Pipecat vs LiveKit vs Bolna vs TEN (2026): Best Open-Source Voice AI Framework Ranked

Open-source voice AI is one of the fastest-moving corners of AI infrastructure. Five frameworks dominate the category in 2026: LiveKit Agents, Pipecat, Bolna, Vocode and TEN Framework. All five are free, all five are production-capable, and all five have very different trade-offs. Here's an honest ranking from a team that builds on one of them and contributes to two more.

TL;DR — who wins which fight

• Best overall for production voice platforms → LiveKit Agents. Highest real-time quality, biggest plugin surface, real commercial backing.
• Best for research and prototyping → Pipecat. Cleanest pipeline abstraction, Python-first.
• Best for Indian outbound dialing if you self-host → Bolna. Sarvam + Twilio India defaults out of the box.
• Best for outbound + simple inbound flows → Vocode. Telephony-first, hosted option available.
• Best for novel multi-agent graphs → TEN Framework. Bleeding-edge orchestration model.
• If you just want to ship voice agents, not build a voice AI platform → use a managed stack. ThinnestAI is built on LiveKit Agents (open source), ships open SDKs and exportable configs, and bolts on everything you'd otherwise build yourself: flow editor, Indian phone numbers via Vobiz, DLT/TRAI compliance, INR billing.

Where we stand: ThinnestAI runs on LiveKit Agents in production. Our SDKs, prompts, datasource configs and agent definitions are all exportable — you can lift the work off our platform and run it on raw LiveKit if you want to. We sell the orchestration layer (no-code flow editor, dashboards, multi-tenant billing, Indian-market plumbing), not the runtime. That's why this comparison can be honest — we'd rather help you pick right than oversell.

The shortlist at a glance

Framework	License	Language	Built by	Best for
LiveKit Agents	Apache 2.0	Python, Node	LiveKit Inc (SF, $83M+ raised)	Real-time voice + video, production scale
Pipecat	BSD 2-Clause	Python	Daily.co (SF)	Pipeline-driven voice workflows, research
Bolna	MIT	Python	Bolna (India)	Indian-language voice agents, outbound dialing
Vocode	MIT	Python, TypeScript	Vocode Inc (SF)	Outbound + simple inbound telephony
TEN Framework	Apache 2.0	Multi-language	TEN (open-source consortium)	Graph-based multi-agent orchestration

LiveKit Agents

What it is

LiveKit is the leading open-source WebRTC server. LiveKit Agents is the Python/Node framework built on top that handles real-time voice agents — STT, LLM, TTS, turn detection, interruption handling, multi-agent handoff. It's the underlying real-time engine for many commercial voice AI platforms, including ThinnestAI.

Strengths

• Production-grade real-time engine. Built on the LiveKit WebRTC server, which handles millions of concurrent connections in production.
• Multi-modal. Voice, video, vision — same framework.
• Massive provider integration surface. Plugins for every major STT, LLM and TTS provider.
• Best-in-class turn detection and interruption handling. The hard parts of real-time conversation are handled for you.
• Large community and corporate backing. $83M+ raised, strong GitHub activity, commercial support available.

Weaknesses

• You still build: billing, phone procurement, flow editor, dashboards, compliance, Indic routing, customer UI.
• Python-centric — Node SDK is maturing but Python is the production path.
• Framework, not product — the learning curve is steeper than a managed platform.

Pick LiveKit when

You have senior voice-AI engineers, you want full control over every layer, and you need a production-grade real-time engine under something you're building. LiveKit is the right foundation for a commercial voice AI platform (we know — we chose it).

Pipecat

What it is

Pipecat is an open-source framework from Daily.co for building real-time voice, video and multimodal AI agents. It's pipeline-based — you compose a voice agent by stringing together "frame processors" (STT, LLM, TTS, tools, memory) into a pipeline. Very popular in the research and prototyping community.

Strengths

• Clean pipeline abstraction. Easy to reason about what the agent does — the data flow is explicit.
• Python-first. Feels like writing PyTorch code — researchers love it.
• Strong transport plug-ins. Daily.co for WebRTC, FastAPI for HTTP, custom transports supported.
• Active community and frequent releases. Moving quickly.

Weaknesses

• The pipeline abstraction is clean for simple flows but gets awkward for complex multi-agent workflows.
• Production WebRTC relies on Daily.co (commercial) for best experience. Self-hosted WebRTC transport is more work.
• Smaller plugin ecosystem than LiveKit.
• Phone / SIP integration is thinner.

