis recognizes the implied concern and suggests an alternative.

Businesses benefit from this by providing better customer engagement, fewer misunderstandings, and more effective automation.

While the steps in NLP help make customer experience better, it’s not all pros. 

Challenges and future advancements in NLP

One of the biggest NLP challenges is the bias in AI models.

Since AI learns from human data, it can reflect societal biases, leading to unfair or misleading outputs. MIT researchers developed a technique that reduces bias in AI models while preserving or even improving their accuracy for fairer and more reliable AI decision-making.

Another challenge is understanding regional dialects and slang. Many NLP models struggle with informal speech, code-switching, and cultural nuances, making accurate interpretation difficult in multilingual or diverse environments.

Ethical concerns, such as misinformation, privacy risks, and deepfakes (AI-generated content that falsely mimics real people) add to the complexity.

Looking ahead, context-aware AI conversations will improve chatbot and virtual assistant interactions, making them more natural and relevant. Real-time speech translation is also advancing, aiming for easy, culturally aware translations without robotic phrasing. As NLP evolves, voice integration in conversational AI will focus on making AI communication more inclusive, ethical, and human-like.

How Plivo's AI-powered voice agents advance intelligent  conversations

Keeping up with customer queries can be overwhelming, especially as your business grows. Long wait times, repetitive questions, and overworked support teams aren’t exactly a route to greater customer experiences.

This is where AI-powered voice automation comes in.

With a system that instantly understands customer requests, responds in natural language, and even recognizes 27 languages to serve a diverse audience in place, keeping your customers happy becomes easy. That’s what Plivo’s AI voice agents do.

They streamline customer interactions with features like real-time transcription, smart IVR for self-service that’s ideal for healthcare, banking, and routine queries, and a secure, scalable voice agent with built-in message redaction and compliance. 

Plus, Plivo lets you integrate any speech-to-text provider, large language model (LLM), or text-to-speech (TTS) engine, giving you complete control over your AI experience.

Thousands of businesses use Plivo to reduce support load, improve response times, and keep customers happy, without disrupting workflows. Contact us to see how our solutions can make your communication systems more efficient.

In 2024 alone, Intercom’s artificial intelligence (AI) voice bot, Fin, tackled 13 million customer questions for over 4,000 businesses. And it’s not just chatbots. Gartner predicts that by 2026, 30% of enterprises will automate over half of their customer interactions, up from just 10% in 2023.

Clearly, AI voice intelligence in customer service is leading the charge.

However, despite its benefits, many business owners still wonder: will automation make customer interactions feel robotic? More importantly, how do you use voice AI in a way that actually improves customer experience?

This guide will break it all down — what voice intelligence is, how businesses use it, and the real impact it has on customer interactions across industries.

What is voice intelligence?

Voice intelligence is an AI-powered system that can understand, interpret, and respond to spoken language the way humans do.

Unlike conventional interactive voice response (IVR) systems, which rely on rigid menu-based navigation, natural language processing (NLP) in voice AI listens to callers' words, processes their intent, and delivers relevant responses.

For example, Apple's Siri goes beyond setting alarms or reminders and asks follow-up questions to maintain context in a conversation. Similarly, Google’s Gemini can summarize web pages, suggest replies, and help you with booking appointments. 

But how does it actually work?

How voice intelligence works

Voice intelligence combines AI tools like NLP, machine learning, and real-time AI-powered speech analysis to analyze calls, voicemails, and digital conversations, helping businesses respond faster and more accurately.

This means they can catch key issues, offer better support, and even automate certain interactions, without losing the human touch.

Let’s break this down with a use case.

User A calls their bank’s support line after noticing an unfamiliar charge on their credit card.

Speech recognition converts voice into text

At the core of voice intelligence lies speech recognition. It converts spoken words into text and allows AI-powered voice agents to "listen" to a caller.

Going back to our example where the user calls their bank, here’s what happens behind the scenes:

When they say, "I see a charge I don't recognize on my card.", the speech recognition gets to work. It transcribes the words into text, identifies individual words, corrects minor pronunciation errors, recognizes the accent, and captures the intent without losing context.

Plivo's automatic speech recognition (ASR) takes it a step further. It filters inappropriate content in transcriptions, supports speech recognition in 27 languages, and offers pre-built models for different industries.

So if the user uses rash language like “I’m pissed off with this bank”, the ASR identifies “pissed off” as inappropriate and removes it from the transcript. At the same time, it correctly interprets 'charge' in the context of financial transactions, avoiding confusion with alternative meanings such as charging a device.

NLP understands intent and context

NLP in voice intelligence recognizes accents, slang, and even sentiments. It actually grasps the meaning behind those words the way humans do.

When the user says, "I see a charge I don't recognize on my card," the system, using NLP, identifies key terms like “charge” and “don't recognize” to understand that the user is reporting a potentially fraudulent transaction.

If such an interaction has occurred in the past, machine learning in voice intelligence learns from it and improves its ability to detect predictable phrases like "unauthorized charge," "fraud," etc. It also detects a spike in customers calling about fraudulent charges in the future.

AI-driven decision-making determines the right response

After the call gets transcribed and analyzed, AI taps into past interactions to offer a faster, personalized resolution. For instance, if the user has travel alerts active on their account, AI determines the charge is legitimate and reassures them.

If the user expresses urgency with phrases like, "It's serious", or "I need to talk to a specialist now", AI picks up on the tone and escalates it to a human fraud specialist. 

But even the smartest voice AI can only make good decisions with high-quality voice data.

Plivo’s call analytics plays a vital role by identifying audio issues like poor network conditions, background noise, or low call clarity. It correlates audio quality metrics with device metadata and network conditions so that businesses can ensure AI decisions are based on accurate, uninterrupted speech data.

This leads to better fraud detection, sentiment analysis, and overall customer experience.

Text-to-speech (TTS) helps bots sound human-like

While voice recognition AI converts the call into text, text-to-speech (TTS) does the reverse. It converts the AI-generated responses into natural, human-like speech.

TTS gauges intent adapts to different accents, and structures responses naturally. Instead of a robotic reply, it might say, “I understand that an unfamiliar charge is concerning. Let me check that for you.”

For urgent cases, it might say, “Let me transfer this call to our fraud specialist right away.”

Unlike stiff, pre-recorded messages, TTS adapts to each conversation in real-time, making AI-powered voice responses feel more human and helpful.

This brings us to our next question: what are the benefits of voice intelligence?

Benefits of voice intelligence for businesses

Now that we know how voice intelligence works, let’s understand its benefits for businesses.

Scalability: Never leave a customer on hold

Voice intelligence enables businesses to manage customer interactions efficiently, regardless of call volume. AI-powered tools ensure immediate attention for every customer, eliminating long wait times and improving satisfaction.

For example, a retail business may experience a surge in inquiries about shipping, returns, or product availability during the holiday season. Voice intelligence deploys agents to answer common questions like "What is your return policy?" or "When will my order arrive?" for multiple customers at the same time.

For calls requiring human assistance, the AI gathers details such as order numbers or the nature of the issue beforehand, helping representatives resolve concerns more quickly.

What’s more, AI can offer callbacks instead of making customers wait on hold, keeping frustration levels low and satisfaction high.

Reduced costs: Say goodbye to excess customer support hiring

Since AI-powered voice agents handle repetitive inquiries, it reduces the workload for human agents. Businesses don't need to hire extra staff to manage call spikes. Plus, during high call volumes, it absorbs extra demand, keeping customer service intact without additional payroll expenses.

AI-powered voice agents also learn instantly and require no training, further reducing the overhead of onboarding new employees.

Increased customer satisfaction: Make context-aware conversations in multiple languages

Become, a financial technology company, integrated Plivo's Browser SDK to enable high-quality voice calls within their web application. This integration allowed account managers to communicate effectively with customers worldwide, totaling over 6 million minutes of calls, thereby improving customer relationships and operational efficiency.

Voice intelligence, however, isn't just for call centers.

It can enhance learning, customer support, and global communication, even for a language-learning platform. The technology can use voice agents to provide real-time translations and personalized tutoring, translate and simplify complex concepts in their preferred language.

Improved compliance: Save a fortune on penalties

Industries like finance, healthcare, and telecom require call recording and documentation to comply with laws like the Health Insurance Portability and Accountability Act (HIPAA), Payment Card Industry Data Security Standard (PCI-DSS), and General Data Protection Regulation (EU) (GDPR).

