Conversational AI Platforms: 13 Best Tools in 2026 Compared

Quick Summary

Callers is a strong fit for high-volume B2C teams seeking inbound resolution and proactive outbound engagement with customer context that carries between interactions. Free and Starter offer voice and web chat; Enterprise extends to text and email. Sierra, Decagon, Ada, and Fin focus heavily on support, while PolyAI and Regal are strong in voice.

Cognigy, Kore.ai, Yellow.ai, and Wonderful serve broader enterprise requirements. Retell and Vapi suit developer-led voice projects.

Looking for a Conversational AI Platform?

Every customer service vendor now calls itself a conversational AI platform. The label covers chat widgets, phone automation, and everything between. This blanket claim makes shopping the category slow and confusing.

This guide compares 13 leading AI voice and chat platforms so you can shortlist faster.

One note before the list. It's business software for automating customer conversations. If you want a personal assistant like ChatGPT, that's a different category. Every platform here builds AI agents that talk to your customers over voice, chat, or messaging, then logs the outcome in your stack.

Why Listen to Us?

Callers is used in real customer-support and sales operations, including Einride and Voyager GM. The public case studies describe what happens when AI agents handle repetitive inquiries and support proactive follow-up at scale.

Voyager GM reported 60% higher customer engagement, around 30% less agent workload, and a 90% reduction in time to lead after deploying Callers. Read the case study: https://www.callers.ai/case-studies/vgm-scaled-customer-support-and-sales/.

What Is a Conversational AI Platform?

A conversational AI platform is a software solution that runs customer conversations for your business.

These tools answer and make phone calls, reply to chats, and handle messages without a human on every interaction. The good ones connect to your CRM, complete real tasks like refunds and bookings, and hand off to your team when it's sensitive.

The term gets stretched, so it helps to know what's outside it.

Consumer chatbots like ChatGPT are for individuals. Scripted website widgets and rigid phone menus predate the category and can't hold a real conversation. The platforms below understand natural language, keep context across turns, and act on what customers say.

Within the category, five distinct types have emerged. Knowing which type you're buying matters more than any feature comparison.

Support-led teams usually start with the CX agents. If calls carry real revenue or volume for you, look at the omnichannel and voice-first rows first, starting with an AI call center approach.

Conversational AI Platform Providers and Vendors

Providers range from developer-first voice infrastructure to broader enterprise AI suites. Retell AI and Vapi offer flexible components that engineering teams assemble and maintain. Platforms such as Callers, Sierra, Decagon, Ada, and Intercom Fin provide more packaged customer-facing workflows, but their deployment and service models differ.

The enterprise end includes Cognigy, Kore.ai, Yellow.ai, and Wonderful, with broad governance, contact-center integration, and product portfolios. Buyers should check what each vendor includes in its specific quote.

The right tier depends on your team, use case, and operational ownership. If you have developers and want control, start with the infrastructure-first options. For high-volume B2C operations, prioritize customer context, inbound resolution, outbound engagement, and practical human handoff—not the number of features in a demo.

The 13 Best Conversational AI Platforms

1. Callers

Callers is an Agentic Customer Experience Platform for high-volume B2C organizations. Its AI agents resolve inbound support requests and conduct proactive outbound engagement while drawing on a persistent customer context layer. Customers do not have to start over when their interactions span supported channels. Free and Starter include voice and web chat; Enterprise supports voice, web chat, text, and email.

For B2C teams, the distinction is continuity: what the AI learns on one interaction can inform the next action and channel, instead of treating every conversation as a new ticket. Customers can explore Free or Starter with self-serve setup; Enterprise adds done-for-you implementation and dedicated customer success support. Actual rollout time depends on workflows and integrations.

Key Features

• Persistent customer context: information from previous interactions can inform follow-up and handoff across supported channels

• Outbound campaign builder: multi-step sequences, conditional retries, and pre-call triggers

• No-code flow builder: drag-and-drop scripting with AI assistance, owned by operators

• Emotionally intelligent voices: natural delivery with mid-call language switching

• Step-level analytics: see the exact step where conversations break down

• Plan-appropriate onboarding: self-serve setup on Free and Starter; dedicated CSM and done-for-you implementation on Enterprise

Pricing

Callers lists three plans at https://www.callers.ai/pricing/: Free ($0/min, with $5 in credits for testing two inbound agents); Starter ($0.16/min, up to five inbound/outbound agents and 30,000 minutes monthly); and Enterprise (custom contract and volume). Free and Starter provide voice and web chat; Enterprise adds text and email plus a dedicated CSM, guided implementation and additional security options. Check the pricing page for current availability and plan details.

