
Package the evidence behind a model release
Build an attributable model release record, reuse unchanged pipeline outputs, and recompute reports and decisions when their dependencies change.
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Build an attributable model release record, reuse unchanged pipeline outputs, and recompute reports and decisions when their dependencies change.

Add static model artifact scanning before registry promotion, preserve scan evidence, check coverage, and bind approval to immutable artifact digests.

Connect experiment records, dataset versions, model artifacts, and review decisions into a reusable ML knowledge repository with Polyaxon.

Establish model trust through provenance, artifact inspection, reproducible evaluation, approval, runtime verification, monitoring, and rapid revocation.