Open-Source Voice AI Frameworks Compared (2026) — LiveKit, Pipecat, Bolna, TEN
Open-source voice AI is one of the fastest-moving corners of AI infrastructure. Four frameworks dominate the category today: LiveKit Agents, Pipecat, Bolna and TEN Framework. All four are free, all four are production-capable, and all four have completely different trade-offs. Here's an honest comparison from a team that builds on one of them.
Full disclosure: ThinnestAI is built on LiveKit Agents. We credit LiveKit publicly and participate in their community. This post will be fair — you'll see exactly when each framework beats LiveKit for your specific use case. We'd rather help you pick right than oversell one option.
The shortlist
| 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 |
| 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.
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 | TEN |
|---|---|---|---|---|
| Maturity | Highest | High | Medium | Low |
| Community size | Largest | Large | Medium (India-focused) | Small |
| Real-time quality | Best | Very good | Good | Good |
| Indic language defaults | Pluggable | Pluggable | Opinionated (Sarvam) | Pluggable |
| Phone / SIP | First-class | Via plug-ins | First-class (India carriers) | Via plug-ins |
| Multi-modal (video / vision) | Yes | Yes | Voice-first | Yes |
| Commercial support | LiveKit Inc | Daily.co | Community | Consortium |
| Best for | Production voice platforms | Research + prototyping | Indian outbound dialing | Multi-agent research |
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.
- 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. If you want to see how a managed LiveKit-based platform feels, try the live ThinnestAI demo — or browse our BYOK page to see exactly which providers we integrate with and how.