u/Slight_Republic_4242

My previous company got acquired and I stayed on with zero workload. Pure management, basically coasting. Quit anyway because it was killing me slowly. Teamed up with my childhood friend and spent 9 months trying to figure out what to build. We shipped 4 different products during that time. All of them went nowhere.

Then we started looking at voice AI agent platforms like Vapi and Retell. The pricing model really bothered us. $0.05/min platform fee on top of the LLM and TTS costs you're already paying. You're basically renting infrastructure you could own.

So we built Dograh (https://github.com/dograh-hq/dograh) . Open source, self-hostable, bring your own API keys. It's a visual workflow builder for voice agents, similar to what n8n does for general AI agents but specifically for phone calls.

You can set up inbound and outbound call flows with drag and drop. Call transfers, variable extraction from conversations, voicemail detection, knowledge base, tool calls to external APIs. We also built a pre-recorded voice mixing system where you use actual human audio clips for predictable parts of the call (greetings, hold messages, confirmations) and TTS only fires when the agent needs to say something dynamic. Saves a ton on TTS costs and honestly sounds way more natural.

Just shipped Speech-to-Speech support via Gemini 3.1 Flash Live too, which collapses the whole STT+LLM+TTS pipeline into a single connection.

Post-call you get QA scoring with sentiment analysis and full call traces through Langfuse so you can debug what went wrong on a bad call.

We're about 6 months in now. 360+ signups last month, 1M organic impressions in the last 40 days, zero ad spend. Still very early but it's starting to compound.

GitHub: https://github.com/dograh-hq/dograh

BSD-2 licensed

Special thanks to this community that supports me with every post ❤️
Any star to the repo is a blessing ⭐️

Would love honest feedback from this community. What's missing? What would make you actually want to self-host something like this?

Been building voice agents for a while now, and integrated Gemini 3.1 Flash Live into our open source stack as soon as the API went live. Wanted to share some honest observations

The good stuff first. The voice cadence and overall feel of calls is genuinely better than what you get from the classic STT + LLM + TTS pipeline. Turn-taking feels more natural. Interruptions are handled way more gracefully. The model just "gets" conversational rhythm in a way that stitching together STT + LLM + TTS never really achieved. Cost also looks very competitive, which matters a lot in S2S.

Now the stuff nobody seems to be talking about. We averaged around 922ms latency end-to-end in our testing. That's not bad, but it's not the sub-300ms numbers I've seen some people throw around. We were testing from Asia, so region probably plays a role here. Would love to know what others are seeing from US/EU

The other thing that caught us off guard is transcripts. You can't access them live during the call, only after it's done. If you're doing any kind of context stitching or real-time context engineering during conversations, this makes things harder. 

Honestly though I don't think we're going back to the old pipeline. The quality gap in how the conversation actually feels is too big.

We integrated this into Dograh, our open-source voice agent platform (very much like Vapi) , if anyone wants to try it themselves: https://github.com/dograh-hq/dograh

What latency numbers are others getting? And has anyone found a clean workaround for the live transcript limitation?

Six months ago me and my childhood friend started building Dograh, an open-source voice AI agent platform competing with companies (vapi, retell etc)  sitting on millions in funding.

Some backstory. My previous company got acquired. I stayed on with the acquirer, zero workload, pure management, basically coasting. Quit anyway. Teamed up with my childhood friend and we spent 9 months trying to figure out what to build. Built 4 different products during that time and failed miserably. All of them went nowhere.

Then we landed on Dograh. Self-hostable, open-source, visual workflow builder for voice AI calling. Think n8n but for voice agents.

Where we are now, 6 months in. 1M organic impressions in the last 40 days. 360+ signups last month on our cloud platform. 20+ meetings booked from inbound. Turned down a VC term sheet to stay bootstrapped and open-source. Zero dollars on ads.

The thing nobody tells you about competing with deep-pocketed players is that it's crowded and slow for a long time before anything compounds. First three months of writing content felt like talking to nobody.

Still figuring a lot of this out. If you're building something open-source against funded competitors I'd love to swap notes.

GitHub: https://github.com/dograh-hq/dograh

I built an open-source voice AI platform you can run on your own infrastructure.

You pick your LLM, STT, and TTS providers, wire them together in a drag-and-drop builder, and deploy with one Docker command.

Built this because tools like Vapi and Retell are closed, expensive, and you have zero control over your data.

https://github.com/dograh-hq/dograh