Pick Pipecat when

You're prototyping quickly, you like the pipeline abstraction, and you're building something novel where you need to compose STT/LLM/TTS with custom frame processors. Pipecat is arguably the best framework for research and early-stage product iteration.

Bolna

What it is

Bolna is an Indian open-source voice AI framework focused on telephony and outbound dialing. It ships with Twilio / Plivo / Exotel integrations out of the box, Indian-language support via Sarvam and Deepgram, and an opinionated "build a voice agent, dial it, measure outcomes" workflow.

Strengths

• Indian-market-first. Sarvam integration, Hindi / Marathi / Tamil support, Twilio India and Plivo defaults.
• Telephony-first. Outbound dialing is a first-class workflow, not an afterthought.
• Opinionated stack. Less decision fatigue — pick STT and LLM, start dialing.
• Active Indian developer community. Lots of Indian startups have kicked tires on it.

Weaknesses

• Smaller team and community than LiveKit or Pipecat — maturity and plugin breadth are limited.
• Less battle-tested at very large scale than LiveKit.
• No managed platform around it — you still run it yourself.
• Real-time conversational latency is good but not at LiveKit's level for heavy production use.

Pick Bolna when

You're an Indian startup or engineering team building voice agents specifically for Indian telephony, you want to self-host the whole stack, and you value opinionated Indian-market defaults over the broader flexibility of LiveKit.

Vocode

What it is

Vocode is an open-source Python (and TypeScript) framework for building voice agents over telephony, browser and custom transports. It's MIT-licensed and ships with first-class Twilio + Vonage integrations, a hosted option for teams who don't want to self-host the SIP plumbing, and a clean abstraction around streaming STT → LLM → TTS.

Strengths

• Telephony-first. Twilio and Vonage are first-class, including outbound dialing, transfer, DTMF.
• Hosted option. Vocode offers a managed cloud if you want to skip the infra.
• Simple, opinionated API. Get a voice agent talking in well under 100 lines of Python.
• TypeScript SDK. Rare in this space — useful if your team is Node-first.

Weaknesses

• Real-time WebRTC quality is meaningfully behind LiveKit for heavy production load.
• Smaller plugin ecosystem than LiveKit or Pipecat.
• India-specific support (Sarvam, Vobiz, Plivo India, DLT/TRAI) is not built-in — you wire it up yourself.
• Less momentum than LiveKit and Pipecat in the last year.

Pick Vocode when

You want to ship a simple outbound dialer or inbound IVR-replacement in a week and you're fine with the Twilio + OpenAI default stack. Especially if your team is TypeScript-first and the Python frameworks feel foreign.

TEN Framework

What it is

TEN Framework is a newer open-source project for multi-modal AI agents. Its pitch is graph-based orchestration — you describe your agent as a directed graph of nodes (STT, LLM, tools, memory) and TEN handles execution. Cross-language, with support for Python, C++, Go and more.

Strengths

• Graph-based orchestration is expressive for complex multi-agent workflows.
• Cross-language. Mix Python and C++ in the same agent for performance-critical paths.
• Multi-modal from the ground up.
• Open-source consortium backing. Not tied to a single commercial company.

Weaknesses

• Newer and less mature than LiveKit or Pipecat — expect rough edges.
• Smaller community and fewer production deployments.
• Cross-language complexity can be overkill for simple voice agents.
• Fewer pre-built provider integrations.

Pick TEN when

You're building a genuinely novel multi-modal agent architecture where graph orchestration maps cleanly to your design, and you have the engineering bandwidth to live on the bleeding edge.

Side-by-side at a glance

Dimension	LiveKit Agents	Pipecat	Bolna	Vocode	TEN
Maturity	Highest	High	Medium	Medium	Low
Community size	Largest	Large	Medium (India-focused)	Medium	Small
Real-time quality	Best	Very good	Good	Good	Good
Indic language defaults	Pluggable	Pluggable	Opinionated (Sarvam)	Pluggable	Pluggable
Phone / SIP	First-class	Via plug-ins	First-class (India carriers)	First-class (Twilio / Vonage)	Via plug-ins
Multi-modal (video / vision)	Yes	Yes	Voice-first	Voice-first	Yes
Hosted option	LiveKit Cloud	Daily.co	Self-host only	Vocode Cloud	Self-host only
Commercial support	LiveKit Inc	Daily.co	Community	Vocode Inc	Consortium
Best for	Production voice platforms	Research + prototyping	Indian outbound dialing	Simple outbound + IVR	Multi-agent research

Where these fall short for Indian businesses

If you're a US/EU developer building a global English voice agent, any of the five frameworks above will get you to production with reasonable engineering effort. The Indian-market story is different. There are five specific problems every Indian business hits — none of which any open-source framework solves out of the box.

