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Designed for teams with DS/ML bandwidth who want the tooling and want to run the improvement loop themselves.

How the work happens

System Knowledge: Your team builds the knowledge book: the metric, why it matters, the business and product context, the data landscape, the warehouse tables. It self-updates and self-verifies from the actual work, so it doesn’t go stale. Agent Studio: Your team formulates hypotheses, generates multiple approaches to move the number, and tests them in parallel against a real benchmark.

Who runs the loop

You.

What stays yours

Code, data, and every learning. A per-client service account means nothing leaves your setup.

Time to first win

Your cadence. Connect your sources, stand up a randomized holdout (even 2–3%), and ship.

What you walk away with

A running improvement loop your team owns.

How to start

1

Connect your sources

Wire up your data and tools, see Connectors.
2

Set the metric

Define the number you want to move and how it’s measured.
3

Run a holdout

Stand up a randomized holdout so models train on clean data, then start shipping approaches.