GraphCanon updated 3w · GitHub synced 3w · 33 views this month
Decision brief
Self-hosted voice AI platform with speech-to-speech, LLM integration, telephony support
Good fit when
- You need on-premise deployment for better security or data control
- Require BYOK and native MCP (Multi-cluster Placement) support
Avoid when
- Seeking cloud-managed services without self-hosting capabilities
- Need real-time collaboration with non-local models in the cloud
Observed Jul 17, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Very active (0d since push)
- As of 3w
- Provenance
- Not a fork · Organization account
- As of 3w
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install dograhSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Dograh is a self-hosted alternative to Vapi and Retell, offering features for on-prem deployment, speech-to-speech, LLM integration, telephony support, with a visual workflow builder.
Capability facts
- Languages
- python
Source: github.language · Jul 29, 2026
Categories
Tags
README
Self-Hosted Deployment
For detailed deployment instructions including remote server setup with HTTPS, see our Docker Deployment Guide.
Getting Started
- 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
📄 License
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.
For agents
This page has a .md twin and JSON over the API.