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Use case

Learning and optimization, built in.

Every run teaches the next one. Baltor is designed to learn from what worked and set up the next task better.

Every run leaves a record

What the step asked for, which files it used, which model ran it, how long it took and whether the result was accepted.

The next task starts smarter

Records of what worked shape the next setup: the files a step is offered, the model it runs on and how the task is broken down.

Measured, not guessed

When two ways of doing a step compete, the choice follows recorded results, and a change waits until there is enough evidence to trust it.

A library that keeps getting better

New vetted skills, tools and plugins keep arriving, items that stop working are withdrawn, and what customers never find is reworked.