I Tested 18+ Top AI Voice Agents in 2025 (Ranked & Reviewed)

After testing 18+ AI voice agents across sales and support workflows, here are my top 10 picks that sound natural, integrate easily, and deliver results you can track.

10 Best AI voice agents in 2025: TL;DR

1. Lindy: Best AI voice agent overall for automation, sales, and support
2. Vapi: Best for omnichannel voice automation
3. ElevenLabs: Best for realistic and expressive AI voices
4. Whisper by OpenAI: Best open-source speech recognition model
5. Bland AI: Best for creating customizable AI voice agents via API
6. Synthflow: Best no-code platform for building and deploying voice agents
7. Retell AI: Best for customer support and inbound call handling
8. CallHippo AI Voice Agent: Best for businesses wanting full-stack call automation
9. Cognigy: Best for large-scale enterprise voice automation
10. Dialpad AI Voice: Best integrated AI calling platform for teams

What is an AI voice agent? 

An AI voice agent is an AI-powered software system that uses speech recognition and natural language processing to have natural, real-time conversations with humans over the phone or other voice channels. 

Unlike older systems, it can understand context, handle complex interactions, and perform tasks like answering questions, scheduling appointments, or resolving issues without human intervention.

Some are great at answering common questions, some can route calls to the right person, and others can even follow up after a conversation.

You can think of it as a phone assistant that doesn’t sleep. 

It can handle simple stuff, stay polite no matter what, and save you from repeating yourself all day long. Whether it’s for support, sales, or just lightening your workload, it’s a huge time-saver.

Best AI voice agents in 2025

1. Lindy: Best AI voice agent overall for automation, sales, and support

What does it do? Lindy is a no-code voice agent platform that can take calls, hold real conversations, qualify leads, send follow-ups, and update your systems without human input.

Who is it for? Perfect for teams that deal with sales calls, support tickets, recruiting, or client onboarding.

Lindy handles real phone calls that sound genuinely human. You can assign it a task, give it a list of numbers, and it'll call each person one by one. It asks the right questions, listens to responses, and summarizes everything it hears without any manual input. 

Here’s an example. We set up a Lindy to handle inbound support calls. When someone calls in, Lindy answers, helps them out, and searches the internal knowledge base if needed.

After the call ends, it automatically logs the conversation, updates the database, and sends a summary to the team in Slack.

The entire process is built using a simple drag-and-drop flow, so no coding is required. You decide what happens when a call comes in, what Lindy should say, what to do after the call ends, and who should be notified.

Even better, it can run multiple calls simultaneously. So, while one Lindy is talking to someone, another is already on the phone with a different prospect.

This isn’t a chatbot pretending to make calls. It’s a fully functional voice agent that knows how to hold a conversation, get things done, and loop you in only when needed. Plus, you can get started with the pre-built templates, connect your workflows with integrations, and hop to Lindy Academy if you need help with anything.

Pricing

Lindy offers a free plan with 400 credits/month to test voice calls and basic features. The Pro plan starts at $49.99/month with 5,000 credits and up to 1,500 tasks. 

For unlimited phone calls and advanced features, the Business plan is $199.99/month with 20,000 credits and support for 30+ languages.

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2. Vapi: Best for omnichannel voice automation

What does it do? Vapi is a developer-focused voice AI platform that creates highly customizable voice agents.

Who is it for? Particularly suited for businesses that need customization, integration with existing systems, and want to handle high volumes of concurrent calls.​

After a week with Vapi, the first thing that hit me was how fast it feels. It’s built for developers, not beginners; everything is API-first and highly customizable.

I could route calls, handle interruptions, and feed context into other APIs instantly, which made it feel more like an engineering toolkit than a no-code app.

Using Vapi with GPT-4 and ElevenLabs, I built an agent that called customers, verified info, and triggered backend workflows through webhooks, all in real time. You can even swap models or adjust logic mid-conversation, which gives dev teams a bit of flexibility.

Vapi even gives you granular control over every part of the call. It supports advanced features like function calling during conversations, so your agent can check databases, update CRMs, or pull live data while still talking.

Once familiar with the setup, you can try building multi-step workflows where one call triggers another action, like sending an SMS confirmation or scheduling a follow-up.

But using Vapi does take some technical know-how. It’s best for developers or teams comfortable with APIs, which offer one of the most flexible ways to embed voice into your product.

Pricing

Vapi comes with a scalable pay-as-you-go model. Every new account on Vapi gets $10 in free credits to start building without the need for a credit card.

