10 best AI voice agent platforms for production teams in 2026

This guide compares 10 leading platforms for technical and product teams. It covers who each platform is for, its strongest capabilities, its pricing model, and the tradeoffs that matter when you move from testing to live calls.

AI voice agent platforms compared at a glance

What to compare before you choose

Each platform profile below focuses on the same practical questions: who it fits, what control it gives you, how it handles telephony and production operations, what its pricing includes, and where the tradeoffs sit. Use those points to eliminate poor fits quickly, then test two finalists with the same call flows and workload.

1. Dasha: best for a managed production platform with developer control

Best for: Technical teams that want to build and run production voice AI agents without assembling and operating every layer themselves.

We built Dasha to give developers a fast managed starting point without boxing them into a basic visual builder. You can create phone and web agents through our dashboard or REST API, choose AI providers, connect business tools, test conversations in the browser, and inspect searchable transcripts.

Our managed runtime reduces the infrastructure work between a prototype and a live deployment. It is a strong fit for product teams that need API access, telephony, monitoring, and room to make conversation behavior more deterministic as requirements grow.

Consider: Dasha is the better fit when you want a managed platform. We also offer a self-hosted path; confirm its scope, operating responsibilities, and commercial availability with us if private deployment is a requirement. If an open-source runtime and full media-layer control are non-negotiable, an open framework may suit you better. Teams with specific security, deployment, or procurement requirements should confirm those details with us during evaluation.

Pricing: You can start with 1,000 free minutes. Growth pricing starts at $0.08 per minute, excluding Voice over Internet Protocol (VoIP) and large language model (LLM) tokens. You can find the full details on our pricing page.

2. Bland AI: best for managed, high-volume enterprise deployments

Best for: Enterprises that want vendor-led implementation, high call volumes, and private deployment options.

Bland AI offers versioned text and audio evaluations where enabled. Enterprise organizations with SIP access can use connection tests, live traces, and trunk diagnostics. Across its tiers, Bland supports contact-center integrations; Enterprise adds dedicated, on-premises, or virtual private cloud infrastructure. Its minute rate includes the LLM, speech-to-text (STT), and text-to-speech (TTS) layers, which makes the base bundle easier to understand than a purely componentized stack.

Consider: Private deployment, dedicated orchestration, priority queuing, custom capacity, and controls such as business associate agreements, single sign-on, data residency, and alarm monitoring are Enterprise-only. Core integrations, pathways, and automations are available on self-serve tiers, while some advanced channels, nodes, and transfer features require Enterprise. Some plans also include a monthly platform fee. Bland's per-minute AI rate includes the LLM, STT, and TTS. Telephony is billed separately through your carrier or Bland at pass-through cost; Bland's billing documentation says SIP cost is included when calls route through Bland's SIP endpoints, so confirm the routing-specific quote. Define who owns and operates any private infrastructure before signing a contract.

Pricing: Bland's plans range from self-serve per-minute pricing to custom enterprise contracts. Compare the complete quote, including telephony, capacity, platform fees, support, and deployment scope.

3. Retell AI: best for integrated operations and live call supervision

Best for: Product and operations teams that want one console for building, testing, deploying, and monitoring voice agents.

Retell AI supports prompt-based and conversation-flow agents, simulation tests, custom telephony, post-call analysis, and latency telemetry broken into percentiles and components. Its live monitoring tools let an operator follow a transcript, listen silently, take over a call, or end it.

Consider: The total rate changes with the selected model, voice, telephony, quality-assurance layer, and add-ons. Retell lists a dedicated stable server, custom single sign-on, and role-based access controls under Enterprise, with custom pricing. Retell is based in the United States and says personal information is primarily stored and processed there, with potential transfers to other jurisdictions. Teams with strict regional-processing requirements should verify every service and safeguard in the data path.

Pricing: Retell's pricing is assembled from voice infrastructure, voice, model, telephony, and optional features. Price the exact configuration rather than using its displayed range as an all-in rate.

4. Synthflow: best for guided visual workflows

Best for: Operations teams, agencies, and enterprises that value visual flows, implementation support, and business integrations.

Synthflow offers Phone call, Chat, Web Call, and Simulation testing in a visual build-and-publish workflow. It also includes analytics, manual data export, customer relationship management integrations, webhooks, and telephony options spanning purchased numbers, Twilio, and enterprise-scoped SIP or private branch exchange paths. That makes it attractive to teams that prefer a guided rollout, while REST, streaming API, and WebSocket options remain available.

Consider: Synthflow's Enterprise contracts start at $30,000 annually, and SIP or private branch exchange connections require an Enterprise plan. Its personally identifiable information redaction does not affect real-time audio or guarantee 100% detection, so regulated workflows still need end-to-end controls.

