dograh VS pipecat

If you like Pipecat’s focus on speed, you might also try out our open source, which comes with all the batteries included (knowledge base, telephony/SIP, variables, BYOK any LLM STT TTS, Speech to Speech, etc )

And it's fully OSS- like n8n for voice AI, and you can use it with OpenClaw or Claude code - recently launched MCPs.Github- https://github.com/dograh-hq/dograh, Youtube -https://www.youtube.com/watch?v=sxiSp4JXqws&list=PLDqzGuN7B1...

I've built voice agents before, but when it came to shipping them for production, I couldn't find a platform that worked quickly in 2 minutes - until we started building Dograh. It's an open-source voice AI platform with a visual workflow builder, built-in telephony, and post-call analytics out of the box. Alternative to Vapi, Retell, and Bland, but self-hostable and BSD-2 licensed. You get a canvas where you connect nodes instead of writing Python, so prompt tweaks don't mean a redeploy. Voicemail detection, call transfer, variable extraction, knowledge base, and CRM connectors all come standard. Same feature set whether you self-host or use the managed cloud. It has native support for BYOK (bring your own key) across every layer. Deepgram or Whisper for STT, ElevenLabs or Kokoro for TTS, and any LLM for the brain. Want to run everything locally? Swap in self-hosted models through the UI, no code required. Check it. https://docs.dograh.com/getting-started Youtube link: https://www.youtube.com/watch?v=sxiSp4JXqws Star the Dograh repo ⭐ → https://github.com/dograh-hq/dograh

We built Dograh OSS, an open-source voice AI platform. When we started, we assumed most failures would come from the LLM - bad answers, missed intent, prompt edge cases. So we spent a lot of early effort there.

if anyone is looking to get into this. pipecat is a great open-source repo and community. https://github.com/pipecat-ai/pipecat

Star the Pipecat repo ⭐ →https://github.com/pipecat-ai/pipecat

Over the past month, I've been contributing to Pipecat, the open-source Python framework for building real-time voice and multimodal AI agents. My focus has been on reliability: fixing race conditions, adding resilience mechanisms, and closing gaps that surface in production telephony deployments. This post covers 9 pull requests across pipecat-ai/pipecat and pipecat-ai/pipecat-flows — 4 merged, 2 still open, and 3 closed (superseded or folded into other work), plus code review contributions on other community PRs.

Pipecat is one of the most widely used open-source frameworks for building conversational AI applications. The framework allows developers to create complex dialog systems, enterprise-grade customer support agents, multimodal interactions (video, voice, and images), and video meeting assistants.

My plan is that Espressif’s WebRTC code[0] will hook up to pipe at [1] that gets you the freedom to do whatever you want.

[0] https://github.com/espressif/esp-webrtc-solution

[1] https://github.com/pipecat-ai/pipecat

Heya!

I saw there was a mention of content moderation when the author discussed https://github.com/pipecat-ai/pipecat

But when I went to the github repo, I didn't see anything about that.

I'm loosely related to the content moderation space through my employer, so wanted to learn more about that.

Pipecat looks awesome! I'll run the examples over the weekend and try to see what the integration hooks need to look like: https://github.com/pipecat-ai/pipecat/tree/main/examples

It should be pretty straightforward at first glance!