What you get
Cost & Usage Tracking
Every request logged. Break down spend by team, feature, environment, or user with custom metadata headers.
Multi-provider Routing
OpenAI, Anthropic, Gemini, Azure, and Bedrock from a single endpoint, plus OpenAI-compatible providers (Fireworks, Together, DeepSeek, Moonshot, Baseten, Nebius, DeepInfra, Novita). Or ask for an open-weight model and let routing pick the cheapest healthy provider serving it.
Replay
Run real production traffic against a candidate model. Get actual cost, latency, and quality numbers on your workload before you switch.
Evals
Build test suites from logged requests. Define scoring criteria. Run scored evaluations against any model before a change ships.
Experiments
Split live traffic across models by weight, compare cost, latency, and quality per arm, and promote the winner, with no application code changes.
Agent Run Tracking
Group the many LLM calls of one conversation or agent run into a single run, with a rolled-up cost and a nested waterfall of which step drove which calls.
Two deployment modes
Managed: Majordomo runs Steward and the dashboard. Point your SDK at the gateway endpoint, create an API key, and you’re logging requests within minutes. No infrastructure to operate. Self-hosted Steward: You run Steward inside your own VPC. Your prompts and completions never leave your infrastructure. Majordomo receives only metadata: token counts, cost, latency, model name. The dashboard works identically. The right choice for teams with data residency requirements or enterprise customers who need to control where AI data is processed. How it works →How integration works
One config change. Everything else stays the same.Open source
Prefer to run a gateway yourself?majordomo-gateway is a standalone, self-hostable LLM gateway, open source under the MIT license, with the same header conventions, priced and logged to your own Postgres, with nothing phoning home.
GitHub →