We learn to speak before we learn to read.
Voice is the most natural interface we have.
We just raised a $100M to make building voice AI as easy as a web app.
Combine LiveKit's programmable audio pipeline with @inworld's state-of-the-art TTS and natural-language steering for emotionally grounded, turn-based dialogue and instant feedback
Our @livekit partner story explores how Inworld’s speech models and LiveKit’s realtime infrastructure help developers build voice applications that can scale with their users.
Through Inworld’s integration with the LiveKit Agents framework, developers can use pre-built or custom
“In today’s world, ‘low code’ really just means ‘low customization.’”
@_kyleshechtman and @chasef07 started Acuity Health on a low-code platform, hit a wall, and rebuilt on LiveKit. Now 80% of patient calls are fully handled by their agents, and most bookings take under a
Two small models we trained for voice agents: turn detection knows when the user is actually done talking, adaptive interruption knows “uh huh” isn’t an interruption.
Free for agents on LiveKit Cloud. Starting today, self-hosted agents can run them in production too: a free
@anam_ai ran its new blind benchmark on a LiveKit pipeline, with the same speech recognition, LLM and voice for every provider, so the only thing that changed was the avatar.
If you're building a voice agent with LiveKit Agents, you can give it a face in a few lines of code.
Cara-4.1 Express is now live at @Anam__ai
Faster and more expressive than cara-4 with better lip sync and stronger prompt adherence. It also handles much wider framings for custom avatars.
We ran blind human evals: 85% of raters scored Anam higher than HeyGen, 88% higher than
