We started WaveKat with a simple belief:
Every small business deserves the voice of a big one.
Small businesses miss calls. They can’t afford a front desk or a 24/7 answering service. Meanwhile, enterprise companies deploy sophisticated voice AI that handles thousands of calls a day. That gap shouldn’t exist.
What we’re building
WaveKat is building tools for real-time voice AI. We’re starting with a set of open-source libraries:
- wavekat-core — shared audio primitives like
AudioFrameand sample format conversion - wavekat-vad — voice activity detection with multiple backends (WebRTC, Silero, and more)
- wavekat-turn — turn detection that knows when a speaker is done talking
- wavekat-lab — an interactive dashboard for testing and comparing audio backends
On top of these libraries, we’re building wavekat-voice — an AI phone answering system that plugs into standard SIP/RTP infrastructure. It picks up the phone, has a real conversation, and handles the call — so the business owner doesn’t have to.
Why start with open source?
We believe the foundational technology — VAD, turn detection, audio processing — should be open, auditable, and free to build on. These building blocks shouldn’t be locked behind enterprise contracts.
What’s next
We’re heads-down building. Follow along on GitHub or check back here — we’ll be writing about the engineering behind real-time voice, the tradeoffs we’re making, and what we learn along the way.