We open sourced Vapi – UI included
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 change a prompt and test it in 30 seconds. Thats why Vapi retell etc exist. So we wrote the entire code and open sourced it as a Visual drag-and-drop for voice agents ( same as vapi or n8n for voice).…
What it does
In the maker’s words, at launch
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 change a prompt and test it in 30 seconds. Thats why Vapi retell etc exist. So we wrote the entire code and open sourced it as a Visual drag-and-drop for voice agents ( same as vapi or n8n for voice). Built on a Pipecat fork and BSD-2, no strings attached. Tool calls, knowledge base, variable extraction, voicemail detection, call transfer to humans, multilingual support, post-call QA, background noise suppression, and a website widget are all included. You're not paying per-minute fees to a middleman wrapping the same APIs you'd call directly. You can set it up with a simple docker command. It comes pre-wired with Deepgram, Cartesia, OpenAI , Speechmatics Sarvam for STT, same for TTS, and OpenAI, Gemini, groq, Openrouter, Azure on the LLM side. Telephony works out of the box with Twilio, Vonage , CLoudonix and Asterisk for both inbound and outbound. There's a hosted version at app.dograh.com if self-hosting isn't your thing. Repo: github.com/dograh-hq/dograh Video walkthrough: https://youtu.be/sxiSp4JXqws We built this out of frustration, not a thesis. The tool is free to use and fully open source (and will always remain so), happy to answer questions about the data or how we built it.
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