3. ElevenLabs: Best for realistic and expressive AI voices

What does it do? ElevenLabs is a voice generation platform that specializes in producing incredibly lifelike, emotionally rich speech.

Who is it for? Perfect for teams who are already building AI voice agents and want them to sound genuinely human.

ElevenLabs delivers some of the most natural-sounding text-to-speech output available today. Voices capture tone, pacing, and emotion with precision, making the audio feel human rather than synthetic.

Using the latest 11 V3 model, I could adjust how expressive each line felt just by tweaking punctuation or adding simple audio tags like [laugh] or [sad]. It didn’t just read my text, it performed it. That makes it easy to create voices that sound calm, upbeat, or even a bit irritated without diving into complex settings.

For longer scripts or multilingual projects, the multilingual V2 model kept tone consistent across languages, making it ideal for global voice agents. I tested it in English, Spanish, and Hindi, and the transitions stayed smooth with natural rhythm and accent.

If your project needs live speech recognition, Scribe V2 Realtime is worth exploring. It streams transcripts instantly, predicts context mid-sentence, and supports over 90 languages with SOC 2, HIPAA, and PCI compliance. I used it to feed transcripts directly into a call workflow, and the latency was barely noticeable.

ElevenLabs doesn’t handle logic or routing on its own, but when paired with platforms like Lindy, it becomes the voice layer that gives your AI agents a genuinely human sound.

Pricing

ElevenLabs offers a free plan with 10k credits per month for basic text-to-speech and voice cloning. The Creator plan starts at $11/month with 100k credits, professional voice cloning, and higher audio quality. 

For teams needing commercial licenses and low-latency voice agents, the Pro plan is $99/month with 500k credits.

4. Whisper by OpenAI: Best open-source speech recognition model

What does it do? Whisper is OpenAI’s open-source speech recognition model that converts spoken language into text.

Who is it for? Ideal for developers and researchers who want complete control over how their speech recognition works.

OpenAI’s Whisper remains one of the most accurate open-source tools for converting speech to text. It handles a wide range of accents, background noise, and fast speech with accuracy that often rivals commercial transcription platforms.

Whisper supports nearly 100 languages and processes both audio and video files using tools like ffmpeg.

It automatically adds punctuation and formatting, producing clean transcripts that can be exported as TXT, SRT, VTT, or TSV files. These formats make it practical for captioning videos, documenting meetings, or training voice agents.

Developers can choose from five model sizes, each balancing speed and accuracy. The Base model offers the best trade-off for most workflows, while the Large model delivers near-perfect accuracy for critical recordings.

Running Whisper on a GPU, such as in Google Colab, significantly improves speed and performance.

Because Whisper is open source, it can be self-hosted, modified, and integrated directly into existing systems. This flexibility eliminates usage limits, subscription costs, and vendor dependencies.

Whisper does not include agent logic or phone handling out of the box, so it works best as the transcription layer within a larger system. 

Pricing

Whisper is completely free to use and modify. You can self-host it at no cost, though real-time results require a solid GPU. If you’d rather skip setup, the OpenAI API offers a pay-per-minute option.

5. Bland AI: Best for creating customizable AI voice agents via API

What does it do? Bland is a voice generation platform that lets you generate custom voices with specific emotions, accents, and tones.

Who is it for? Best for large teams and enterprises looking to scale voice agent deployments across customer-facing apps, IVRs, or internal systems.

Bland even lets you choose from multiple styles, accents, and age ranges, then layer in emotional inflections like cheerful, frustrated, calm, or excited. A friend tested it with a customer service script and used it for her YouTube voiceovers. To her surprise, both felt noticeably more human than the flat voices most TTS tools offer.

Not to forget, it wasn’t just speaking, but reacting as well. Even a simple tweak like adding a slight upswing in tone at the end of a sentence made the delivery feel more lifelike.

Another win is how easy it is to plug into your stack. I used their API to send voice responses back through a Twilio workflow, and it worked great. You don’t get bogged down in SDKs or weird deployment blockers.

That said, Bland doesn’t offer a no-code interface or agent logic. You’ll need to pair it with tools like Lindy to build a full conversation flow. 

Bland includes review analytics to track call performance. You can listen to recordings, read transcripts, review outcomes, and analyze sentiment to spot patterns and improve how your agents handle conversations.

