How it works
Catalyst sits between your application and your LLM provider. Route requests through the platform by swapping a base URL. Your SDK, provider credentials, and application logic stay the same. Data collection happens at the edge and adds under 10ms of overhead.📍 TODO:MEDIA
Graphic showing how data flows with the gateway installed (app → gateway → provider, with data captured at the gateway layer).
Key concepts
| Concept | Description |
|---|---|
| Gateway | The transparent layer between your app and your LLM provider. Captures traffic with under 10ms overhead. |
| Inference | A single LLM API call captured by the gateway. Records the full request, response, cost, latency, and token counts. |
| Task | A user-defined objective (like “summarize docs” or “classify tickets”) that groups related inferences so you can track each AI feature independently. |
| Metrics | Aggregated cost, latency, error rates, and token usage across your inferences. Filterable by model, task, or provider. |
Next steps
Set up tasks
Group your LLM calls by objective.
Integrate with your LLM provider
Connect your app and start capturing traffic.
Metrics Explorer
See your LLM usage dashboards.
Inference Viewer
Browse individual LLM calls.