Pros

• Warm transfer routes high-stakes conversations to your team

• Self-serve setup for initial agents, with Enterprise implementation options for complex workflows

• 610+ native integrations, including Salesforce, HubSpot, and Zendesk

• Step-level analytics that show exactly where scripts lose people

• Proven at scale with DoorDash, Einride, and PadSplit

Cons

• Text and email channels, custom Enterprise security features, and dedicated CSM support require Enterprise

• Free is limited to two inbound agents and one concurrent call; Starter is capped at five agents and five concurrent calls

Best for

High-volume B2C teams that want inbound support, outbound engagement, and customer context that persists across interactions. Plan selection determines channel and service availability.

Why Choose Callers

Choose Callers when customer conversations drive revenue, retention, or support workload, and continuity matters across those interactions. Voyager GM reported 60% higher engagement and around 30% less agent workload after implementing Callers. See the results: https://www.callers.ai/case-studies/vgm-scaled-customer-support-and-sales/. Explore the AI call center workflow: https://www.callers.ai/use-cases/ai-call-center/. Compare plans: https://www.callers.ai/pricing/.

2. Sierra

Sierra's the enterprise heavyweight of the AI agent category and it was founded by former Salesforce co-CEO Bret Taylor. It deploys a single agent across chat, SMS, WhatsApp, email, voice, and even ChatGPT, with customers like Rocket Mortgage, SiriusXM, and ADT.

Key Features

• Ghostwriter: builds production-ready, multilingual agents from your existing docs

• Voice Personas: configurable voice agents with low-latency speech

• Insights: deep analytics on agent conversations and performance

• Observability: an audit trail of every action the agent takes

• Broad channels: chat, SMS, WhatsApp, email, voice, and ChatGPT

Pricing

Sierra doesn't publish pricing. The model's outcome-based. You pay when the agent delivers a defined outcome, like a resolved conversation or a saved cancellation, and unresolved conversations generally cost nothing. Deals are negotiated through sales.

Pros

• Outcome-based pricing aligns cost with results

• Strongest enterprise logo roster in the category

• Mature voice, well beyond a chat bolt-on

• Ghostwriter cuts agent build time dramatically

• Strong governance story for regulated buyers

Cons

• There's no published pricing, and entry costs sit at enterprise level

• Every deal needs careful negotiation of what's counted as an outcome

• There's no self-serve option or trial

Best for

Large enterprises with heavy support volume that want a premium, outcome-priced agent platform.

Why Choose Sierra

Choose Sierra if you're a large enterprise standardizing customer conversations on one agent platform and you want the vendor's incentives tied to resolutions. Budget for an enterprise sales cycle and a guided rollout.

3. Decagon

Decagon builds AI support agents that teams steer in plain English. Its Agent Operating Procedures let CX teams write workflows as natural language instead of code or config, across voice, chat, and email. Customers include Duolingo, Chime, and Rippling.

Key Features

• AOPs: agent workflows written and edited in natural language

• Omnichannel agents: voice, chat, and email on shared logic

• Simulation and A/B testing: test agent behavior before and after launch

• Watchtower: continuous automated QA on live conversations

• Insights: deflection tracking and customer intelligence reporting

Pricing

Decagon doesn't publish pricing and has no public pricing page. The company describes two models, per conversation and per resolution, and you settle on one through sales.

Pros

• Ops teams iterate on agent behavior without engineering tickets

• Choice between usage-based and outcome-based billing

• Strong built-in QA loop from simulation to live monitoring

• One agent brain across voice, chat, and email

• Well referenced among modern consumer and fintech brands

Cons

• It's enterprise-only, with no trial and no public pricing

• Per-conversation billing includes conversations the AI can't resolve

• It's a younger vendor, which procurement in regulated industries may flag

Best for

Mid-market and enterprise consumer brands that want an agent their ops team can tune in plain English.

Why Choose Decagon

Decagon fits teams that expect to adjust their AI agent constantly and want that power inside the CX team. If your support content changes weekly, natural-language AOPs beat filing tickets against a vendor services team.

