Ten Framework
Open-source framework for building real-time voice AI agents with modular STT, TTS, and NLU pipelines you host yourself.
Pick Ten Framework if your team wants to own the voice stack and can absorb the DevOps work — the modular pipeline and plugin architecture let you swap STT, TTS, and NLU pieces independently, and the demo agent shows a working audio + video assistant on GPT 5 out of the box. Skip it if you need a managed service, a visual builder, or vendor-backed support: you'd spend more time on infrastructure than on your agent. If a managed voice stack is the requirement, look at Dialogflow or Voiceflow instead; if you want open source but hosted, that is a different category of tool. The flexibility is real, and so is the operational bill.
Verified 7d ago · liveness 63/100 · cite: rightaichoice.com/tools/ten-framework
- Developers building custom voice assistants from scratch
- Teams creating conversational IVR on their own infrastructure
- Open-source enthusiasts customizing AI agent pipelines
- Startups prototyping voice interfaces with full control
- Non-developers seeking no-code visual builders
- Teams that need a fully managed cloud service
- Organizations requiring vendor support SLAs
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Skip Ten Framework if you need a managed endpoint, a visual builder, or a contractual support SLA — the framework expects you to run and debug the voice pipeline on your own infrastructure.
You pay for the GPUs or cloud instances that host the pipeline, plus the STT, TTS, and LLM API calls you plug in — the framework itself is free but the pipeline is not.
The framework itself costs nothing to download; the real spend is infrastructure and the model APIs you connect. That puts it below per-seat managed voice platforms if you already run servers, and above them if you would otherwise buy convenience. Compare against Dialogflow or Voiceflow on total cost of ownership, not licence fee.
In short
Ten Framework — Open-source framework for building real-time voice AI agents with modular STT, TTS, and NLU pipelines you host yourself. Best for Developers building custom voice assistants from scratch, Teams creating conversational IVR on their own infrastructure, Open-source enthusiasts customizing AI agent pipelines. Free to use.
What people actually say about Ten Framework — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
51 mentions across 4 sources (Hacker News, YouTube, GitHub, Lemmy) · researched Aug 1, 2026.
Average across the 4 sources that answered — each source counts once, not each post.
- +Free and open-source with self-hosting full data control.
- +Multi-language SDKs (Go, Python, C++, Node) for extension development.
- +Modular plugin architecture enables deep customization.
- +Low-latency voice pipeline with dedicated VAD component.
- +Broad integrations for STT, TTS, and NLU models.
- −Requires advanced technical expertise to deploy and maintain.
- −Sparse user community and few real-world usage reports.
- −UI design criticized as unfriendly, with naff icons.
- −Documentation considered insufficient by early adopters.
- −Large open issues backlog (220) raises maintenance concerns.
- • Infrastructure costs for running real-time audio processing
- • Paid integration services for STT/TTS/NLU models
- • Time and expertise required for setup and maintenance
Viability Score
How well maintained and how widely used is Ten Framework? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- Real-time voice interaction pipeline
- Speech-to-text (STT) integration
- Text-to-speech (TTS) integration
- Natural language understanding (NLU)
- Intent recognition
- Multi-language support
- Modular plugin architecture
- Low-latency audio processing
- Extensible API for backend integration
- Pre-built agent examples
- Self-hosted deployment on your own infrastructure
- Open-source community contributions
- Audio and video input in the example agent
- Microphone and camera device selection
- Selectable language model (demo shows OpenAI GPT 5)
About Ten Framework
Ten Framework (TEN) is an open-source, self-hosted framework for developers building real-time voice agents without handing the stack to a vendor. Instead of a managed cloud product, it ships modular building blocks — speech-to-text, intent recognition, natural language understanding, and text-to-speech — wired together by a plugin architecture, so you choose which models sit at each stage of the pipeline. You assemble the pipeline, tune latency per stage, and keep voice data on your own infrastructure. The public demo on agent.theten.ai is a multi-purpose voice assistant example that connects audio and video with a microphone and camera input, and its model selector shows OpenAI GPT 5 handling the language side — a useful signal that TEN is model-agnostic rather than tied to one vendor's speech stack. The audience is developers, not no-code builders: the examples repo on GitHub has drawn roughly 11.1K stars, so there is a real community around the project if you need to read code before you commit. Multi-language support and pre-built agent examples shorten the path from install to working demo. Compared with managed platforms such as Dialogflow or Voiceflow, the tradeoff is deliberate: full customization and data control in exchange for operational responsibility. There are no per-call cloud fees and no vendor deciding when your models get swapped out, but uptime, scaling, audio quality, and pipeline debugging all land on your team. Ten Framework is for coding teams who value sovereignty over simplicity.