A provider like Plivo ensures businesses can automatically record and store calls securely. Its APIs implement custom monitoring and analytics solutions tailored to your compliance needs. So, it helps improve customer experience while ensuring your business complies with the necessary regulations.

Real-world use cases of voice intelligence

Let’s look at how businesses are putting voice intelligence to work, improving customer experiences, and solving everyday challenges.

1. Faster customer support and personalized shopping assistance  

AI-powered voice agents can handle order tracking, refunds, and cancellations without human intervention.

When a customer asks, "Where's my order?", the AI agent fetches real-time tracking updates instantly, reducing wait times and improving customer satisfaction.

With voice AI analytics, businesses can also gain customer insights and offer personalized shopping assistance. Voice agents guide customers through product selections, suggest tailored recommendations, and even complete purchases.

2. Streamline routine financial services

As per a 2024 survey by Bain & Company, financial services firms are experiencing notable productivity gains through AI adoption. For instance, voice intelligence software in financial services can offer instant account information, transaction processing, and personalized financial advice anytime, anywhere to the customers.

It can also become a financial advisor for the customer and recognize trends and patterns to suggest smart investment strategies.

3. Improve patient outcomes

Voice intelligence in healthcare helps providers deliver secure, and HIPAA-compliant interactions to ensure a smoother journey for everyone.

You can easily provide preliminary health assessments, medication reminders, and appointment scheduling with a personalized AI touch.

4. Make customers feel included

For educators and institutions, AI-powered voice solutions reduce the need for multilingual tutors, making education more scalable and cost-effective.

Even better? They can act as personalized tutors, adapting to each student’s learning style, and providing clarifications, explanations, and feedback in real time.

Take the first step toward integrating voice intelligence with Plivo-powered AI voice agents 

Integrating voice intelligence into your communication systems can feel daunting, especially with technical bottlenecks, and the risk of sounding too ‘robotic’. 

However, Plivo-powered AI voice agents make it easy. It lets you integrate any speech-to-text provider, LLM model, and text-to-speech provider of your choice, giving you the flexibility to build natural, high-quality AI voice interactions.

Plus, Plivo delivers on two key pillars of exceptional customer interactions, crystal-clear voice quality and reliability. With 99.99% uptime and high-quality 16kHz audio, it ensures reliable communication across 220+ countries and territories.

Whether you use voice agents to preserve emotions, emphasis, and accents, or to handle mid-speech interruptions, Plivo-powered AI voice agents reduce latency and provide real-time responsiveness.

Since the future of voice intelligence lies in context-aware, emotion-driven interactions, it’s time to switch to a provider that offers all that and more. Contact us to learn how thousands of businesses optimize their workflows without disrupting customer experience with Plivo.

Experts project the global Voice over Internet Protocol (VoIP) services market to reach USD 361.53 billion by 2031. This growth is driven by businesses seeking more flexible, cost-effective solutions for their communication needs. However, to meet customer expectations, VoIP call quality must remain front and center.

With a staggering 93% of customers expecting their issue to be resolved on the first call, businesses are under increasing pressure to provide efficient customer service.

Good VoIP call quality can make or break the customer experience. In this blog post, we will explore 11 steps to ensure your VoIP calls show just how committed you are to great service.

The inside scoop on call quality

Call quality refers to the clarity and reliability of a voice call when using a VoIP phone system. It includes factors like audio clarity, the absence of delays or dropped calls, and the communication flow between the caller and agent.

More than technical metrics, good VoIP call quality ensures a smooth experience, customer satisfaction, and business success.

Poor call quality often results from choppy audio or dropped calls caused by network congestion, insufficient bandwidth, or a poor internet connection. For more in-depth insights, let’s understand the process of VoIP data transmission and what affects the call quality in a VoIP system.

Process of VoIP data transmission over calls

VoIP calls turn sound waves into digital signals and packetize them for transmission before reconverting them into sound waves as they reach the other end. Here are four key steps involved in data transmission:

• Signal conversion: When you speak into the VoIP device, it captures your voice as an analog signal. VoIP codecs turn the analog signal into digital data and break it into small digital packets.
• Data transmission: These digital packets are then transmitted over the internet. Every data packet travels the fastest route possible.
• Signal reassembly: As it reaches the other end, the VoIP system decodes and reassembles the data packets into an analog audio stream.
• Protocols and codecs: Session initiation protocol (SIP) handles the call lifecycle from connection to end, while an audio codec compresses and decompresses spoken words.

The source(s) of your VoIP problems

VoIP call quality issues arise when there’s a failure in packet transmission.

As mentioned, analog sound gets converted to packetized digital data. These voice packets travel through the user’s device, the router, the VoIP provider’s media server, and the carrier network before reaching the recipient's device.

Each step in this process presents an opportunity for call quality issues. Network issues such as packet loss, bandwidth usage, and insufficient internet connection speed can result in poor call quality.

To improve VoIP call quality, you’ll need to ensure smooth packet transmission. While you cannot control issues on the recipient's end, you can follow best practices for call quality for your browser software development kit (SDK).

Types of VoIP call quality issues

Here’s a list of some common call quality issues faced in VoIP systems.

• Audio latency: Latency can cause delays in audio delivery, leading to awkward timing where participants may speak over each other.
• Jitter: Jitter in VoIP calls means skipped audio or silent gaps caused by irregular packet delivery, which disrupts the rhythm of conversation.
• Packet loss: Missing or delayed data packets, often due to bandwidth restrictions or unreliable internet connections, can result in missing audio.
• Poor network connections: Weak or unstable internet connections can degrade call quality, causing latency, jitter, and packet loss.
• Codecs used: Low-bandwidth codecs may compromise audio quality.
• Quality of Service (QoS) policies: QoS settings that don’t prioritize VoIP traffic cause network congestion, which negatively impacts call quality.

How to improve VoIP call quality when hiccups strike

Here are 11 steps to enhance VoIP performance.

1. Monitor call quality

Monitoring VoIP call quality is essential for identifying and resolving issues.

Track call quality metrics such as jitter, packet loss, and mean opinion scores (MOS) with tools that give visibility into network health. You can also enable logging for individual devices to track events of errors. Network management software can help monitor bandwidth usage.

Improving VoIP call quality also involves enhancing the customer experience once calls are connected. Actively respond to complaints about choppy audio, echoes, or dropped calls.

Consider upgrading VoIP equipment and implementing an effective IVR (interactive voice response) system to streamline customer interactions. When cross-referenced with objective metrics, subjective issues can help identify and resolve call quality problems.

For instance, VoIP service providers like Plivo offer Call Insights to track key metrics.

Plivo’s Call Insights help assess call quality for packet analysis of voice traffic. The Call Summary Dashboard summarizes performance data and segments calls by subaccount, geo-location, hangup details, carrier network, and device metadata.

It also lets you collect end users’ feedback with the Call Quality Feedback API to determine the root cause of frequently reported issues.

Using this feature, you can obtain detailed call statistics of each call to troubleshoot VoIP issues. Additionally, it becomes convenient to discover patterns by drilling down the key vectors influencing quality and correlate them with audio quality issues.

2. Upgrade your router

Most small and medium business routers are basic and require little maintenance. If you're scaling your business and experiencing VoIP call issues, consider upgrading your router. Choose a router compatible with SIP and VoIP for better call quality and high-speed connectivity.

An upgraded router offers advanced features, such as QoS settings to prioritize VoIP traffic, implement jitter buffers, and segment voice traffic with a virtual local area network (VLAN). These features ensure smoother voice communication by reducing latency and packet loss.

3. Increase bandwidth

Voice packets pass through routers and servers before reaching the other end, and any congestion in the route can degrade VoIP call quality.

Network congestion occurs when multiple applications use bandwidth simultaneously, much like traffic on a busy highway, slowing down communication.

Opt for higher bandwidth if your network cannot handle several devices and users. This offers speedier data transfer when multiple users or devices are logged in simultaneously, lowering congestion and increasing overall VoIP call quality.

4. Configure QoS

Another way to beat congestion is to prioritize VoIP calls on your network.

Network prioritization involves adding dedicated lanes for VoIP calls, ensuring that voice packets have the bandwidth to travel smoothly.

Configure QoS to prioritize VoIP calls over other data types on your network to reduce VoIP latency and packet loss. Setting up QoS for VoIP involves configuring the router’s bandwidth settings to optimize VoIP network settings, which may require assistance from an IT professional.