4. Ada

Ada's been automating customer service since 2016, which makes it the veteran of the AI agent group. It runs one agent across messaging, email, and voice in 60+ languages for brands like Pinterest, Monday.com, and Malaysia Airlines.

Key Features

• Single agent, many channels: messaging, email, and voice from one build

• Playbooks: multi-step workflows that take real actions

• Multi-LLM orchestration: accuracy controls without single-model lock-in

• 60+ languages: consistent brand terminology managed via glossaries

• Coaching tools: test, measure, and improve the agent over time

Pricing

Ada doesn't publish pricing. Its pricing page routes to a demo booking. Ada's own content argues for conversation-based billing, so expect to pay per conversation handled rather than per resolution.

Pros

• Nearly a decade of production deployments

• 60+ languages for global brand consistency

• Multi-LLM approach avoids model lock-in

• Strong measurement culture with testing and coaching tools

• Reportedly a lower entry price than newer enterprise rivals

Cons

• It's got chat heritage, with voice and email newer and less deep

• Custom-only pricing with no trial

• Its own billing-model shift means contracts aren't straightforward

Best for

Established global consumer brands that need broad language coverage from a proven vendor.

Why Choose Ada

Ada's the safe, mature pick among the CX agents. If your board asks "who else has run this in production for years," Ada's got the longest answer. The 60+ language coverage fits a global footprint too.

5. Intercom Fin

Fin is Intercom's AI agent and the volume leader in published performance claims, citing a 76% average resolution rate across 12,000+ customers. It works inside Intercom or on top of Zendesk, Salesforce, and other helpdesks, with customers like Anthropic and Rocket Money.

Key Features

• Helpdesk-agnostic: runs on Intercom, Zendesk, Salesforce, and more

• Procedures and Tasks: multi-step actions like refunds and order lookups

• Train, test, deploy tooling: preview testing and guidance controls

• QA dashboards: observability on resolutions and agent behavior

• Fin Copilot: an AI assistant for your human agents

Pricing

$0.99 per resolution, published on the vendor's site, with a 50-outcome monthly minimum. Qualification outcomes for sales use cases cost $9.99 each. Using Fin inside Intercom's own helpdesk adds $29 per seat per month. Fin Voice isn't included and goes through sales separately.

Pros

• Transparent published pricing, paid only on outcomes

• Strong published resolution benchmarks at huge scale

• No helpdesk migration required

• There's mature testing and QA tooling

• 14-day unlimited trial with self-serve start

Cons

• It's got chat and email heritage but voice is new and gated behind sales

• Per-outcome costs climb fast at high volume

• Deepest experience sits inside Intercom's own ecosystem

Best for

Support teams on chat and email that want a proven agent with pricing they can model in a spreadsheet.

Why Choose Fin

Fin's the easiest platform on this list to try. The trial's self-serve, the price is public, and it works on the helpdesk you already run. For digital-first support automation, it's the lowest-friction serious option.

6. PolyAI

PolyAI builds enterprise voice agents with some of the most natural-sounding conversations in the industry. It’s been trained on over a billion enterprise calls and serves large contact centers in hospitality, banking, and healthcare. The company’s served notable customers like PG&E and Golden Nugget.

Key Features

• Lifelike voice agents: handle interruptions, accents, and background noise

• Raven model: proprietary conversation model built for enterprise calls

• Agent Studio: no-code builder, plus an SDK for developers

• Pre-trained industry agents: faster starts for common verticals

• Enterprise compliance: SOC 2, HIPAA, GDPR, and PCI DSS

Pricing

PolyAI doesn't publish rates. Pricing runs per minute and bundles ongoing tuning, maintenance, and 24/7 support. You'll need an enterprise sales process to get numbers.

Pros

• Widely regarded as a benchmark for natural enterprise voice

• Managed model includes continuous optimization by PolyAI experts

• Strong regulated-industry credentials

• Proven containment results at recognizable brands

• Both no-code and developer build tracks

Cons

• There's no published pricing and no self-serve tier

• It's inbound-first heritage, with outbound requiring account-team activation

• Managed deployments mean longer cycles and vendor involvement

Best for

Large contact centers with heavy inbound call volume that want premium managed voice automation.

Why Choose PolyAI

PolyAI suits enterprises that want a vendor deeply involved in deployment and tuning. If you'd rather buy a managed outcome than operate a platform, and your volume justifies the contract, it's a strong inbound choice.