Behind the Verdict
Ten Framework's central pitch is that you should not have to rent your voice pipeline. Everything in the project follows from that: modular STT, TTS, NLU and intent-recognition components, a plugin architecture for bringing your own models, and an extensible API so the agent can talk to your existing backend. The strongest evidence that this works is the example agent hosted at agent.theten.ai — a multi-purpose voice assistant that handles audio and video simultaneously, takes microphone and camera input, and exposes a model picker currently showing OpenAI GPT 5 with English selected. That last detail matters more than it looks. It shows the framework treats the language model as a swappable component, not as the product, which is the opposite of how most voice-agent startups are built. Where it fits: teams building conversational IVR, hands-free assistants for devices, multilingual booking agents, or voice support bots where the audio cannot leave your infrastructure. Multi-language support and pre-built agent examples mean you are not starting from an empty repo. The GitHub project's ~11.1K stars suggest enough other people have walked the same path that community answers exist for common problems. Where it does not fit: anyone who wants a visual builder, a managed endpoint, or a support contract. There is no SLA and community help runs through GitHub. There is no bundled analytics dashboard, so you will wire up your own observability for latency, transcription accuracy, and call outcomes. Scaling is a function of your infrastructure, not the project's — the framework will not save you from a badly sized cluster or a noisy audio path. Debugging a real-time pipeline is harder than debugging a request/response API, and you should budget engineering time for audio quality tuning that no documentation will do for you. The honest summary: Ten Framework is infrastructure, and it behaves like infrastructure. If your team already runs containers and thinks in terms of pipelines, it is a credible open-source base. If your team's value is in the conversation design rather than the plumbing, a managed platform will get you to production faster and cheaper once you price in the engineering hours.
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Real-world workflow fit
Concrete scenarios for the personas Ten Framework actually fits — and what changes day-one when you adopt it.
They clone the repo, stand up the pipeline on a container host, point STT and TTS at their preferred providers, and wire the NLU stage to their existing support knowledge base.
Outcome: A working voice FAQ agent they can call from a browser, with all audio staying on their own infrastructure.
They assemble an STT → intent → TTS pipeline using the modular components, reuse a pre-built agent example, and extend the API so bookings land in their scheduling backend.
Outcome: A voice booking flow that handles multiple languages without a per-call vendor fee.
They run the example audio-and-video agent, select a language model from the dropdown, and test microphone and camera input against a hands-free interaction.
Outcome: A demo they can put in front of stakeholders before committing to a full build.
Use Cases
- Build a voice-based customer support agent that answers FAQs from your own backend
- Create a hands-free virtual assistant for smart devices and kiosks
- Deploy a multilingual voice bot for appointment booking
- Develop a conversational agent for interactive voice response systems
- Prototype an audio-plus-video conversational agent with camera input
Models Under the Hood
as of 2026-09-29
Limitations
- As an open-source framework, scaling depends entirely on your deployment infrastructure.
- There is no managed cloud option and no SLA; support runs through the community on GitHub.
- You need DevOps expertise to self-host and maintain the system, and no pre-built UI dashboards or analytics are included, so latency, accuracy, and call-outcome monitoring are yours to build.
- Real-time audio pipelines are harder to debug than request/response APIs, so budget engineering time for audio quality tuning before you promise production quality.
as of 2026-10-03
Verification history
We have re-verified Ten Framework 8 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
Showing the 6 most recent of 8 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Ten Framework tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Open Source
$0
Ideal for
Development teams with DevOps capacity who want to self-host a real-time voice pipeline and keep audio on their own infrastructure.