5. Set up a jitter buffer

Another way to beat network congestion or packet loss is by setting up a jitter buffer. A jitter buffer helps smooth VoIP call quality by collecting, storing, and sending voice packets at even intervals.

While the jitter buffer may introduce a slight delay due to packet processing time, it will reduce interruptions caused by packet delivery inconsistencies. More stable and clear voice communication significantly enhances the call experience.

6. Segment traffic with a VLAN

A VLAN enables devices of any geographical location to share a connection to specific servers.

Segmenting voice traffic with a VLAN prioritizes VoIP calls over other data, improving call quality even in large or distributed networks. Therefore, VLAN is a network prioritization method for businesses operating in multiple locations or operating a VoIP call system with remote workers.

Most enterprise networks support VLAN configuration, so check with your network provider to see if this option is available.

7. Purchase a high-quality headset

Headsets can also be a VoIP call quality hazard as they may be prone to connectivity and sound issues.

Some headsets may not be compatible with certain operating systems, while some have advanced features that detect long silences and disconnects. In addition, certain headsets also have microphones that pick up incoming audio, prioritize one-way audio, and cause sound distortion.

Purchase high-quality wired VoIP headsets as wireless headsets can have adapter and driver configuration issues that cause static or white noise. What’s more, headsets with noise-canceling features can ensure call quality even in noisy environments.

8. Choose the right codec

The codec you choose for your VoIP phone system will determine bandwidth usage and affect call quality. Codecs like G.711 offer excellent sound quality but consume more bandwidth. Others, like G.729, focus on maximizing compression to reduce bandwidth usage at the cost of some audio quality.

Consider the impact of these codecs during peak usage times — G.729 may result in a few lost packets. Still, it may provide better VoIP bandwidth management, improving overall call quality.

9. Avoid WiFi

WiFi coverage is often spotty, especially in larger office spaces with network congestion. It wasn’t designed for real-time applications like VoIP, and multiple devices on the network can compete for bandwidth, degrading call quality.

If you’re facing VoIP call quality issues, consider a wired ethernet connection over WiFi for a stable internet connection.

Ethernet connections help avoid interference from other devices, such as smartphones and microwaves, which can cause crackling or humming sounds during calls.

10. Prioritize mobile phone traffic

VoIP systems offer the flexibility of mobile apps, allowing users to make VoIP calls from mobile phones. While some features may be limited to desktop apps, mobile VoIP calls provide remote work advantages for sales and support teams.

In terms of voice quality, VoIP calls made on a mobile phone are similar to voice-over-IP methods like FaceTime audio.

A strong LTE connection is usually sufficient for maintaining high VoIP call quality. You can prioritize VoIP traffic on your mobile device by disabling cellular data for other apps to improve VoIP call quality.

Pro Tip: Avoid relying on shared internet connections due to potential network congestion when using public WiFi.

11. Improve call handling with a well-designed IVR

A well-designed IVR system is essential for improving VoIP call quality and enhancing customer satisfaction.

With Plivo’s PreAnswer feature, you can engage callers before they connect to a live agent. Offering helpful information, promotions, or answering FAQs while they wait keeps them informed and reduces the strain on agents. This leads to shorter wait times, fewer call drops, and a hassle-free experience.

Creating an intuitive IVR menu prevents confusion and frustration. It’s also vital in businesses that handle sensitive information like banking. Integrate clear, concise, and easy-to-navigate IVR menus to reduce call wait times and improve customer satisfaction significantly.

Keep testing and optimizing the IVR for peak traffic to ensure quick routing and smooth call handling during busy times.

VoIP calls made seamless with Plivo

If your team faces issues with VoIP call quality, try these steps and eliminate stuttering, echoes, dropped calls, or other communication disruptions.

Plivo’s Voice API offers VoIP services with powerful features like call forwarding, call recording, and call analytics. It integrates voice calls into your browser and mobile applications to ensure exceptional call quality. The advanced call insights facilitate:

• Proactive call quality monitoring
• Quick identification and troubleshooting of VoIP issues
• Detailed call statistics
• User feedback gathering

For a smoother communication experience, contact us today and see how Plivo can improve your VoIP call quality.

Voice AI technology drives a $12 billion market projected to quadruple by 2029. Major companies such as Amazon, Apple, and Google have already demonstrated its potential. Today, voice AI is much more than simple command systems and preset responses — it handles complex conversations, grasps context, and provides human-like interactions at scale.

For business leaders and developers, this translates to automated customer support, multilingual communication, and accessible digital experiences. With 157 million users expected to rely on voice agents by 2026, companies need to integrate Voice AI to stay competitive.

Here's your guide to voice AI's components, applications, and business impact.

What is an AI voice?

AI voice is a technology that simulates human-like speech from text inputs or other sources using deep learning models trained on real voice data. It creates natural-sounding voices that can be customized based on gender, age, accent, and emotions.

Using AI voice agents in businesses means you slash support costs and offer 24/7 availability — like Bank of America's virtual assistant Erica, which handles over 2 billion customer interactions.

With AI voice, you can automate customer service, handle high call volumes, and provide consistent service quality across all customer interactions through voice bots and IVR systems. Modern AI voice tools analyze speech context, understand user intent, and generate appropriate responses without human intervention.

How do AI voices work: A detailed breakdown

AI voice systems convert human speech into actionable computer responses through five core components — each handles a specific task in the voice interaction chain. Here’s a walkthrough of these components.

Automatic speech recognition (ASR)

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ASR is the first step to speech-to-text conversion. When users speak to a voice assistant or call customer service, ASR converts their speech into text in a few steps:

• Audio capture: First, ASR captures audio through your microphone and splits it into tiny segments of 10-20 milliseconds. It then converts these segments into spectrograms — visual maps that show sound frequencies over time.
• Sound analysis: Deep learning models analyze these spectrograms and match them to phonemes (basic speech units). The system's neural networks break down the audio, compare it against existing speech patterns, and identify matching words from its data pool.
• Noise management: ASR filters out background noise and audio glitches that could affect accuracy before processing the text.
• Speech processing: Finally, a language model combines the identified phonemes into words and sentences. It checks the probability of word combinations to ensure that the transcription makes sense in the user's target language.

Modern ASR handles diverse accents, speaking speeds, and background conditions. The flexibility makes it effective for customer service, voice commands, and automatic transcription.

Natural language processing (NLP)

Next, NLP converts the text from ASR into meaningful actions. Here's how:

• Text breakdown: NLP splits user input into analyzable chunks and runs a syntactic analysis (checking word patterns and sentence structure). 
• Meaning extraction: The system collects the core meaning from text and analyzes it semantically (context and word relationships) to understand the user intent.
• Entity recognition: NLP spots and labels key information like customer names, account numbers, dates, and locations to process requests.
• Intent classification: The system identifies the specific action a user wants to take, whether it's checking a balance, scheduling an appointment, or filing a complaint.
• Sentiment analysis: NLP looks at word choice and phrasing to gauge user emotions and helps systems respond appropriately to satisfied or frustrated customers.

Dialog management

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Dialog management links the voice AI components together. It controls voice AI conversations through two core processes:

1. Dialog modeling

The system records essential information to maintain the conversation state. It tracks discussed topics, stores user-provided details and identifies missing information needed to complete requests. This data is often structured into slots in a form populated with values gathered during the interaction. 

For example, in a hotel booking conversation, it tracks check-in dates, room preferences, and guest information until all required fields are complete.

2. Dialog control

The system determines the next action based on the collected information. It decides when to request missing details, verify unclear inputs, or proceed with task completion. Confidence scores guide these decisions; high scores lead to task execution, while low scores trigger clarification requests.

For example, if the check-in date is unclear when booking that hotel room, the system will ask for confirmation before proceeding.

Natural Language Generation (NLG)

The process converts system decisions into human-friendly responses. It begins when NLG receives input from the dialog management system. This input contains the intent and relevant information needed for the response.

The system then structures this data into a logical sequence and applies grammar rules specific to each language.

For example, when recommending a product, the system converts structured data like: recommend(product="Premium Plan", features="24/7 support, unlimited calls") to natural responses: "Would you like to try our Premium Plan with 24/7 support and unlimited calls?"

Text-to-speech Synthesis (TTS)

Text-to-speech technology converts written text into spoken words. It follows these steps:

• The process starts with text analysis, where the system breaks text into processable units.

