Crystallize is a lightweight Python framework for rigorous, reproducible data science experiments. Define modular pipelines, apply treatments as experimental variations, and verify hypotheses with statistical tests, all with built-in caching, immutability, and parallelism for trustworthy, efficient results.

A meta-experimental framework exploring quantum feedback structures, observer-driven alignment, and the role of intent absence in circuit evolution.