Bifrost AI Gateway

The fastest way to build AI applications that never go down

Bifrost is a high-performance AI gateway that unifies access to 23+ providers (OpenAI, Anthropic, AWS Bedrock, Google Vertex, and more) through a single OpenAI-compatible API. Deploy in seconds with zero configuration and get automatic failover, load balancing, semantic caching, and enterprise-grade features.

Quick Start

Go from zero to production-ready AI gateway in under a minute.

Step 1: Start Bifrost Gateway

# Install and run locally
npx -y @maximhq/bifrost

# Or use Docker
docker run -p 8080:8080 maximhq/bifrost

Step 2: Configure via Web UI

# Open the built-in web interface
open http://localhost:8080

Step 3: Make your first API call

curl -X POST http://localhost:8080/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "openai/gpt-4o-mini",
    "messages": [{"role": "user", "content": "Hello, Bifrost!"}]
  }'

That's it! Your AI gateway is running with a web interface for visual configuration, real-time monitoring, and analytics.

Complete Setup Guides:

• Gateway Setup - HTTP API deployment
• Go SDK Setup - Direct integration

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Enterprise Deployments

Bifrost supports enterprise-grade, private deployments for teams running production AI systems at scale. In addition to private networking, custom security controls, and governance, enterprise deployments unlock advanced capabilities including adaptive load balancing, clustering, guardrails, MCP gateway and and other features designed for enterprise-grade scale and reliability.

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Key Features

Core Infrastructure

• Unified Interface - Single OpenAI-compatible API for all providers
• Multi-Provider Support - OpenAI, Anthropic, AWS Bedrock, Google Vertex, Azure, Cerebras, Cohere, Mistral, Ollama, Groq, and more
• Automatic Fallbacks - Seamless failover between providers and models with zero downtime
• Load Balancing - Intelligent request distribution across multiple API keys and providers

Advanced Features

• Model Context Protocol (MCP) - Enable AI models to use external tools (filesystem, web search, databases)
• Semantic Caching - Intelligent response caching based on semantic similarity to reduce costs and latency
• Multimodal Support - Support for text,images, audio, and streaming, all behind a common interface.
• Custom Plugins - Extensible middleware architecture for analyti