• Next, it converts these units into phonetic symbols that represent speech sounds.
• The system then adds prosody — the patterns of rhythm and sound in speech. This includes marking where to pause, which words need emphasis, and how to adjust tone.
• Finally, deep learning models generate audio waveforms that produce the actual speech output.

Modern TTS systems support different languages and voices and process thousands of requests simultaneously.Putting it all together: The voice AI workflowVoice AI creates a continuous cycle of speech processing and response generation. Here's how the components connect:

1. ASR captures user speech and converts it to text. When a customer asks, "What's my account balance?" ASR processes the audio and produces text output.
2. NLP analyzes this text to identify the user's intent — for example, checking account balance. It gathers key details like account references and command types.
3. The dialog manager takes this processed request and checks if it has all needed information, retrieves the account balance from the connected system, and decides how to present this information to the user.
4. NLG formats the response and turns raw data like "balance: $1,245.50" into a clear statement: "Your current balance is $1,245.50."
5. TTS converts this text response into spoken words delivered to the user through speakers or phone lines.

Plivo's Voice API lets you add call functionality across devices through server-side software development kits (SDKs) in multiple programming languages. You can create interactive voice response (IVR) menus with speech recognition, set up real-time coaching for agents, and detect answering machines for smart responses.The platform processes voice interactions in 28 accents across many languages and supports dual-channel call recording with encryption. Debug logs monitor performance, while webhooks keep you updated on on-call status.

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AI voice applications

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Voice AI is shifting business operations across industries with measurable impact. Let’s look at how these sectors leverage this technology.

Customer service

Voice AI balances automating interactions and conversation quality to deliver stellar customer services to businesses. The technology uses IVR systems to understand

natural language, route calls based on intent, and resolve common issues without human agents. These systems collect customer data, maintain conversation context, and transfer complex queries to live agents with relevant background information.

And the business impact — voice bots will reduce agent costs by $80 billion by 2026, with market growth projected at 23.3% through 2028.

Voice AI handles essential functions like intent detection, authentication, and technical troubleshooting. Companies see measurable results, too — 24/7 availability, simultaneous processing of thousands of conversations, and consistent response quality.

Plivo CX delivers these results with enterprise-grade IVR systems and voice bots that integrate with major platforms like Salesforce and Zendesk.  With this, you can:

• Integrate your voice AI with existing customer relationship management (CRM) systems.
• Monitor performance through real-time analytics, coach agents live, and optimize operations with 99.99% uptime.
• Deploy voice bots that process queries across 220+ countries and territories.

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Also read: How to Use AI to Analyze Phone Calls and Improve Customer Experience

Content creation

AI voice technology improves content production across multiple channels. For example:

• Podcasting creators use AI generated voices to convert written scripts to audio episodes without studio equipment.
• Marketing teams use AI voice generators for consistent brand messaging through video voiceovers, multilingual ads, and customer service greetings.
• Companies clone brand ambassador voices (with consent) for message consistency at scale.
• Publishers and authors turn books into audiobooks in days rather than weeks.

Accessibility

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Users with disabilities need more inclusive digital experiences. Yet, 98% of websites fail basic accessibility standards, which limits access to millions of potential users.

Businesses can fix this through AI voice to help users with visual impairments access digital content through advanced screen readers. Unlike traditional robotic voices, AI voice creates natural-sounding speech that improves comprehension and engagement. This matters for businesses because:

• Users spend more time with accessible content.
• Companies meet Web Content Accessibility Guidelines (WCAG) compliance requirements.
• More customers can access digital services independently.

AI voice converts written materials into audio formats for education and training to support employees with dyslexia or reading challenges.

Online retailers use AI voices to read product descriptions and reviews to make shopping accessible to visually impaired customers. The result? Increased sales plus brand loyalty among previously underserved groups.

Entertainment

AI voice helps reduce costs and speed up content delivery across multiple formats. The key applications are:

• Gaming: Create character voices and test dialog variations during development.
• Film and TV: Dub content in multiple languages and maintain continuity when human voice actors aren’t available.
• Advertising: Produce regional ad variations with a consistent brand voice.
• Animation: Generate character voices without multiple studio sessions.

Benefits of AI voice for businesses

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Here’s what AI voice means for your business:

• Streamlined customer support: Customer support teams handle cases faster through smart voice routing. The system qualifies leads, sorts urgent cases, and directs conversations to specialized agents based on intent recognition.
• Refined customer experience: Support teams receive prioritized call queues based on real-time voice sentiment analysis. The NLP engine learns from each interaction to refine responses, boosting customer satisfaction (CSAT) scores.
• Personalized and automated customer interactions: The platform learns to build customer profiles from each interaction. Voice patterns and conversation history shape responses so each conversation feels natural and informed.
• Reduced customer support costs: Voice automation cuts training costs and agent onboarding time. As the system manages routine conversations through NLP engines, new team members handle complex queries sooner.
• Used by differently-abled customers: Screen reader integration and voice commands make your services work for everyone. Customers with different abilities complete transactions independently using ASR technology.

Also, with Plivo-powered context-aware AI Voice Agents trained on knowledge base of choice, businesses can effortlessly manage everything from scheduling appointments and sending reminders to offering tailored financial advice. Boost your sales with AI-driven shopping assistance, break down language barriers in education through real-time translations, and provide outstanding customer support without a hitch. The possibilities are endless!

For your customers, this means:

• Self-serve: Customers get things done through simple voice commands. They check order status, update accounts, and solve issues without ever touching a keypad or screen.
• One-time data collection: Customers share information once, and you use it everywhere. The voice system securely stores customer data and shares it across your support channels so no one repeats their story.
• Less friction in communication: Voice AI removes communication barriers by letting customers speak in their language. They get instant answers 24/7 without navigating complex phone menus or facing language problems.

The future of AI voice technology and ethical considerations

Voice AI now combines multiple technologies to solve real business challenges. Some emerging voice AI trends include:

• Advancements in NLP create systems that learn your preferences and work habits, making every interaction count. Support teams can now communicate globally as these systems handle multiple languages, accents, and dialects.
• Voice systems work with cameras and motion sensors to understand what you see and do. Visual AI and gesture recognition let you control devices naturally in smart environments.
• The technology reads vocal patterns to detect your mood through tone analysis and deliver empathetic responses.
• The system learns your work patterns and routines through user profiling to respond based on contextual awareness (user location, schedule, and recent activities).
• Voice cloning lets you customize how the system speaks — use your own voice or choose from a library of options. The voice adapts to match different situations and conversations.
• Edge computing processes voice commands directly on your device, giving you instant responses and offline functionalities. Your data stays local instead of going to cloud servers, protecting privacy.
• Internet of Things (IoT) integration predicts what you need based on your habits and responds without you having to activate it first. One voice interface controls all your smart devices.

For those building and deploying these systems, privacy is crucial. Voice data needs data security protocols and consent policies. Voice cloning and sentiment analysis need guidelines to protect users and their data.

Your success with voice technology depends on getting this balance right. Build in privacy and security from the start, set clear guidelines, and you'll create systems your users trust and value.

Transform your communication strategy with Plivo Voice AI

With Plivo, there’s no room for privacy and security concerns. The enterprise-grade Voice AI platform provides the security protocols and infrastructure to launch context-aware voice bots while protecting customer data. You get immediate access to:

• AI integration: Connect with any STT, TTS, or LLM provider through simple APIs for maximum flexibility.
• Rapid recovery: Switch to backup networks in less than two seconds during outages to maintain operations.
• Dialog management: Maintain conversation context and natural flow across all interactions.
• Performance analytics: Track and optimize voice bot performance through detailed metrics and insights.
• Crystal-clear audio: 16kHz high-quality audio for smooth interactions.
• Unmatched reliability: 99.99% platform uptime for uninterrupted service.

Automate your support operations with Voice AI. Contact us to build your voice AI strategy.

Voice Artificial Intelligence (AI) is no longer just a futuristic concept — it’s here, reshaping how businesses engage with customers. With the conversational AI market set to jump from $13.2 billion in 2024 to $49.9 billion by 2030, voice integration is transforming industries.

From handling customer queries to automating workflows, voice AI redefines e-commerce, healthcare, finance, and many industries. It’s not just about commands anymore; voice AI now delivers context-aware, natural interactions that transform customer experiences with real-time assistance and a sense of personal touch.