What this tier adds
Starting tier: the framework itself at no licence cost, with self-hosted deployment, modular STT/TTS/NLU components, and a plugin architecture — you supply the infrastructure and model API spend.
Where the pricing makes sense
The company stage and team size where Ten Framework's pricing actually pencils out — and where peers do it cheaper.
The framework itself costs nothing to download; the real spend is infrastructure and the model APIs you connect. That puts it below per-seat managed voice platforms if you already run servers, and above them if you would otherwise buy convenience. Compare against Dialogflow or Voiceflow on total cost of ownership, not licence fee.
Setup time & first value
How long it actually takes to get something useful out of Ten Framework — broken out by persona, not the marketing-page minute.
A developer comfortable with containers can get the example agent running in an evening; a production pipeline with your own STT, TTS, NLU, and backend wiring is a multi-week project once you factor in latency tuning and audio testing.
Switching to or from Ten Framework
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From a managed voice platform: re-implement intents and prompts as pipeline stages and point the API layer at your own backend.
- →From a hand-rolled STT/TTS script: replace your glue code with the framework's modular components and plugin interfaces.
- →From a single-vendor voice SDK: swap the model calls behind the plugin layer so you can change providers later without a rewrite.
- ↗To a managed voice platform: export your intent definitions and prompts and rebuild the flow in the vendor's console.
- ↗To a hosted open-source alternative: keep your model configuration and re-host the pipeline behind a managed runtime.
- ↗To a cloud provider's speech stack: port the STT and TTS stages to native cloud services and drop the framework layer.
Resources & Guides
Tutorials & Learning
TEN Framework: Voice AI That Can Actually Be Interrupted
Better Stack
Getting Started with TEN Framework and TEN Agent in Under 5 Minutes
Elliot Chen
YouTube returned 6 videos for “Ten Framework”, and we withheld 4: 4 did not mention Ten Framework. Showing the 2 we can prove are about Ten Framework.
Official links
Tools that pair well with Ten Framework
Common stack mates teams adopt alongside Ten Framework, with the specific reason each pairing earns its keep.
Liberate
Insurance-native AI agents that resolve calls, emails, SMS, and digital FNOL end-to-end inside your core systems.
DeepCura
DeepCura bundles seven clinician-supervised AI agents — scribe, receptionist, billing coder, inbox, intake, research and chart canvas — into one
ElevenLabs
ElevenLabs generates ultra-realistic AI voice, music, dubbing, and voice agents from one shared credit pool.
Featured Head-to-Head Comparisons
Ten Framework vs Locus Robotics
These tools serve completely different domains. Locus Robotics is a RaaS hardware+software solution for warehouse automation, ideal for high-volume fulfillment centers needing 2-3x productivity gains. Ten Framework is a free, open-source toolkit for developers building custom voice AI agents. Your choice depends on whether you need physical robots in a warehouse or voice interface software. There is no direct competition.
Ten Framework vs Presto Voice
Choose Ten Framework if you're a developer wanting full control and customization for a general-purpose voice AI agent, and you're willing to self-host. Choose Presto Voice if you run a QSR chain and need a battle-tested, turnkey drive-thru automation solution with proven ROI from upselling — but be prepared for custom enterprise pricing and minimal transparency.
Ten Framework vs Truleo
Choose Truleo if you're in law enforcement needing an all-in-one intelligence platform to connect siloed data and automate investigations. Choose Ten Framework if you're a developer building a custom conversational voice AI from scratch and want free, open-source control. These tools serve completely different buyers—there's no overlap.
Alternatives to Ten Framework
View all
Liberate
Insurance-native AI agents that resolve calls, emails, SMS, and digital FNOL end-to-end inside your core systems.
DeepCura
DeepCura bundles seven clinician-supervised AI agents — scribe, receptionist, billing coder, inbox, intake, research and chart canvas — into one
ElevenLabs
ElevenLabs generates ultra-realistic AI voice, music, dubbing, and voice agents from one shared credit pool.
Frequently Asked Questions
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