Pricing

Bland’s pricing is not publicly disclosed, and you will need to contact their sales team, which can add some friction when comparing tools.

6. Synthflow: Best no-code platform for building and deploying a voice agent

What does it do? Synthflow is a no-code platform for building AI voice agents that can make and receive calls, hold natural conversations, and integrate with your business systems.

Who is it for? Best for businesses, teams, and agencies that want to automate customer interactions like support, lead follow-ups, or appointment booking without hiring developers or messing with APIs.

Synthflow is a plug-and-play option that still offers enough control for real business use cases. You start by dragging out a conversation flow. And since no scripting or coding is needed, you can train it to understand what people might say at each step.

I tested it for lead qualification and had it running with CRM integration in less than a day. It could answer basic questions, confirm details, and pass leads into HubSpot when calls ended.

The built-in analytics section is both informative and neat. You can monitor how many calls your agent made, where callers dropped off, and even pull up full call transcripts. 

Synthflow offers production-ready agents built for specific industries. Whether you need scheduling, claims processing, or always-on support, the platform provides pre-configured templates that handle common business scenarios. 

Agents work across BPO, call centers, retail, and finance, with multilingual support and secure system integration to automate conversations without sacrificing quality.

But it’s not all perfect, as there’s a steeper learning curve than I expected. 

While you don’t need to code, you do need to understand how logic blocks and fallback responses work, or your flows might break in the middle of a call.

Pricing

Synthflow offers a Pro plan at $375/month for low call volumes with 2,000 minutes and 25 concurrent calls. The Growth plan is $900/month with 4,000 minutes and 50 concurrent calls. 

For agencies and resellers, the Agency plan starts at $1,400/month with 6,000 minutes and unlimited subaccounts.

7. Retell AI: Best for customer support and inbound call handling

What does it do? Retell AI is a fully featured voice AI platform that helps you build, deploy, and monitor phone-based AI agents. 

Who is it for? Perfect for support and sales teams who want voice agents that don’t just answer calls but turn every conversation into structured, usable data.

Retell AI lets you build and deploy AI voice agents that can help you with lead qualification, support automation, follow-ups, and much more.

I find Retell’s agent builder quite intuitive, as I could sync my website content and docs directly into the agent’s knowledge base with ease.

There’s even a Conversation Flow feature through which you can build structured call logic, define fallback paths, and guide the agent through complex scenarios with guardrails in place. It cut down errors during testing.

And once the call ends, the post-call analysis is solid, too. Retell didn’t just tell me what was said; it told me what was done. 

Whether a call resulted in a booked appointment, unresolved task, or follow-up, I could see that instantly in the dashboard. It even flagged issues like low sentiment or failed handoffs, which made it easy to spot where things went wrong.

Retell AI connects with major business tools to automate post-call workflows. Integration with HubSpot lets your voice agent automatically log call summaries, update contact records, and move deals through your pipeline without manual data entry. 

Likewise, Slack integration sends real-time notifications when calls end, so your team gets instant alerts about qualified leads or support tickets that need attention.

Pricing

Retell offers a pay-as-you-go model starting at $0.07/minute with no platform fees or subscription-based pricing.

8. CallHippo: Best for businesses wanting full-stack call automation

What does it do? CallHippo is a cloud-based VoIP phone system with AI agents that handle inbound calls, outbound dialing, and omnichannel customer communication.

Who is it for? Small and medium-sized businesses looking for an affordable, all-in-one solution with global reach and CRM integrations.

CallHippo delivers a flexible business phone system that gets you up and running in minutes. You can grab virtual phone numbers from practically anywhere in the world, route calls smartly using IVR menus, and manage everything from one platform.

The AI Voice Agent is built to handle sales and support calls 24/7. It manages inbound queries, runs outbound campaigns, and qualifies leads without needing human intervention. This works especially well for teams drowning in routine calls who want to free up agents for complex conversations.

CallHippo also includes AI Copilot for real-time insights. 

During calls, it provides sentiment analysis, live transcripts, and workflow suggestions to help agents respond better. After calls end, it automatically generates summaries and handles follow-ups, cutting down on manual admin work.

For sales teams, the Parallel Dialer connects agents to live calls instantly by eliminating dialing time. It maximizes productivity by reaching more leads faster, which is useful for high-volume outbound campaigns.

CallHippo’s omnichannel inbox helps you manage conversations across WhatsApp, SMS, Telegram, email, Instagram, and voice calls, all from one place. This keeps customer communication centralized instead of scattered across multiple apps.