In this article, we’ll discuss how voice integration in conversational AI drives change, its industry applications, and the advantages it offers for businesses and customers.

What is conversational voice AI?

Conversational voice AI focuses on voice-based interactions between users and machines under the umbrella of conversational AI. It uses speech recognition and natural language processing (NLP) to understand and respond to voice commands. Speech recognition converts spoken words into text, while NLP uses algorithms to understand the intent of the converted text.

The response then reverts to speech through speech synthesis.

Various devices, such as smart speakers, mobile apps, interactive voice response (IVR) systems, and even in-car voice systems, use conversational voice AI to improve user engagement and operational efficiency.

Sneak peek of conversational AI: The OG

Conversational AI comprises technologies and algorithms that create lifelike conversations between machines and users. Users interact with these technologies via:

• Customer support chatbots found in apps or on websites
• Smart assistants like Google Assistant or Amazon Alexa
• Customer support voice bots that handle queries over the phone

Conversational AI systems process voice commands, understand user queries, and provide relevant responses using NLP, machine learning (ML), and speech recognition.

The rise of voice technology in conversational AI

🗣️: Ok Google, navigate to the closest gas station.

🗣️: Hi Siri, remind me to pick up groceries at 10 AM.

🗣️: Alexa, set a timer for 5 mins.

Google, Amazon, and Apple have transformed voice-based interactions using conversational AI.

Voice integration in conversational AI provides a natural and intuitive way to interact compared to traditional text-based methods. It mirrors human conversation, making it faster and easier for users to communicate with AI systems.

With 97% of mobile users relying on AI voice assistants, voice-based conversational AI is now a regular part of daily life. Businesses are adopting voice AI to offer seamless, hands-free experiences as consumers grow familiar with voice commands.

Looking under the hood: Conversational voice AI and customer service

Conversational AI in customer service helps businesses offer instant support to customers and handle routine tasks with ease. Voice-enabled conversational AI answers queries, processes requests, and speeds up customer interactions. This improves efficiency, reduces wait times, and lets agents focus on complex issues.

Let’s explore the different applications of conversational AI that can amp up the game of customer experiences across the board.

Smart call routing

Voice assistants with conversational AI analyze customer inquiries and route calls to the right department.

Unlike traditional IVR systems that rely on keywords, voice AI maximizes IVR menu efficiency through natural language understanding (NLU), allowing customers to speak naturally.

Voice assistants also capture customer details, like names, account numbers, and requested services, giving agents all information upfront. This saves time for both customers and agents.

Omnichannel support

While text, email, and chat are standard communication channels, voice adds immediacy and a personal touch to customer service interactions, which other channels often lack.

With voice AI in their omnichannel support system, businesses can offer seamless platform transitions. For instance, a customer might use voice commands in-store to check product availability and continue the conversation online later.

This unified experience provides a smooth customer journey and boosts customer satisfaction and brand loyalty.

Pro Tip: Add customizable voice IVR to your omnichannel support and build a better brand perception.

Streamline authentication

Automating customer authentication with voice technology and conversational AI reduces time and costs. Additionally, voice authentication using NLP is a more cost-effective alternative to voice biometrics authentication, providing an equally smooth experience.

Simplify troubleshooting

Voice assistants powered by conversational AI and chatbots can handle much of the troubleshooting process, automating common issues and often resolving them without involving an agent. This reduces agents' time on repetitive tasks and boosts customer service operations.

If the bot can’t resolve the issue, it transfers the customer to a human agent. It also gives the agent a detailed record of already taken troubleshooting steps to ensure a smoother handoff.

More agent efficiency = Better customer experience.

Better security and reliability

In industries like finance and healthcare, security is paramount.

Voice AI integration provides robust security measures, such as encrypted voice recordings and secure data transmission. It protects sensitive customer data while meeting industry regulations.

A dependable voice platform with voice AI reduces downtime and ensures continuous service through a well-designed IVR system. For example, banking IVRs improve security and customer interactions and ensure a smooth, secure flow of information.

Multi-language support

Voice technology with conversational AI allows businesses to support multiple languages and create a more inclusive and accessible customer experience. For example, Plivo’s AI voice agents support speech recognition in 27 languages and their regional variants.

Using speech recognition technology, businesses can engage with diverse customer bases worldwide and offer personalized support in various languages. It helps companies enhance customer interactions and improve overall satisfaction.

Hands-free experience

98% of websites don’t provide basic accessibility features, limiting access to millions of users with disabilities. Voice-enabled conversational AI supports Web Content Accessibility Guidelines (WCAG) and allows more customers to access digital services independently.

Voice technology powered by conversational AI uses advanced speech synthesis to support users with visual impairments. It enables interaction with content through natural-sounding speech, making information easier to understand and more engaging.

These systems convert text into audio, providing access to online shopping, education, and training in a more inclusive way.

Personalization

Conversational AI platforms leverage customer data like browsing history and purchase behavior to offer highly personalized recommendations in real-time. For example, voice assistants can narrow down a general query about a mobile phone to a specific model based on the customer's preferences and budget.

Voice-enabled AI bots, like Plivo-powered voice agents, also guide customers from discovery to checkout, helping them:

• Compare products
• Suggest complementary items
• Offer specific discounts
• Upsell based on past purchases

Unlike text-based bots, voice agents are more personalized, adding a human touch to customer interactions.

Conversational voice AI for different industries

When a customer calls, they want to feel valued and understood. Conversational AI with voice recognition technology puts the customer at the center of the experience.

Here’s how voice AI transforms industries and enhances customer interactions across sectors.

E-commerce

Caption: Personalize customer’s shopping experience with Plivo-powered voice agents

Alt text: Image depicting Plivo-powered AI bots recommending products based on user input

E-commerce customers want quick responses and 24/7 support. If they don’t get it, they may choose a competitor.

While chatbots work well for tasks like answering FAQs or checking order status, voice integration in conversational AI transforms customer service and creates standout shopping experiences by:

• Assisting customers with product selection
• Offering personalized recommendations
• Automating the sales process

Integrating voice agents in customer relationship management (CRM) systems also provides real-time updates, such as order status, with just a voice command. Businesses are better suited to provide a 24/7 personalized shopping experience with quicker response times and higher customer engagement.

Education

AI voice integration with multilingual support can empower inclusive learning experiences in the education sector with personalized tutoring. Voice agents can instantly support students by providing real-time translations and remove language barriers by clarifying complex terms in their preferred language.

This integration reduces the need for multilingual staff, making learning more accessible for global students.

Healthcare

No industry values prompt responses more than healthcare.

Voice integration in conversational AI healthcare sectors improves customer experience, provides timely care, and improves operational efficiency. It simplifies patient care and delivers personalized support through:

• Medication reminders 
• Appointment scheduling
• Preliminary health assessments

In addition, voice agents help healthcare providers automate tasks, improve medication adherence, and lighten their workload, making services more efficient and patient-focused.

Finance

Conversational voice AI supports financial sectors with a forward-thinking approach. Voice agents improve the customer experience by offering quick, accurate responses without wait times. Banks use voice agents to:

• Automate routine tasks
• Provide instant account updates
• Process payments
• Deliver personalized financial advice 24/7

Approaches to deploying conversational AI for voice integration

When you're ready to implement voice-integrated conversational AI, you'll discover several ways to design, build, and deploy a voice assistant. Some approaches may appear cost-effective at first but quickly turn into obstacles, complicating deployment or causing user dissatisfaction.

Here are three primary methods for deploying conversational AI for voice:

1. Partner with a voice-first vendor

Partnering with a voice-first vendor like Plivo is the most efficient and effective way to deploy conversational AI for voice applications.

One of the key advantages of working with a vendor like Plivo is the speed and efficiency it brings to deployment. Instead of building a voice assistant from the ground up, businesses can leverage Plivo’s pre-built solutions and technical expertise. This accelerates time-to-market and reduces the burden on in-house development teams.

Plivo's platform is designed to handle the complexities of voice integration, such as managing call flows, ensuring compliance with global telecommunication standards, and delivering high-quality audio. Additionally, its APIs are highly customizable, allowing businesses to tailor their solutions to fit specific use cases.

2. DIY with a third-party platform

Another approach to deploying conversational AI for voice is using third-party platforms like Google DialogFlow or Amazon Lex. They can handle natural language processing and speech algorithms for your applications.