• Indian phone numbers. Twilio India is restricted; you need DLT registration for SMS, KYC for outbound voice, and a relationship with an Indian carrier (Vobiz, Plivo India, Exotel, Knowlarity). Every framework above leaves this to you.
• Hindi + Hinglish quality. Defaults assume English. Hindi and code-switched Hinglish need Sarvam or Deepgram Nova with specific tuning, plus an LLM that handles Devanagari and Latin script in the same prompt. Pluggable, but not free — getting Hindi to sound natural at sub-300ms is days of iteration, not minutes.
• 22 Indian languages. Marathi, Tamil, Telugu, Bengali, Gujarati, Kannada, Malayalam, Punjabi — each has different STT/TTS quality cliffs across providers. Routing the right provider per language per turn is non-trivial. No framework ships this opinion.
• TRAI / DPDPA / RBI compliance. Outbound voice campaigns to Indian numbers need DLT scrubbing, time-of-day rules, RBI Fair Practices Code adherence for debt collection, DPDPA consent capture. None of this is in the framework — you build it.
• INR billing + GST. Your customers want to pay in rupees and get a GSTIN invoice. Razorpay integration, GST calculations, monthly invoicing — all on you.

For an Indian engineering team, you can build all of this in 6–9 months of senior engineering. That's the actual cost of "free" open source. For a managed platform like ThinnestAI, the same plumbing is built-in: Vobiz number rental in 5 minutes, Sarvam-first Indic routing, DLT/TRAI defaults, INR billing with GST, all on top of the same LiveKit Agents runtime you'd otherwise self-host.

The hard question: should you self-host at all?

All four frameworks are free. The real cost is not the framework license — it's the engineering time to build everything around the framework that turns it into a product. Specifically:

• No-code flow editor (non-engineers configure flows)
• Phone number procurement and DLT / TRAI compliance
• Billing and invoicing (especially INR + GST for Indian businesses)
• Customer-facing dashboards and analytics
• Observability — call recordings, transcripts, outcome tagging, audit trails
• Opinionated Indian-language routing across providers
• Multi-tenancy, RBAC, SSO for enterprise customers
• Compliance defaults — RBI Fair Practices Code, DPDP Act, IRDAI, DLT

Building all of that from scratch takes a senior engineering team 6–12 months minimum. For most teams, the math says "use a managed platform" — especially if the alternative is to pull 3 engineers off your actual product for a year.

The exceptions are: (1) you're a voice AI platform company yourself, (2) you have compliance requirements that forbid third-party SaaS (self-hosted in your own VPC is the answer), or (3) your engineering team's opportunity cost genuinely is lower than a managed platform's price.

Our honest recommendation

• Building a voice AI product company? Use LiveKit Agents. It's the strongest foundation and commercial support is available.
• Prototyping a research idea? Pipecat. The pipeline abstraction is the cleanest for experimentation.
• Indian startup building your own stack for outbound dialing? Bolna. It's purpose-built for exactly your problem.
• Outbound dialer or simple IVR, Twilio-shaped use case? Vocode. Fastest path to a working dialer.
• Need a multi-modal / multi-agent research architecture? TEN — but expect bleeding-edge roughness.
• Just want to build voice agents for your business, not build a voice AI platform? Use a managed platform. ThinnestAI gives you LiveKit's real-time quality plus everything you'd otherwise build yourself — flat ₹1.5/min, no engineering team required.

Ship it

Open-source voice AI is a real option, and for the right team it's the right call. For most teams building voice agents to serve their business, a managed platform is dramatically faster and usually cheaper once you account for engineering opportunity cost. Specifically for Indian-market voice agents, the cost of building Indian-carrier integration, Indic routing, DLT/TRAI compliance and INR billing on top of any of these frameworks is roughly 6–9 months of senior engineering — which is almost always more expensive than a managed platform's price.

Three next steps depending on where you are:

• Want to see a managed LiveKit-based platform in action? Try the live ThinnestAI demo — it's a real voice agent answering in Hindi, Hinglish or English in under three seconds.
• Curious about the cost math vs DIY? Read our voice AI cost per minute breakdown for India.
• Comparing managed alternatives? See ThinnestAI vs Vapi, vs Sarvam AI, vs Bland, or browse the full comparison index.

And if you want to stay on raw open-source: LiveKit Agents, Pipecat, Bolna, Vocode and TEN Framework all have GitHub-first onboarding docs that are good enough to clone-and-run today.