It even integrates with major CRMs like HubSpot, Salesforce, Zendesk, and Pipedrive, so call data flows directly into your existing stack. 

Pricing

CallHippo offers a free Basic plan to get started. The Starter plan is $18 per user/month, the Professional plan is $30 per user/month, and the Ultimate plan is $42 per user/month (billed annually). 

9. Cognigy: Best for large-scale enterprise voice automation

What does it do? Cognigy is an enterprise-level AI automation platform built for contact centers. 

Who is it for? If you’re running a contact center at scale, especially in sectors like banking, telecom, retail, or healthcare.

Cognigy is built for real enterprise use. Its voice agents understand intent accurately, even in longer conversations, and can pull or update customer records mid-call without missing a beat. 

It comes with an AI Agent Manager that’s like a mission control center for building, deploying, and monitoring every voice experience. 

And while it’s packed with features, it didn’t feel clunky. 

I could define fallback scenarios, set escalation rules, and even design proactive outbound flows, all through a visual builder.

There’s also a Cognigy voice gateway that gives you plug-and-play integration with major telephony providers like Avaya, Amazon Connect, and Genesys. Here, I didn’t have to stitch together SIP or Twilio calls myself, as Cognigy handled it.

Cognigy uses agentic AI to handle complex, multi-step customer interactions across voice and chat. Agents can reason through problems, access knowledge bases, and execute actions autonomously while maintaining context throughout the conversation.

Insights feature breaks down automation rates, tracks intent success, and surfaces missed opportunities, exactly what large ops teams need to iterate and scale.

The catch? Cognigy is not built for solo builders or small teams. Plus, the learning curve is real, and setup often requires collaboration between IT and ops.

Pricing

Pricing for Cognigy isn’t publicly listed. 

10. Dialpad AI Voice: Best integrated AI calling platform for teams

What does it do? Dialpad AI is a business communications platform with built-in AI that transcribes calls, coaches agents in real time, and automates post-call summaries.

Who is it for? Support teams, sales reps, and contact centers that need live coaching, instant transcripts, and automated quality management.

Dialpad AI runs on DialpadGPT, a proprietary language model trained on billions of conversation minutes. This gives it the ability to transcribe calls with high accuracy, analyze sentiment in real time, and deliver context-aware insights during conversations.

The AI Live Coach feature is where Dialpad really shines. While an agent is on a call, the system listens and displays real-time cues based on what the customer is saying. 

If a specific question comes up, Dialpad surfaces the right answer instantly. This turns average agents into top performers without requiring constant manager oversight.

After each call, AI Recaps automatically generate summaries and action items, cutting call wrap-up time by 50%(claimed by Dialpad). You don't need to manually document what happened; the system does it for you and logs everything into your CRM.

For quality management, AI Scorecards grade agent performance automatically. Managers get instant visibility into how calls are going without listening to hours of recordings. 

Dialpad also calculates AI CSAT scores for most of the calls, giving you full visibility into customer satisfaction without sending post-call surveys.

Everything runs from one app with voice, messaging, and video all in the same place. It integrates across Dialpad Connect for general communications, Dialpad Support for contact centers, and Dialpad Sell for sales teams. 

Pricing

Dialpad AI's Standard plan starts at $27 per user/month with unlimited calls, AI-powered meetings, and real-time transcripts. The Pro plan is $35 per user/month and adds advanced integrations, 24/7 support, and multi-office management. 

Enterprise pricing is available with SSO, unlimited scalability, and 99.9% uptime guarantees.

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How I tested the best AI voice agents

Each voice agent was tested in realistic business workflows to assess performance, accuracy, and usability. Testing covered voice quality, responsiveness, logic handling, integrations, and overall developer experience. Here’s how I tested them: 

• Voice Quality and Realism: Each agent was tested in real call scenarios to judge how natural the voice sounded, how it handled tone and pacing, and whether it could adapt smoothly when the conversation took an unexpected turn.
• Performance in Live Calls: Agents were placed in both inbound and outbound test calls to see how quickly they responded, handled interruptions, followed logic branches, and escalated issues when human support was needed.
• Accuracy and Context Retention: I checked whether each tool understood caller intent, remembered context across multiple turns, and delivered consistent responses without losing track of the conversation flow.
• Ease of Setup and Integration: Setup time, documentation quality, and workflow flexibility were tested across platforms, from plug-and-play tools to developer-first APIs, to see which made it easiest to build, connect, and customize.
• Reliability and Support: Each platform was observed over repeated tests to evaluate uptime, stability under load, and how quickly issues were resolved through documentation, updates, or direct support channels.