However, this option may limit control. Performance can vary based on language or application needs, especially in voice-heavy use cases.

3. Port chatbot technology into voice

Many businesses start with chatbots and attempt to convert them into voicebots.

Doing so involves integrating speech recognition and text-to-speech capabilities with the chatbot’s existing NLP engine. This allows the system to understand spoken input, process it, and deliver relevant responses through audio.

Nevertheless, transitioning from a text-based chatbot to a conversational AI voice agent can be challenging.

Chatbots are primarily designed for text-based communication, and the conversion process often leads to issues with speech recognition and intent detection, resulting in subpar performance. It also requires careful attention to voice-specific nuances, such as accommodating variations in accents, ensuring accurate speech synthesis, and optimizing dialogue flow for spoken interactions.

Note: While porting chatbot technology to voice can save time and resources compared to building a voice assistant from the ground up, it may lack the full customization and voice-centric features provided by dedicated voice-first solutions.

Get started with Plivo

Whether integrating AI features into your existing systems or considering third-party solutions, conversational voice AI empowers teams, drives efficiency, and enhances customer experience.

Plivo’s Voice API offers flexibility and seamless integration with your preferred speech-to-text, text-to-speech, and language model providers. It connects directly with OpenAI’s RealTime API through simple integration endpoints for instant deployment. Context-aware AI Voice Agents trained on custom knowledge bases support businesses to:

• Schedule appointments and send reminders
• Offer personalized financial advice
• Boost sales with AI-driven shopping assistance
• Break language barriers with real-time translations
• Deliver exceptional customer support with accurate responses

Plivo’s platform also offers industry-leading performance metrics, including 99.99% uptime reliability and low-latency global connectivity.

To explore the potential of Plivo-powered AI voice agents, contact us today.

“Press 1 for Billing,” “Press 2 for Account Information” — you’ve probably heard this before, right?

That’s an interactive voice response (IVR) system, and it does a lot more than just guide callers through a menu. It’s often one of the very first brand impressions your customers receive. 

But why does it matter so much? Because your customers crave autonomy. In fact, research shows that over 80% of consumers want more self-service options, and many are calling for these solutions to be smarter.

A well-designed IVR doesn’t just route callers to the right department — it understands their needs and can even boost your team’s efficiency.

In this guide, we’ll explain IVR’s meaning, how it works, and tips to optimize it for a seamless customer experience. Let’s begin!

What is an IVR?

IVR is a telecommunication technology that automates customer interactions over the phone. It allows callers to access information, make requests, or complete tasks using voice commands or menu inputs — no live agent required.

The technology uses pre-recorded messages, speech recognition, and dynamic menus to guide callers to the information or service they need with ease. It's similar to a 24/7 virtual assistant that transforms how businesses manage customer interactions.

Here’s what an IVR can do:

• Automatically answer and route calls to the right department.
• Offer self-service options, like checking account balances or appointment scheduling.
• Collect caller data for smoother follow-ups.
• Integrate with databases to deliver personalized responses.

Think of IVR as your business’s first line of defense. It handles repetitive tasks while seamlessly forwarding complex issues to human agents based on factors like agent skills, call volume, or even time of day.

Industries like banking, healthcare, and customer support rely on IVR systems to:

• Improve accessibility with 24/7 availability.
• Reduce wait times for callers.
• Manage high call volumes.

How does IVR work?

IVR systems are versatile and can operate on both public switched telephone networks (PSTN) and voice over Internet Protocol (VoIP) networks.

At their core, IVR systems rely on a combination of components to function effectively:

• A Transmission Control Protocol/Internet Protocol (TCP/IP) network: Ensure connectivity to both the internet and internal intranet systems.
• Databases: Provide necessary data for IVR applications to deliver accurate and relevant responses.
• Web/application server: Host IVR software applications, typically written in VoiceXML. These applications can handle various tasks, such as managing contact centers, conducting outbound sales calls, or performing speech-to-text transcription.

From these components, three primary types of IVR systems are made:

Touch-tone replacement

This system uses keypad inputs to guide callers. For instance, a prompt might say, "Press 1 to check your account balance," and the caller responds by pressing the corresponding number on their keypad.

Directed dialog

With this approach, callers are guided through verbal prompts based on their inquiries. For example, the system might ask, "Are you calling to check your account balance or update your contact details?" The caller then responds with "Check my account balance."

Natural language

The most advanced type, this system leverages speech recognition to understand more complex user inputs. A prompt like, "How can I assist you today?" allows callers to reply conversationally, such as "I want to check my account balance" or "I’d like to update my email address."

Let’s understand an IVR call flow with a simple example.

A customer calls a healthcare provider to book an appointment. The IVR system greets them with a friendly message and offers language options for accessibility.

Next, it presents a menu of choices, such as scheduling an appointment, checking the status of test results, or connecting with a live representative. The customer can either press the corresponding number on their keypad or say the desired option aloud.

The IVR system processes the input and takes the appropriate action. This might include providing pre-recorded information about:

• Available appointment slots.
• Transferring the caller to a scheduling agent.
• Collecting additional details like the patient’s name and preferred time.

Benefits of IVR for businesses

The IVR market is thriving, with North America expected to drive 40% of its growth in the coming years. Here are six main benefits of IVR for businesses:

1. Reduces operational costs

IVR systems for businesses save money by handling routine inquiries, reducing the strain on customer service agents. In fact, next-gen IVR solutions have shown to cut live-agent calls by over 10%.

Plus, they enable 24/7 service without additional staffing costs.

For enterprises, a single IVR system handles call flows for multiple applications, simplifying operations. Customizing IVR menus for each use case enables businesses to scale efficiently while maintaining cost control.

2. Improves first contact response rate (FCR)

Well-designed IVR systems for businesses can handle many inquiries on the first call. Research shows IVR self-service reaches a 74% FCR rate, and customers often prefer it over IVRs that just pass them along to live agents.

This success comes from handling simple tasks like confirming orders, checking balances, or viewing status updates — no human intervention needed.

3. Enables call routing and triage

Studies show that 44% of boomers, 30% of millennials, and 24% of Gen Z shoppers are likely to switch to a competitor after a single negative experience. Instead of risking that churn, use an IVR system to prioritize your most valuable callers and move them straight to the front of the line.

With smart triage and call routing technology, you can:

• Give VIPs top priority so they never wait without reason.
• Direct customers to the right team or agent based on location, priority, sentiment, intent, or language.
• Quickly review which callers are in the queue and what they need.
• Trigger dynamic changes to call priority or routing destinations as customers enter the queue.
• Seamlessly connect callers to the first available agent to speed up resolutions.

4. Provides personalized support

63% of customers want an IVR experience that speaks directly to their unique needs, not just a generic menu. They’re looking for personalization beyond superficial marketing approaches. IVR can help by offering:

• Language options that make callers feel understood from the start.
• Custom greetings that acknowledge their history with your brand.
• Tailored promotions and product suggestions that suit their past purchases or inquiries.

5. Enhances workflows

High call volumes can strain call centers, especially during busy periods. An IVR system eases the workload on agents and streamlines operations. Here’s how:

• Offer voicemail or scheduled callbacks instead of long wait times.
• Direct callers to the appropriate team or specialist.
• Guide callers to your website or present additional options via a recorded message.
• Deliver immediate answers to common questions through pre-recorded messages.

6. Helps understand customer behavior

IVR interactions generate valuable data on caller preferences, common inquiries, and recurring pain points. Analyzing these insights informs strategic decisions, enabling you to refine your services and better meet customer expectations.

IVR use cases

IVR systems play an important role across many industries, serving multiple functions. Here are some of the most common applications of this technology:

Auto attendant

When someone calls your number, they hear a simple menu. For example:

• Press 1 for Sales.
• Press 2 for Support.
• Press 3 for Billing.

It’s fast, smooth, and eliminates the need for a human operator to manage incoming calls.

IVR covers after hours too. It can automatically handle voicemails, ensuring no call is ever missed. This means your team can follow up promptly, leaving a great impression.

The result?

• Reduced workload for live receptionists.
• A polished, professional experience for your customers.
• Every call is handled with care, no matter the time of day.

Payments and banking

Banks use IVR systems to help customers perform tasks like checking account balances, making payments, or reporting lost cards without waiting for a representative.

