# Dograh — Open-Source Self-Hosted Voice AI Platform

> Dograh is an open-source voice AI platform for building conversational voice agents with telephony support. It offers a self-hosted alternative to cloud voice APIs with a visual workflow builder, MCP integration, and support for speech-to-speech and LLM-based pipelines.

## Install

Save in your project root:

# Dograh — Open-Source Self-Hosted Voice AI Platform

## Quick Use
```bash
git clone https://github.com/dograh-hq/dograh.git
cd dograh
docker compose up -d
# Open http://localhost:3000 for the workflow builder
```

## Introduction
Dograh provides the infrastructure for building voice AI agents that handle phone calls, voice interactions, and real-time conversations. It runs on your own servers, giving you full control over voice data and eliminating per-minute cloud API costs.

## What Dograh Does
- Processes inbound and outbound voice calls with AI agents
- Provides a visual no-code workflow builder for designing call flows
- Supports speech-to-speech and LLM-driven conversation pipelines
- Integrates with telephony systems via SIP and WebRTC
- Connects to local LLMs and TTS/STT models for on-premise deployment

## Architecture Overview
Dograh is built in Python with a modular pipeline architecture. Voice input flows through configurable stages: speech-to-text, language model processing, and text-to-speech. The visual workflow builder generates pipeline configurations that the runtime engine executes. Telephony integration uses Asterisk ARI for SIP connectivity, while WebRTC handles browser-based voice interactions.

## Self-Hosting & Configuration
- Deploy with Docker Compose for a complete stack setup
- Configure telephony providers through the web dashboard
- Connect your own STT, LLM, and TTS models or use integrated defaults
- Set up SIP trunks for production phone number integration
- Scale horizontally by adding worker nodes for concurrent call handling

## Key Features
- Visual workflow builder for designing voice agent logic without code
- Native MCP integration for connecting AI agents to external tools
- Support for both cloud and local AI model backends
- Real-time speech-to-speech mode for low-latency conversations
- Telephony-ready with SIP, WebRTC, and PSTN connectivity

## Comparison with Similar Tools
- **Vapi** — cloud-based voice AI API with per-minute billing; Dograh is self-hosted with no usage fees
- **Retell AI** — managed voice agent platform; Dograh provides equivalent features as open-source software
- **LiveKit Agents** — real-time communication focused on WebRTC; Dograh adds telephony and visual workflow design
- **Pipecat** — Python framework for voice pipelines; Dograh adds a no-code builder and telephony integration on top

## FAQ
**Q: Can Dograh handle production phone calls?**
A: Yes. It integrates with SIP trunks and supports inbound and outbound calling through standard telephony protocols.

**Q: What AI models does it support?**
A: It works with any OpenAI-compatible API, local models via Ollama, and specialized STT/TTS engines like Whisper and Piper.

**Q: How many concurrent calls can it handle?**
A: Concurrency depends on your hardware and model choices. Worker nodes can be scaled horizontally for higher throughput.

**Q: Is it suitable for customer service automation?**
A: Yes. The workflow builder supports conditional logic, knowledge base lookups, and handoff to human agents.

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


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Source: https://tokrepo.com/en/workflows/asset-173db922
Author: AI Open Source