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Introducing Quravin: production AI tools behind one API

June 1, 2026 · Quravin

Shipping an AI feature usually means gluing together prompt templates, a model client, retries, caching, rate limits and cost controls — over and over, per feature. Quravin packages that work once.

Pipelines, not prompts

Every tool is a versioned pipeline: a typed sequence of steps the runner interprets — cache lookup, prompt render, model call, transform. Because the pipeline is data, you get reproducibility (pin a version), auditability (every run is recorded) and safe iteration (publish a new version without breaking callers).

Serverless and cheap by default

The whole data plane is S3-only — no database to run. The API writes a ticket to S3 and asynchronously invokes a runner Lambda; the browser SDK polls for the result. Idle cost is essentially zero; the dominant cost is the model itself, which we gate with per-org quotas and a daily spend cap.

Try it now

Head to the tools and run a translation right in your browser — no signup. When you’re ready to build, open the Console, create an app, enable the tools you need, and call the SDK with a short-lived token. See the how-to guides to wire your first call.