For instance, when you call Wells Fargo, you’re prompted to enter your account or card number. The system then offers personalized options, such as reviewing transactions or checking payment statuses.

Support surveys

IVR systems for businesses aren’t just for managing inbound calls; they’re equally effective for outbound campaigns. Businesses and organizations can use them to automate surveys and gather customer feedback.

For example, a healthcare provider may use an IVR technology to remind patients of upcoming appointments and ask about their recent experience with services.

Similarly, a telecom company might conduct automated surveys to measure customer satisfaction after resolving a support issue.

Lead assignment and routing

An IVR system makes it easier to qualify leads and connect inbound sales calls to the right sales representative. It asks targeted questions to understand the customer’s needs, budget, or preferred products.

For example, an automotive dealership can use the IVR to route inquiries about new cars to a sales team specializing in that area, while calls about financing options are directed to a financing expert.

Key considerations for choosing an IVR solution

Choosing the right IVR solution for your business is a critical decision. Here are the key factors to focus on:

Customizable call flows

A customizable call flow lets you design personalized IVR experiences tailored to your customers’ needs. With this feature, you can create workflows that guide callers through specific communication channels based on their preferences.

Efficient call routing

The best IVR systems for businesses offer intelligent call routing capabilities. They can direct calls based on customer relationship management (CRM) data or predefined criteria to ensure each caller reaches the right agent.

Speech recognition and DTMF support

An effective IVR system should offer robust speech recognition and dual-tone multi-frequency (DTMF) capabilities. This allows customers to interact with the menu by speaking or pressing buttons, making the process intuitive and accessible for everyone.

Seamless integration

Look for an IVR system that integrates easily with your business tools — like payment processors, workforce management software, and CRM platforms. These integrations ensure the IVR has all the information needed to handle tasks without a hitch.

Comprehensive analytics

Strong call insights and reporting features let you track patterns and identify common customer queries. Use this data to make informed decisions, improve your service, and address recurring issues effectively.

Best practices to implement an IVR system

Here are five IVR best practices that help improve productivity and provide a great customer experience:

Keep the IVR menu simple

A successful IVR self-service system should be simple and user-friendly. Long and complicated menus can frustrate callers, leading to hang-ups.

Stick to a main menu with five options or fewer, while ensuring all essential needs are covered. Always provide a clear path to connect with a support representative if needed.

As an example, look at this IVR menu:

"Welcome to Zenith Tech Solutions:

• For technical support, press 1.
• For billing inquiries, press 2.
• To speak with a sales representative, press 3.
• To reach the HR department, press 4.
• To speak to an operator, press 0."

This menu is clear, relevant, and ensures that customers can reach a human representative when necessary.

Use audio streaming for customer insights

Audio streaming integrated with AI-based tools helps businesses:

• Deliver smarter voice-based services.
• Analyze conversations for deeper insights.
• Enhance user interaction.

Plivo’s Audio Streaming capabilities detect emotions like frustration or satisfaction during a call. If it senses an issue, the system can instantly adjust its response or transfer the customer to a live agent for a more personalized touch.

With Plivo, you can also build AI voice agents to handle common queries instantly, making customer service faster and more efficient.

Additionally, Plivo’s integrations enable real-time transcription to convert conversations into text seamlessly. Need multilingual support? Plivo connects with live translation tools, making it effortless to communicate during meetings or conferences in any language.

Optimize call queues

Waiting can be frustrating, but honesty and transparency can make the experience more bearable for customers. In fact, a survey found that 47.84% of customers feel estimates and updates significantly improve their waiting experience.

One way to handle this is by implementing an IVR solution with a callback feature. This prevents long hold times and helps customers continue their day while waiting for a response.

Another approach is to use IVR to handle low-priority calls and reduce average handling time (AHT). Directing callers to pre-recorded messages with helpful information can solve their problems efficiently.

For example, Plivo’s PreAnswer feature allows businesses to play custom caller tunes or automated messages after a call is transferred but before it's answered. It can be used in various ways.

For instance, if your team is frequently answering the same question, you could use this feature to play a pre-recorded message with an answer to this query.

If the caller gets the information they need, they can disconnect satisfied, letting your team handle more complex tasks.

Implement personalization

76% of consumers say personalized communication is a major factor when considering a brand. Plus, 78% are more likely to repurchase when they feel the content speaks directly to them.

This applies to your IVR system, too. Connecting your IVR to customer data facilitates customized experiences that make every interaction feel personal.

So, when a customer calls your helpline after recently booking a travel package. Instead of a generic greeting, they hear, “Hello, Sarah! We see you’ve recently booked a trip to Paris. Are you calling about your travel itinerary, or do you need assistance with something else?”

It’s about showing you understand what they care about. A personalized IVR system makes customers feel valued and turns routine calls into meaningful conversations.

Monitor and adjust regularly

Once your IVR system is up and running smoothly, it’s tempting to leave it as is. But businesses evolve, and so do their needs. Departments shift, processes change, and some may no longer exist.

To keep your IVR effective, regularly review and update your menus. Ensure they align with your current business structure and customer needs.

Don’t stop there — update greetings, hold messages, announcements, and any other pre-recorded messaging. These small changes ensure your IVR stays relevant and provides a seamless customer experience.

Improve your customer service with Plivo’s smart IVR

The world is rapidly shifting towards AI, and your customer support should too. Traditional IVR systems with rigid menus just aren't cutting it anymore. 

Smart IVR takes things to the next level by using artificial intelligence, contextual awareness, and data-driven insights to deliver more intuitive and personalized caller experiences.

Plivo is here to help you make that transition effortlessly. Our Smart IVR uses AI voice agents and advanced audio streaming to transform your traditional IVR into a smarter, more efficient system. 

This means faster interactions, reduced agent burnout, and happier customers — all while streamlining your operations.

On top of that, Plivo offers powerful features such as:

• AI-Powered functionality: Let customers speak naturally instead of pressing buttons. Our integration with Large Language Model (LLM), Speech-to-Text (STT), and Text-to-Speech (TTS) providers makes launching voice bots a breeze.
• Automated support: Handle routine inquiries automatically, freeing your team to tackle more complex issues.
• Crystal-clear audio: Deliver high-quality audio across 220+ countries and territories, ensuring smooth and professional conversations.
• Enhanced customer insights: Gain valuable data from interactions to refine your services and meet customer demands effectively.
• Fully customizable menus: Design multi-level menus tailored to your business needs, complete with personalized greetings using pre-recorded audio or text-to-speech technology.
• Easy setup: Simple APIs and XML integration allow you to quickly create and manage custom IVR workflows without hassle.
• Smart call routing: Direct calls based on input, agent skills, or even business hours, ensuring customers are always connected to the right person.
• Outbound IVR support: Custom menus for outbound campaigns like surveys or voting make engagement effortless. 

Plivo’s IVR system isn’t just a tool; it’s a way to enhance your customer service and streamline operations. Ready to elevate your communication? Contact us today to learn more!

A voice API is a tool that software developers use to make and receive phone calls programmatically. With a voice API, they can use various channels, phones, browsers, and virtual assistants.

 It connects web or mobile applications to the Public Switched Telephone Network (PSTN), enabling seamless voice communication without needing extensive telecom expertise, time, and developer resources.

Voice APIs are highly configurable, easily integrated, and scalable tools, providing cost-effective communication for businesses.

‍How much does a voice API cost? 

A voice API costs typically range from $0.003 to $0.014 per minute for outbound calls and $0.003 to $0.022 per minute for inbound calls, depending on call type, provider, and features. 

Prices may differ due to factors like infrastructure, service quality, and additional features like real-time analytics or automated routing. 

Using a voice API makes more financial and logistical sense for businesses than investing resources into developing advanced voice calling features from scratch. By choosing a best-in-class voice API provider, companies can integrate various voice capabilities with a shorter development span and achieve a better ROI. 

Plivo offers cost-effective solutions with competitive pricing while maintaining high-quality services.

Here’s a quick comparison of pricing for each type of voice call between Plivo and Twilio to give an idea of voice API cost structures and offerings.

‍How can a voice API give customers a better experience? 

Integrating a voice API enables businesses to offer personalized, efficient customer support services on browsers or apps with advanced voice features. It can help reduce voice call traffic and wait times in contact centers. These APIs can route calls efficiently through the phone network, including toll-free phone numbers, ensuring smooth call handling.

