dograh

dograh is a speech (TTS/STT) tool - Open source voice AI platform. Self-hosted alternative to Vapi and Retell. On Prem, BYOK across Speech to Speech or LLM/STT/TTS, with a visual workflow builder, MCP native and telephony support.

Overview

The open-source, self-hostable alternative to Vapi & Retell — build production voice agents with a drag-and-drop workflow builder. From zero to a working bot in under 2 minutes.

An honest comparison on the axes that matter most to teams evaluating voice AI platforms.

1. Open http://localhost:3010 in your browser. 2. Pick Inbound or Outbound, name your bot (e.g. Lead Qualification), and describe the use case in 5–10 words (e.g. Screen insurance form submissions for purchase intent). 3. Click Web Call — you're talking to your bot.

For detailed deployment instructions including remote server setup with HTTPS, see our Docker Deployment Guide.

• Python SDK — pypi.org/project/dograh-sdk - Node SDK — npmjs.com/package/@dograh/sdk

• Slack — the cornerstone of Dograh AI contributions. Connect with maintainers, discuss features before coding, get help with setup, and stay current on contribution sprints. - GitHub Discussions — share use cases, ask questions, swap workflow recipes. - GitHub Issues — report bugs or request features.

We love contributions! Dograh AI is 100% open source and we intend to keep it that way.

Dograh AI is licensed under the BSD 2-Clause License- the same license as projects that were used in building Dograh AI, ensuring compatibility and freedom to use, modify, and distribute.

dograh is open-source, written primarily in Python, with 4,279 GitHub stars under the BSD-2-Clause license. The latest release is dograh-v1.34.0 (2026-06-03).

Key capabilities

From the project's documentation:

• 100% open source, self-hostable — no vendor lock-in, unlike Vapi or Retell
• Full control & transparency — every line of code is open, with flexible LLM / TTS / STT integration
• Maintained by YC alumni and exit founders, committed to keeping voice AI open
• Languages: English support (expandable to other languages)
• Custom Models: Bring your own TTS/STT models
• Real-time Processing: Low-latency voice interactions

How it fits a local-AI stack

dograh runs on your own hardware, so pair it with a model and a GPU sized to your needs. Use the VRAM calculator to pick a model that fits your card, and see what you can run for hardware guidance. Related speech (TTS/STT) tools in the directory:

• Kokoro TTS
• Miso One / MisoTTS
• Piper TTS
• Sherpa Onnx

Sources

• Source code & docs: dograh-hq/dograh
• Official website: https://app.dograh.com

Stats from GitHub, 2026-06-08.