Define release scope
Identify the release candidate, agent/application version, test specification, environment and assurance scope before evaluating results.
- Release ID
- Agent build
- Environment identity
Turn AI testing, evaluation and security results into traceable release evidence and governed GO, NO-GO or REVIEW decisions.
A dashboard is a navigation layer. Release assurance needs a defensible evidence chain that explains what was tested, what failed, what risk remains and why the release decision follows.
Identify the release candidate, agent/application version, test specification, environment and assurance scope before evaluating results.
Combine deterministic, semantic, execution-integrity and security gates with clear pass/fail semantics and documented exceptions.
Allow reviewers to drill from a release statement to the gate, evaluation, conversation, trace and raw observation behind it.
Produce a governed verdict with the evidence and rationale needed by engineering, quality, security and governance stakeholders.
AI release assurance is the controlled process of establishing evidence that an AI system meets required quality, behavioural, execution, security and governance conditions before release.
It should identify the release, system version, test specification, environment, run IDs, evaluator version, gate results, exceptions, underlying evidence and final verdict.
Yes. Release evidence and gates can be incorporated into engineering delivery workflows so assurance is part of the release process.
Bring one business journey and see how Shyena maps, tests, evaluates, secures and connects the evidence to release decisions.
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