7. Regal

Regal comes from the outbound side of the contact center. It pairs AI phone, SMS, and chat agents with a dialer, IVR, and journey orchestration. This stack is aimed squarely at high-volume B2C operations and customers include Toyota, AAA, and Coursera.

Key Features

• AI agents on three channels: phone, SMS, and chat in one platform

• Journey Builder: multi-step, multi-channel customer journeys

• Built-in contact center stack: dialer, IVR, routing, unified profiles

• A/B testing: compare agents, scripts, and journeys in production

• Conversation intelligence: automated QA and monitoring

Pricing

Regal's pricing page has no rate card and directs you to sales. The company's own blog cites a typical rate of about $0.20 per minute for AI agents, with platform and implementation fees on top.

Pros

• Handles outbound and inbound in one system

• Journey orchestration can replace parts of a CCaaS stack

• Strong claimed results on containment and speed-to-lead

• A/B testing supports continuous optimization

• The rare vendor-stated cost creates an anchor for the category

Cons

• Regal's own guidance targets teams with 25+ agents and 100K+ monthly minutes

• Total cost still requires a sales conversation

• It's a broader platform for teams that want only support automation

Best for

High-volume B2C contact centers that want AI agents plus dialer and journey infrastructure together.

Why Choose Regal

Regal makes sense when you want to consolidate outbound infrastructure and AI agents into one vendor at a serious scale. The entry bar's high for smaller teams.

8. Cognigy

Cognigy, now NiCE Cognigy after its acquisition by NICE, is an analyst-recognized enterprise platform for customer service AI. It's a Gartner Magic Quadrant Leader with deep contact-center connectivity and customers like Lufthansa, Toyota, and DHL.

Key Features

• AI Agent Studio: low-code builder for agentic AI and flows

• Voice Gateway: turnkey connectivity into CCaaS platforms

• Knowledge AI: RAG over enterprise content

• Agent Copilot: real-time assist for human agents

• 80+ languages: with real-time translation

Pricing

Cognigy doesn't publish prices and billing's conversation-based. Its docs define a conversation as up to 50 user inputs in 24 hours on digital, or up to 10 minutes of voice per call. Numbers come through sales.

Pros

• Leader placement in major analyst evaluations

• Deep voice and CCaaS integration, strengthened by NICE ownership

• Customer-facing agents and agent-assist in one platform

• Strong multilingual and translation capability

• Proven with major global enterprise brands

Cons

• There's no published pricing at any tier

• Rollouts commonly take months and you'll often need system integrators

• There's a steep learning curve before business users are self-sufficient

Best for

Large enterprise contact centers, especially NICE CXone shops, buying through a formal evaluation.

Why Choose Cognigy

Cognigy's the defensible enterprise pick. If your organization requires analyst validation, procurement rigor, and deep contact-center integration, it belongs on the RFP shortlist.

9. Kore.ai

Kore.ai covers more surface area than any other platform here. It spans customer service AI, employee-facing agents for HR and IT, and a general agent-development platform with governance. Customers include banks and pharma companies like Morgan Stanley and Pfizer.

Key Features

• Agent Platform: multi-agent orchestration with governance and model choice

• AI for Service: contact center automation, IVR, and agent assist

• AI for Work: prebuilt employee agents for HR, IT, and finance

• Search AI: enterprise RAG over company knowledge

• Marketplace: prebuilt agents and industry templates

Pricing

Kore.ai publishes a self-serve Standard plan in its developer docs at $0.20 per conversation, with $500 in free credits. The main pricing page shows no numbers. Enterprise tiers are custom quoted and billed per session or per seat depending on the product. Enterprise AI for Service and broader agent-platform evaluations typically require a tailored quote, and trial or developer access may differ from the final production contract, so verify current pricing and availability with Kore.ai.

Pros

• One governed platform for customer, employee, and custom agents

• Deep credentials in regulated industries

• A published pay-as-you-go entry point, rare at this tier

• Real code support alongside low-code building

• Large marketplace shortens common builds

Cons

• There's a dense interface with a steep learning curve

• You'll probably need technical teams or partners to get it running

• Enterprise pricing beyond the entry tier is negotiated and opaque

Best for

Regulated enterprises that want customer and employee AI agents under one governance model.

Why Choose Kore.ai

Choose Kore.ai when the mandate's bigger than customer service. If one platform must serve CX, employee support, and internal agent development with governance over all of it, few vendors match its breadth.

