AI Gateway
OpenAI-compatible proxy with routing, guardrails, PII firewall, caching, budgets, rate limits, and per-key controls — keeping your AI traffic secure and observable.
Workspace
A complete AI workspace for your team: chat with RAG and knowledge bases, 23+ connectors, web search, voice, agents, workflows, and model evaluations.
Deployment & Training
Deploy open models to your Kubernetes cluster or dstack environment. Run LoRA fine-tuning jobs against your own data, entirely on your infrastructure.
Organizations
Every tenant is an organization, and organizations are fully isolated from one another: separate teams, users, API keys, conversations and knowledge bases. Self-serve signup, invite flows and the operator console for managing all orgs are always available — there is nothing to turn on. This is independent of where you run it. A single-team deployment on your own infrastructure is one organization, and works the same way. Themode: onprem / mode: saas config key that used to select between two
models has been removed; see Deployment model.
How it fits into your stack
Key capabilities
- Drop-in OpenAI compatibility — point your existing OpenAI SDK clients at ManyLayers with a single base URL change. No code rewrites.
- 18 provider translations — route to Anthropic, Azure, Gemini, Vertex, Bedrock, Cohere, and 12 more. Your clients always use the standard OpenAI format.
- Settings live in the database — your YAML config seeds initial values; the admin UI overrides them permanently without a restart.
- All data stays on your infrastructure — no telemetry, no external calls except to the AI providers you configure.
Next steps
Requirements
Check what your environment needs before installing.
Quickstart
Get a working gateway running in under 5 minutes.