Do

Dograh – voice agents that pick Recordings over TTS using LLM

Hacker News

Dograh – voice agents that pick Recordings over TTS using LLM

TL;DR: Dograh is an open-source platform to build voice AI agents with drag-and-drop workflows. New in v1.20: Gemini 3.1 live support, Pre-recorded audio support for lower latency and more natural responses. Fully self-hostable, no vendor lock-in. Hi HN, We’re the Dograh team (YC alumni). While building voice bots, we found that wiring WebRTC/ Telephony + STT + LLM + TTS took more time than the bots themselves. Teams are spending weeks on plumbing - handling call flows, extracting variables, dealing with telephony edge cases, and redeploying for small changes. Tools like Vapi/Retell are easy to start with but come with lock-in and platform fees. So we built Dograh: a 100% open-source platform that handles the full stack, with a visual workflow builder and self-hosting by default. Dograh v1.20 introduces two major additions: 1. Gemini 3.1 Live support Run fully real-time voice agents using Gemini’s streaming APIs, without stitching together separate STT + LLM + TTS components. 2. Pre-recorded audio (hybrid voice) Upload real voice clips (greetings, confirmations, etc.), and the agent plays them instantly while using TTS only for dynamic responses. This reduces latency, improves naturalness, and cuts TTS costs. It also includes: - Plug-and-play LLM / STT / TTS (including self-hosted models) - Telephony integrations (Twilio, Vonage, Telnyx) along with Call Transfer - Post-call QA, transcripts, and variable extraction - Observability via Langfuse (OpenTelemetry traces + prompt playground) Try it now: If you have Docker, you can run the below command for a 2-minute setup (no API keys needed out of the box). https://gist.github.com/a6kme/072252bf885270787bbb8376687c67... [ sorry, HN wont let me post the entire command ] Looking Ahead: We’re expanding self-hosted model support: you can already bring any LLM (e.g. Llama, Qwen) or TTS (Kokoro, Voxtral) by configuring API endpoints. We are working on updates that will enable anyone to run everything on a single server - your AI models along with Dograh Orchestration. Looking forward to hearing thoughts of the community.

Share card

Actual performance

4points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, model · Missing: mac, macos, cursor
99%99% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Strong signals: para, including, gemini · Missing: supports, reddit linkedin, podcasting
77%77% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: llama, io, including · Missing: https docs, excited, just released
65%65% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: para · Missing: mobile apps, ios, personal
53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, host, builder · Missing: plus, intuitive, reviews
47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
28%28% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: audio, introduce · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

Similar products

CL
CLI to build voice agents with STT/TTS/LLM in one command38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

CLI to build voice agents with STT/TTS/LLM in one command

Hacker News1
SpeechifyAI Simba Voice Agents
SpeechifyAI Simba Voice Agents95%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Voice agents powered by Simba 3.2 the world's #1 voice model

Product Hunt+161API
Ad
Adversarial voice agents to test your voice system32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Adversarial voice agents to test your voice system

Hacker News1
Gu
Guiding LLM outputs using Zod42%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Guiding LLM outputs using Zod

Hacker News3
Fu
Fusion-runtime – self-hosted voice agents, STT+LLM+TTS in one process52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Fusion-runtime – self-hosted voice agents, STT+LLM+TTS in one process

Hacker News2
Voicebun
Voicebun89%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Build voice agents in seconds

Product Hunt+189Developer Tools
Pi
Pick Your Paranoia40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Pick Your Paranoia

Hacker News10
Pi
Pick One40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Pick One

Hacker News1
ST
STT –> LLM –> TTS pipeline in C69%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

STT –> LLM –> TTS pipeline in C

Hacker News11
Co
CogniSim – Interaction utilites for crossplatform LLM agents53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

CogniSim – Interaction utilites for crossplatform LLM agents

Hacker News4