10. Yellow.ai

Yellow.ai runs conversational AI for high-volume B2C enterprises across 35+ channels, with a multi-LLM architecture and its VoiceX voice product. It claims 1,300+ brands, with strength in commerce, banking, travel, and logistics across global markets.

Key Features

• 35+ channels: WhatsApp, web, mobile, email, and voice with shared context

• VoiceX: low-latency voice AI with broad language claims

• AI Agent Builder 2.0: no-code creation with automated testing

• Multi-LLM architecture: 15+ models with no single-vendor lock-in

• User360 and campaigns: customer data layer plus outbound automation

Pricing

Yellow.ai publishes a free plan with one agent and 500 chat sessions a month included, then $0.99 per resolution. Its Enterprise tier shows no public prices and routes through sales.

Pros

• Free entry tier with published per-resolution pricing

• Context carries across channel switches, useful for WhatsApp-heavy markets

• Multi-LLM design lets enterprises swap underlying models

• Broad channel and language coverage for global B2C

• Usable no-code builder with a large connector catalog

Cons

• Reviewers cite intent-matching misses and occasional lost context

• Enterprise pricing beyond the free tier isn't transparent

• Prebuilt connectors often need more configuration than the label implies

Best for

Global B2C enterprises, especially in WhatsApp-first markets, that want chat and voice on one platform.

Why Choose Yellow.ai

Yellow.ai earns a look when your customers live on messaging apps across multiple countries. It's hard to match at this price point.

11. Retell AI

Retell AI gives engineering teams a production-grade platform for AI phone agents. It pairs APIs with a drag-and-drop flow builder and handles telephony work most platforms leave to you. That includes batch calling, SIP trunking, and caller ID reputation.

Key Features

• Agent flow builder: drag-and-drop framework with guardrails and function calling

• Telephony depth: batch campaigns, SIP trunking, branded caller ID, IVR navigation

• Model choice: OpenAI, Claude, or Gemini, plus multiple voice providers

• Streaming knowledge base: RAG with auto-sync from your content

• Built-in QA: post-call analysis, transcription, and call scoring

Pricing

Retell publishes component pricing that lands between $0.07 and $0.31 per minute. This price covers voice infrastructure, your chosen LLM, voices, and telephony. Add-ons like knowledge bases, branded caller ID, and PII redaction bill separately. New accounts get $10 in free credits.

Pros

• Transparent per-minute pricing with a cheap entry point

• Telephony tooling competitors leave to third parties

• Built-in QA and analytics reduce bolt-on tooling

• SOC 2 Type II, HIPAA, and GDPR available on self-serve tiers

• 20 free concurrent calls is generous for testing

Cons

• The $0.07 headline climbs fast with capable models and premium voices

• It's still a developer platform despite the visual builder

• Phone-first, with chat and SMS secondary

Best for

Engineering teams that want production phone agents with the telephony details handled.

Why Choose Retell AI

Retell fits teams with engineers who want control over the agent but don't want to build voice infrastructure. You get the plumbing solved and keep the logic.

12. Vapi

Vapi's an API-first orchestration layer for teams that want to assemble their own voice AI stack. You pick the transcription, LLM, and voice providers. Vapi runs the real-time orchestration between them at scale as proven by customers like Ring and Intuit.

Key Features

• Model-agnostic stack: mix any STT, LLM, and TTS, or bring your own keys

• Low latency: sub-500ms averages with real-time interruption handling

• Workflow builder and test suite: simulate and evaluate agents pre-launch

• SDKs and webhooks: deploy to phone, web, and mobile

• Enterprise controls: SSO, RBAC, guardrails, and fleet monitoring

Pricing

Vapi publishes a $0.05 per minute platform fee that’s billed to the second. Speech-to-text, LLM, and voice costs pass through at cost, or they'll drop to zero with your own provider keys. Telephony bills are at your provider's rates. HIPAA compliance is a $2,000 per month add-on.

Pros

• Maximum flexibility across every layer of the stack

• Low platform fee makes high-volume economics attractive

• Strong developer ergonomics with SDKs and eval tooling

• Proven at very large scale

• New models and voices arrive as fast as providers ship them

Cons

• Assembly required, and you'll own tuning across four separately billed vendors

• Total per-minute cost's harder to predict than an all-in rate

• Compliance add-ons price out smaller regulated use cases

Best for

Developer teams that want full control of the voice stack and the lowest marginal cost at scale.

