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Feature · Release governance

Govern AI-system promotions with release records built for oversight

SentinelAI gives teams a governed release timeline for AI systems, tying each rollout to approval state, dependency snapshots, rollback references, and evaluation-aware promotion controls.

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What this area covers

Release governance makes AI deployment decisions visible and durable. Teams can create release records for runtime AI systems, route them through approval and promotion steps, preserve rollback pointers, and invalidate records automatically when prompts or retrieval dependencies change.

Related product areas

  • AI systems

    Track governed runtime systems that combine models, approved use cases, datasets, release state, and readiness into one operational record.

  • Prompt registry

    Govern versioned prompts, retrieval settings, linked AI systems, and evaluation posture from a dedicated prompt operations record.

  • RAG sources

    Register governed retrieval sources with ingestion status, version history, citation context, and AI-system linkage.

  • Evaluation suites

    Define governed prompt evaluation suites with baselines, regression thresholds, run evidence, and release-blocking posture.

  • Governance cases

    Coordinate alerts, findings, remediation, evidence posture, SLA deadlines, and closure outcomes in one shared case workspace.

  • Compliance workflows

    Operationalize evidence collection, control tracking, remediation, and framework mapping across AI systems.

Core capabilities

Built to support production governance work

Release records for AI systems

Anchor each rollout to an AI system with a governed version, release name, target environment, and descriptive metadata.

Approval and promotion workflow

Move records through draft, pending approval, approved, released, rejected, and revoked states with clear workflow transitions.

Dependency snapshots

Preserve the linked prompt and RAG-source set associated with the release so reviewers know what was part of the promotion decision.

Rollback references

Record rollback pointers and historical release relationships so teams can investigate and recover from release issues faster.

Dependency invalidation

Mark releases for re-review when linked prompts or sources change, making it harder for approvals to drift away from the current dependency state.

Target users

  • Release and platform owners coordinating governed AI-system promotions
  • AI governance teams that need deployment state tied to approval and dependency history
  • Prompt, retrieval, and ML teams whose changes can invalidate a prior release decision
  • Risk and assurance stakeholders reviewing whether release evidence is still current

Governance value

  • Makes AI release approvals reviewable instead of leaving them inside developer tooling alone
  • Improves traceability between runtime promotion decisions and the dependencies they relied on
  • Connects evaluation posture and rollback planning to the same governed release record
  • Surfaces when a once-approved release needs re-review because supporting assets changed
  • Helps teams explain release readiness to governance councils and auditors with less reconstruction

How teams use it

A practical operating flow for this feature family

Step 1

Create a governed release record

Attach the rollout to the AI system, capture the target environment, and preserve the current prompt and source dependency set.

Step 2

Run approval and promotion steps

Move the record through review, approval, promotion, rejection, or revocation with the surrounding governance context attached.

Step 3

Respond to dependency change

Invalidate or re-review release records when prompts, sources, or evaluation posture change after approval.

Continue exploring

Explore how SentinelAI connects adjacent governance workflows

AI systems

Track governed runtime systems that combine models, approved use cases, datasets, release state, and readiness into one operational record.

Prompt registry

Govern versioned prompts, retrieval settings, linked AI systems, and evaluation posture from a dedicated prompt operations record.

RAG sources

Register governed retrieval sources with ingestion status, version history, citation context, and AI-system linkage.

Evaluation suites

Define governed prompt evaluation suites with baselines, regression thresholds, run evidence, and release-blocking posture.

Governance cases

Coordinate alerts, findings, remediation, evidence posture, SLA deadlines, and closure outcomes in one shared case workspace.

Compliance workflows

Operationalize evidence collection, control tracking, remediation, and framework mapping across AI systems.