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.

📖 Docs  ·  📜 BSD 2-Clause

• 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

Featured by Better Stack — a hands-on look at Dograh

📺 Prefer a 2-minute product walkthrough? Click here.

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

Note We collect anonymous usage data to improve the product. You can opt out by setting the ENABLE_TELEMETRY to false in the below command.

Note If you wish to run the platform on a remote server instead, checkout our Documentation

curl -o docker-compose.yaml https://raw.githubusercontent.com/dograh-hq/dograh/main/docker-compose.yaml && REGISTRY=ghcr.io/dograh-hq ENABLE_TELEMETRY=true docker compose up --pull always

Note First startup may take 2-3 minutes to download all images. Once running, open http://localhost:3010 to create your first AI voice assistant! For common issues and solutions, see 🔧 Troubleshooting.

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.

🔑 No API keys needed. Dograh ships with auto-generated keys and its own LLM / TTS / STT stack. Connect your own keys for LLM, TTS, STT, or Telephony (e.g. Twilio, Vonage, Telnyx) anytime.

• Telephony: Built-in telephony integration like Twilio, Vonage, Vobiz, Cloudonix (easily add others), with support for transferring calls to human agents
• Languages: English support (expandable to other languages)
• Custom Models: Bring your own TTS/STT models
• Real-time Processing: Low-latency voice interactions

• Zero Config Start: Auto-generated API keys for instant testing
• Python-Based: Built on Python for easy customization
• Docker-First: Containerized for consistent deployments
• Modular Architecture: Swap components as needed

• Test Mode: Try your agent end-to-end before publishing, with no production calls or data affected
• In-Dashboard Web Calls: Talk to your bot directly while building — no telephony setup required
• QA Node: A built-in workflow node that analyzes prompt quality across your other nodes

Refer Local Setup

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

Visit https://www.dograh.com for our managed cloud offering.

You can go to https://docs.dograh.com for our documentation.

👋 Coming from the Better Stack video? Drop your use case in our pinned GitHub Discussion — we read every reply and the founders personally onboard early adopters.

• 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.

👉 Join us → Dograh Community Slack

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

• Fork the repository
• Create your feature branch (git checkout -b feature/AmazingFeature)
• Commit your changes (git commit -m 'Add some AmazingFeature')
• Push to the branch (git push origin feature/AmazingFeature)
• Open a Pull Request

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.

Built with ❤️ by Dograh (Zansat Technologies Private Limited) Founded by YC alumni and exit founders committed to keeping voice AI open and accessible to everyone.

⭐ Star us on GitHub | ☁️ Try Cloud Version | 💬 Join Slack