Why Choose Vapi

Vapi's the right call when engineering control's the priority and you have the team to use it. Nothing on this list is more flexible but nothing hands you more of the work either.

13. Wonderful

Wonderful is an enterprise AI platform that deploys agents across customer, employee, and back-office workflows in 30+ markets. A multi-model operating layer routes tasks to whichever LLM fits best, and dedicated local teams handle the deployment from inside your organization.

Key Features

• Multi-model operating layer: routes each task to the best-fit LLM across providers, so nothing you build is locked to a single model

• Embedded local deployment teams: places a forward-deployed engineer and a deployment strategist inside your environment

• Omnichannel agents: handles voice, chat, email, and document-based work across channels

• Enterprise compliance and deployment options: supports SOC 2 Type II, ISO 27001, GDPR, and PCI DSS

Pricing

Wonderful doesn't publish pricing. Deals run through sales, and every contract includes the embedded deployment team. There's no self-serve tier or public rate card.

Pros

• Dedicated local teams embed inside your organization for every deployment

• Model-agnostic platform avoids LLM vendor lock-in

• Proven at scale with named enterprises across 30+ countries

• Provides multi-tenant, single-tenant, BYOC, or fully air-gapped on-premise deployment

• Multi-model operating layer uses the best LLM for dedicated tasks

Cons

• Services-led delivery means longer timelines than self-serve platforms

• No public pricing and no self-serve option

• Largest production deployments sit in non-English-speaking markets

Best for

Large multilingual enterprises that want a vendor's team embedded on-site for the full deployment lifecycle.

Why Choose Wonderful

Pick Wonderful when your organization spans multiple countries and you want a deployment team on the ground in each one. The tradeoff is timeline and investment. Deployments take months and pricing is at enterprise level.

Choose the Right Conversational AI Platform

The right platform depends on which conversations you're automating. Sierra, Decagon, Ada, and Fin are strong picks for chat-led support resolution.

Cognigy, Kore.ai, Yellow.ai, and Wonderful offer broader enterprise platforms; Retell and Vapi give developer teams greater control over voice infrastructure. PolyAI and Regal focus on larger contact-center programs, with different degrees of managed service and orchestration.

If customer conversations carry revenue or support volume, consider Callers for persistent context across inbound resolution and outbound engagement. Compare Free and Starter voice-and-chat options with Enterprise's broader channel coverage, CSM support, and implementation services. Voyager GM's results offer one example of the operational impact: https://www.callers.ai/case-studies/vgm-scaled-customer-support-and-sales/.

Explore Callers' AI Call Center use case: https://www.callers.ai/use-cases/ai-call-center/. See current pricing: https://www.callers.ai/pricing/. Book a meeting to evaluate Enterprise workflows: https://www.callers.ai/book-a-meeting/.

FAQs

1. How Much Do Conversational AI Platforms Cost?

Pricing ranges from free trials and usage-based entry plans to custom Enterprise contracts. Callers lists Free, Starter at $0.16/min, and custom Enterprise plans; Vapi lists a $0.05/min platform fee before provider costs. Compare the full stack, minimums, limits, and human-service components rather than headline unit prices alone.

2. What’s the Difference Between a Chatbot and a Conversational AI Platform?

A chatbot follows scripted rules and can't hold a real conversation. A conversational AI platform understands natural language, keeps context across turns, connects to your CRM, and takes real actions like processing refunds. It's the difference between answering one question and managing an entire customer interaction. The platforms in this guide don't just deflect tickets; they replace or augment human agents.

3. How Long Does It Take to Deploy a Conversational AI Platform?

Timelines depend on use-case scope, contact-center integration, and operating requirements. Callers Free and Starter support self-serve setup, while Enterprise includes guided implementation and a dedicated CSM. Voyager GM's case study describes expansion from inbound support to outbound workflows; enterprise schedules should be agreed for each deployment.

4. Can Conversational AI Platforms Handle Phone Calls?

Most platforms on this list support voice, but depth varies. PolyAI and Regal are voice-first, so they're strongest here. Callers, Sierra, and Decagon handle voice alongside chat and messaging from one agent. Retell AI and Vapi give developers full control over the voice stack. Ada and Intercom Fin have added voice more recently, so they aren't as mature on that channel. If voice is your priority, don't start with a chat-first platform.