Unlike older inflexible phone network systems, a programmable voice API supports AI-powered virtual assistants that can receive calls 24/7, understand user requests, and guide customers through their queries as effectively as human agents. With voice recognition and text-to-speech features, customers can express themselves naturally and receive the assistance they need without delay.

The voice bot can also record calls and collect contextual data to prepare agents to resolve the issue when they take over quickly. This streamlined process saves time and preserves the unique, personal touch of voice calling.

Features like click-to-call, voice control, and hands-free interactions also increase flexibility, allowing users to have an interactive and engaging call. 

Wouldn’t it be nice to simply say the query out loud and receive a clear response instantly?

A voice API makes this possible by enabling your company to answer customers' questions instantly without navigating through endless clicks. Voice API seamlessly integrates voice solutions into browsers or apps to transform the customer experience. 

There’s more to it:

• Interactive and hands-free features: Customers can use click-to-call, voice commands, or hands-free interactions, enhancing convenience.
• Personalized customer support services: Offer tailored assistance with AI-powered virtual assistants and voice recognition features. These tools help customers articulate requests naturally and get relevant responses.
• 24/7 availability: AI-powered virtual assistants answer calls anytime, providing immediate assistance, even outside business hours.
• Enhanced agent support: Voice bots can record calls, gather context, and equip agents with the information they need to resolve issues swiftly when human intervention is required.

Voice APIs streamline communication and create a memorable, user-friendly experience that fosters trust and loyalty.

How can a voice API streamline communication processes?

A voice API makes interactions more efficient and aligned with business goals and needs. Here's how:

• Makes it easy for customers to connect: Unlike traditional voice calls confined to phone networks, a programmable voice API extends voice capabilities to an app or website. Users can use a click-to-call feature directly within an app or site.
• Adds efficiency to your team: Automating routine customer interactions allows voice bots to handle a significant portion of inbound calls. This reduces call traffic in the contact center, freeing human agents to manage complex or high-priority cases.
• Scales with business: As businesses grow, you can seamlessly expand voice-enabled services, ensuring consistent voice call handling without sacrificing quality. For example, businesses can use voice APIs to automate phone calls for marketing campaigns or appointment reminders.
• Supports developers: From a developer's perspective, a voice API integrates smoothly with other APIs and communication platforms. 
• Offers robust security: Programmable voice APIs often come with robust security features, including encryption and secure call record storage, in compliance with regulations like GDPR or HIPAA. 

Take, for example, CallHub.

They use Plivo's voice API to simplify communication for political campaigns, offering tools like power and predictive dialers. These features let campaigns reach voters efficiently, connecting them directly with representatives or leaving messages without manual effort. Browser-based calling also ensures volunteers' privacy, making it secure and straightforward for customers to interact.

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Choosing a voice API provider

Programmable voice APIs can range from basic functionality to feature-rich platforms that handle complex voice call flows and integrations. Here’s what to look for when evaluating a voice API provider:

Comprehensive call management features

A strong voice API should include fundamental voice call management functions to make, receive, and record calls, and global audio conferences. To ensure effective communication, look for APIs that offer configurable conference experiences, such as muting/unmuting participants, automatic call termination, and host controls.

Text-to-speech and accessibility options

Text-to-speech (TTS) is essential for both accessibility and user convenience. It converts text into spoken output, making automated systems more user-friendly, especially for multitasking or on-the-go customers. 

Ensure your provider's TTS capabilities support multiple languages and accents to cater to diverse customer needs.

Smart interactive voice response (IVR) systems

A voice API should enable the creation of intelligent, multi-level interactive voice response (IVR) systems that route calls efficiently. 

Smart IVRs can handle straightforward customer service tasks autonomously, incorporating:

• AI technologies for interactive experiences
• Intelligent call routing
• Integration with multiple channels
• Call recording and TTS capabilities

These capabilities help build customer-first IVR solutions that guide users seamlessly to the right department or agent.

Real-time call handling and notifications

Real-time features such as Answering Machine Detection (AMD) are invaluable for optimizing call strategies based on the type of response received. 

AMD helps identify whether an outgoing call is answered by a human or voicemail, which is especially beneficial for tasks such as lead follow-ups, customer updates, and automated voice surveys.

Integration with existing systems

The right voice API should facilitate integration with communication systems, including SIP-enabled hardware and software. 

This adaptability allows your business to maintain flexibility as communication needs evolve.

Audio streaming

Audio streaming, or media streaming, is a vital feature that sets advanced voice APIs apart. This functionality allows your application to deliver calls while duplicating call media to multiple recipients. It also enables real-time analysis and enhances features like sentiment analysis, conversational AI, call transcriptions, fraud detection, and voice biometrics.

Plivo stands out by offering all of these essential voice API capabilities. Moreover, it offers advanced features, such as:

• Play audio prompts: Plays pre-recorded audio files during a call, making it useful for IVR menus or announcements. This feature facilitates caller engagement and delivers professionalism in communication.
• Text to speech: Converts text into natural voice messages in various languages. It supports real-time updates like notifications, reducing dependency on pre-recorded audio and increasing flexibility.
• Dual channel call recording: Captures conversations with separate audio tracks for each participant. This allows for detailed analysis of interactions, making it ideal for call centers or compliance needs.
• Custom caller ID: Displays a specific phone number during calls, which builds brand trust and increases the likelihood of calls being answered. It’s particularly helpful for global and region-specific outreach efforts.
• Get digit input: Collects user responses via keypad entries, making it useful for gathering information such as account numbers or confirming choices during calls. It simplifies customer interactions and integrates effectively into IVR systems.
• Advanced call control: Gives businesses detailed control over call functions like transfer, mute, and hold. This capability supports smoother call handling and enhances customer support operations.
• Supervisor coaching: Allows supervisors to listen in on live calls and provide guidance without the caller being aware. This feature supports agent training and improves call outcomes as they happen.
• Call whisper: Plays a short message to the agent before connecting the call, providing context about the caller or the purpose of the call. It helps agents prepare better, leading to more tailored and effective support.

How does Plivo's voice API work?

Plivo's voice API is a robust framework that enables developers to manage voice communications programmatically with REST APIs to allow comprehensive control over call flows—from initiation to termination. 

Throughout a call's lifecycle, Plivo sends webhooks at various stages, prompting your application to respond with specific commands. This dynamic exchange between webhooks and responses provides granular control over call behavior, facilitating the creation of customized and efficient voice communication solutions.

What makes a good voice API?

A good API is easy to build. It offers flexibility and customization options to cater to different users’ needs and tailor a top-notch experience for your customers. 

Here’s what to look for:

SDKs and robust documentation 

A good voice API provider should offer developers comprehensive Software Development Kits (SDKs) and robust documentation to ease the development process. 

Plivo offers client SDKs for browser (JavaScript) and mobile (native iOS and Android) with no upfront costs. Plus, access extensive product documentation with quickstart guides, tutorials, and product overviews to cover various use cases.

Connect and control calls to any device 

Voice API should allow developers to build powerful voice workflows and integrate voice calling into web and mobile apps. 

With Plivo, you can connect phone calls over the PSTN to more than 200 countries without managing complex telecom carrier interactions. This flexibility extends to SIP-enabled devices and software, allowing seamless connection to your existing SIP infrastructure and enabling advanced communication features in the cloud.

Premium network

A premium network is essential for a voice API to deliver clear, uninterrupted audio quality, as it minimizes delays, reduces jitter, and ensures stable call connections. 

Plivo ensures premium voice quality through its Regional Points of Presence (PoPs), which reduce latency and maintain high call quality using one-hop, in-country carrier connections. 

Great developer support

Sometimes, a voice API can be complicated and needs assistance; make sure your provider offers 24x7 premium support backed by a consultative customer success team that provides the technical guidance and industry expertise developers need. 

Those additional support resources can  include:

• Extensive documentation and a rich knowledge base
• Up-to-date service status and product updates
• Regular product improvements and enhancements

Upgrade your business communication with Plivo's voice API

We've covered what a voice API is and what to look for in a provider—now it's time to put that knowledge into action. Upgrade your business communication with Plivo's voice API, a powerful, flexible voice API that meets your business needs.

If you'd like to receive customized rates with guided onboarding and premium support, get our volume prices. A team member will contact you to help determine whether an annual agreement suits you based on your personal use case.

Plivo’s simple, usage-based pricing model ensures that businesses only pay for what they use, making it a cost-effective choice.

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