Top use cases for AI voice agents

AI voice agents have quietly become the backbone of customer communication for many businesses. They answer calls, qualify leads, and manage appointments without breaks or delays. 

Here's where they work best:

• Customer support: Voice agents answer common questions, troubleshoot issues, and route complex cases to human agents. They work 24/7 without breaks, handling multiple calls at once during peak hours.
• Lead intake and qualification: These agents capture caller information, ask qualifying questions, and schedule follow-up calls with sales teams. They can also book discovery calls directly into calendars.
• Healthcare appointment management: Medical offices use voice agents to schedule appointments, send reminders, and collect patient information before visits. This frees up front desk staff for in-person tasks.
• Real estate property inquiries: Agents field questions about listings, schedule property tours, and capture buyer information. They can handle after-hours calls when offices are closed.
• Research and data collection: Voice agents conduct surveys, gather feedback, and collect responses at scale. They follow scripts while adapting to caller responses.
• Internal operations: Companies use voice agents for employee support, IT helpdesk calls, and HR questions. They handle routine inquiries so teams can focus on complex issues.

Limitations and challenges

Even the best AI voice agents come with practical limits. They’re powerful for handling repetitive or structured calls, but still rely on human oversight for complex reasoning, emotional nuance, and unexpected edge cases.

• Setup takes time and iteration: Training a voice agent on your specific workflows, terminology, and edge cases requires careful prompt engineering and testing. Expect several rounds of refinement.
• Voice quality varies by provider: Some agents sound natural and conversational, others feel robotic or have awkward pauses. Test different models to find what works for your use case.
• Latency can disrupt conversation: Response delays of even 2-3 seconds make interactions feel clunky. This improves as models get faster, but it's still a factor.
• Cost scales with usage: While voice agents cost less than human staff, high call volumes add up quickly. Per-minute pricing means popular numbers can get expensive.
• Complex scenarios still need humans: Voice agents handle routine calls well but struggle with nuanced situations, strong emotions, or requests outside their training. You'll need clear escalation paths.

​​Try Lindy: An AI assistant that handles support, outreach, and automation

Lindy uses conversational AI that does more than chat. It handles real calls, lead qualification, and customer support automatically. It also responds instantly, adapts to caller intent, and integrates with your tools so nothing falls through the cracks.

Here’s how Lindy goes further:

• Real-time voice responses: Lindy answers calls and routes inquiries in seconds.
• 24/7 availability: Perfect for async teams or after-hours coverage.
• Multilingual support: Handles over 30 languages for global teams.
• Extensive integrations: Connects with CRMs, Slack, and more.
• High-volume reliability: Scales across thousands of conversations without slowdown.

Try Lindy free and automate your first 40 tasks today.

FAQs

1. How do AI voice agents work?

AI voice agents work by capturing speech, converting it to text, and then using Natural Language Processing (NLP) to understand the user's intent. The system then uses a dialogue manager to decide on the appropriate action or response, which is generated and converted back into natural-sounding speech to be delivered to the user. 

2. What is the best AI voice agent in 2025?

Lindy is the best AI voice agent in 2025 for flexibility and customization. You can customize agents for specific use cases, connect them to your business tools, and have them work alongside other AI assistants in your workflow. Other strong options include Bland AI for simple outbound calls and Air AI for natural-sounding conversations.

3. Can AI voice agents replace human agents?

AI voice agents can't fully replace human agents, but they handle routine tasks effectively. They’re best suited for FAQs, scheduling, and basic troubleshooting. In most teams, they act as the first line of contact, managing repetitive calls, collecting information, and routing complex issues to humans who can handle emotional or high-stakes interactions.

4. How accurate are AI voice agents?

AI voice agents are typically 80-90% accurate for structured inquiries when properly trained and configured. Their precision depends on call complexity, background noise, and how well intents are mapped. With clear scripts, regular testing, and clean audio, top-performing agents can match or exceed human consistency for simple, high-volume customer interactions.

5. How do I train or customize one?

You can train or customize an AI voice agent by uploading call scripts, FAQs, and sample conversations. Most platforms let you define escalation rules, tune responses, and adjust tone based on context. With visual flow builders like Lindy, teams can design, test, and refine complete call experiences without writing a single line of code.