Pricing: Synthflow pricing lists Enterprise contracts starting at $30,000 annually. Call volume, concurrency, telephony setup, integrations, security needs, and launch support shape the final contract.

5. Vapi: best for hosted component flexibility

Best for: Developers that want broad choice across speech and model providers, telephony paths, custom components, and SDK options.

Vapi supports single assistants, multi-agent squads, custom transcriber, LLM, and text-to-speech servers, several carrier and SIP paths, evaluations, pre-deployment simulations, and custom-server integrations. Bring-your-own provider keys and custom bucket storage also give teams control over provider billing and where call artifacts are stored.

Consider: Provider selection affects cost, latency, quality, and resilience; a call can fail if the selected transcriber and its fallbacks fail. When you bring an eligible provider key, that provider bills you directly. Vapi offers automatic transcriber fallback and also lets you configure a manually ordered fallback list. You can tune endpointing and interruption behavior, but Vapi continues to run the orchestration layer; internal system logs and product usage metrics remain on Vapi infrastructure.

Pricing: Vapi's Build pricing lists $0.05 per minute for Vapi hosting. Transport and STT, LLM, and TTS costs are separate; with eligible provider keys, Vapi lists the model-provider charge as $0 and the provider bills you directly. Model the full stack and support requirements.

6. Deepgram Voice Agent API: best for a unified speech and runtime API

Best for: Engineering teams that want one real-time interface across speech recognition, model orchestration, and speech generation.

Deepgram Voice Agent API combines Deepgram STT, LLM orchestration, and TTS through a WebSocket API. Teams can bring their own LLM or TTS provider, and Deepgram advertises managed, dedicated single-tenant, virtual private cloud, and self-hosted deployment paths. Its pricing FAQ describes private-cloud and on-premises self-hosting for Enterprise customers. Persisting the WebSocket's non-audio frames creates a replayable event record covering transcripts, tool calls, errors, configuration changes, and latency.

Consider: Telephony comes through an external carrier or integration, and Deepgram's dashboard offers high-level usage rather than per-session, turn-by-turn observability. Per-session analysis and operational monitoring require you to persist WebSocket events yourself; store raw binary audio frames separately if recordings are required. The listen layer currently supports only Deepgram STT, so replacing STT means moving outside the unified API rather than swapping a provider.

Pricing: Deepgram's Standard-tier pay-as-you-go rate is $0.075 per minute, billed for WebSocket connection time, and includes Deepgram STT, a Standard-tier managed LLM, TTS, and orchestration. Bring-your-own provider rates reduce the Deepgram charge; budget external-model and telephony-provider charges separately. Growth starts at a $4,000 annual commitment.

7. ElevenLabs Agents: best for voice selection and a fast managed path

Best for: Teams that prioritize voice selection and want a managed path with testing, experiments, monitoring, and telephony.

ElevenLabs Agents combines its voice catalog with model choice, simulations, automated tests, versioning, experiments, analytics, and enterprise-only real-time monitoring. Tests can be created from existing conversations, and the same test can run multiple times to report a pass rate and group failures.

Consider: ElevenLabs supplies ASR, TTS, and proprietary turn-taking while allowing a supported or custom LLM. Its documented agent configuration uses Scribe v2 Realtime for ASR (scribe_realtime); the legacy elevenlabs ASR provider is deprecated. ElevenLabs TTS and turn-taking models remain built in, and the schema does not expose arbitrary external ASR or TTS provider fields. Teams that need source-level control of the runtime or media stack may prefer an open framework. ElevenLabs recommends testing multiple voices for the target language and region; validate the final setup with representative calls. Private deployment is available to authorized Enterprise customers, and access and technical details require the account team or sales.

Pricing: ElevenLabs agent pricing bundles 15 to 12,375 call minutes and four to 40 concurrent calls across its self-serve plans. Additional call minutes cost $0.08; when burst pricing is enabled, calls above a plan's concurrency limit cost $0.16 per minute. LLM and telephony charges are separate, while Enterprise pricing and higher concurrency are custom.

8. LiveKit Agents: best for code, media, and deployment control

Best for: Developers building highly custom voice, video, multimodal, or human-in-the-loop agents.

LiveKit Agents is an open-source Python and Node.js framework with provider plugins and deployment through LiveKit Cloud or a custom environment. Its telephony supports SIP trunks plus cold and agent-assisted transfers. For agents connected to LiveKit Cloud media servers, Agent Observability combines transcripts, traces, logs, audio, and metrics in a per-session timeline. LiveKit Cloud agent deployments use rolling releases, sending new sessions to new instances while old instances get time to finish active sessions.

