Same category, but fundamentally different model.
https://github.com/dograh-hq/dograh
We kept hitting the same wall building voice AI systems. Pipecat and LiveKit are great projects, genuinely. But getting it to production took us weeks of plumbing - wiring things together, handling barge-ins, setting up telephony, Knowledge base, tool calls, handling barge in etc. And every time we needed to tweak agent behavior, you were back in the code and redeploying. We just wanted to...
For anyone wanting this production ready out of the box, Dograh is an OSS project built on the same principles and goes much beyond ( https://github.com/dograh-hq/dograh ).
Groq, Flux(Deepgram), instant barge-in cancel, full streaming pipeline etc .but also telephony, echo handling, tool calls for external services, variable extraction, and domain dictionary baked in. All the parts needed in production are already solved.
We are happy to share some technical details for anyone interested. A lot of Dograh’s internal work went into extending the functionality of the pipeline by including custom Frames and Processors, creating a ReactFlow based visual agent builder and creating an Engine that can parse that Agent JSON and call conversational LLM loops with function calling. Also we enhanced the functionality by creating easier access to extracted variables, call transcripts and recordings - things that are needed in any production deployment.
One thing we are still trying to understand better: how teams handle long-running conversations while keeping context tight and cheap. Would love to hear how others have approached that.