Consider: LiveKit gives you more control because it leaves more application behavior and provider selection to your team. In custom deployments, your team is responsible for container orchestration, autoscaling, storage, networking, and rollout grace periods; LiveKit Cloud manages builds, deployment, scaling, and observability. A session timeline also does not replace fleet logs for startup, crash, or dispatch failures.

Pricing: LiveKit pricing itemizes agent sessions, models, telephony, and observability, with plan-specific allowances and overages. Include infrastructure, engineering, upgrades, load testing, and on-call work when comparing a self-hosted path.

9. PolyAI: best for managed enterprise contact centers

Best for: Large contact centers that want a managed program, existing contact-center integrations, and ongoing optimization.

PolyAI combines enterprise voice assistants with visual and developer workflows. Its developer platform includes Git-backed changes, command-line tests, continuous integration and deployment, version review, and rollback. Managed monitoring and optimization can reduce the internal team needed to run a large program.

Consider: PolyAI documents US, UK, and EU regional Studio and API hosts, plus a separate self-serve Studio region, and says each workspace lives in exactly one region. It also documents integrations with major telephony platforms. Custom SIP, residency, and customer-specific hosting or deployment scope still need to be confirmed for your account.

Pricing: PolyAI pricing uses a per-minute model but does not publish the dollar rate. The listed plans include proactive performance improvements, maintenance, monitoring, and 24/7 support. Compare those services with the work other vendors leave to your team.

10. Telnyx AI Assistants: best for a carrier-native stack

Best for: Phone-first teams that want numbers, carrier infrastructure, speech, inference, orchestration, and troubleshooting from one vendor.

Telnyx AI Assistants combines a communications network with a managed agent layer. It includes console and API workflows, version and traffic controls, traces, latency breakdowns, transcripts, AI-to-AI handoff, and optional voicemail detection on transferred calls. Having the carrier and agent layer together can simplify phone-call debugging.

Consider: That consolidation also concentrates risk. Teams committed to another carrier, or those that want the agent runtime to stay provider-neutral, may not want the phone and AI control planes tied to one vendor.

Pricing: Telnyx advertises a $0.05-per-minute voice-engine rate for orchestration, Telnyx-hosted STT (including Deepgram models), and the listed Telnyx-hosted TTS voices. LLM tokens, the Voice API platform fee and inbound or outbound SIP trunking, phone numbers, non-included or bring-your-own TTS voices, AI-enabled storage and embeddings, messaging, and optional Voice API features such as recording or call transfer are priced separately or billed by the external provider. Use your actual destinations, call direction, numbers, models, and features when estimating pay-as-you-go costs or requesting a volume quote.

How to narrow the list to two platforms

You do not need a 12-category scorecard to reach a useful shortlist. Start with four decisions:

1. Choose your operating model. Decide whether you want a managed platform, composable API, open framework, carrier-native stack, or guided enterprise program.
2. Set knockout requirements. Confirm telephony countries, existing number or SIP support, data region, retention, security, concurrency, transfer behavior, and any private-deployment requirement.
3. Run the same pilot on two finalists. Use the same call script, carrier route, models, tools, voices, and traffic. Record task completion, caller-audible latency, interruption recovery, failed-tool recovery, and cost per successful outcome.
4. Compare total cost, not a headline rate. Include runtime, STT, LLM, TTS, telephony, add-ons, support, implementation, monitoring, and ongoing engineering.

A simple cost model is enough to expose most bundle differences:

monthly cost = connected minutes x per-minute stack cost + plan and capacity fees + implementation and ongoing engineering

Ready to build? Start with Dasha

If you are a technical team that wants to launch production voice agents without operating every runtime component, start with Dasha. Our dashboard and API give you a managed path from browser testing to live phone and web conversations, with provider choice, tools, transcripts, and production operations in one platform.

Explore Dasha's production voice AI platform, or start with 1,000 free minutes.

FAQs

Is an AI voice agent platform the same as a text-to-speech API?

No. Text-to-speech turns text into audio. A production voice agent also needs telephony or media transport, speech recognition, turn detection, conversation state, model orchestration, tools, monitoring, and failure recovery.

Does a vendor's HIPAA, GDPR, or PCI support make my deployment compliant?

No. Compliance depends on your full system and workflow, including carriers, AI providers, tools, storage, staff access, consent, retention, contracts, and data regions. Involve your security, privacy, compliance, and legal teams before launching a regulated use case.

What should I test in an AI voice agent pilot?

Test real call flows, noisy audio, interruptions, slow or failed tools, transfers, burst traffic, and dependency failures. Compare task completion, caller-audible latency, recovery behavior, and cost per successful outcome across the same configuration.