Capability
Governance risk and control-gap detection
Identify missing approvals, weak ownership, missing evidence, and misaligned controls across governed AI records with structured severity and confidence scoring.
Feature · AI governance intelligence
Move from passive AI recordkeeping to active governance intelligence.
Give enterprise governance teams one place to surface duplicate AI initiatives, control gaps, and rationalization opportunities with explainable findings, side-by-side review, and auditable human decisions.
The governance problem
AI portfolios grow faster than governance teams can compare, explain, and rationalize them.
Large enterprises often end up with overlapping copilots, duplicate use cases, inconsistent approvals, and hidden control gaps spread across business units. The records exist, but the signal does not. Governance teams discover issues too late, usually through manual review, fragmented reporting, or audit pressure.
SentinelAI adds an intelligence layer on top of the governed records you already maintain so teams can surface explainable findings earlier, compare overlapping assets with context, and route decisions into auditable human workflows.
Proof maturity
The portfolio view is already live; the findings workflow is the next product proof to show.
This page now shows the operating shape of the findings feed, comparison workspace, and audit flow that turn governance intelligence into an actionable reviewer experience. The goal is to make the walkthrough legible before every surface is represented by final production screenshots.
Best demo sequence
1
Start on the portfolio view to frame where attention is needed.
2
Open a finding with evidence, confidence, and linked assets visible.
3
Jump into side-by-side comparison to validate overlap before acting.
4
Finish on the reviewer decision and resulting audit trail.
Product proof
Give reviewers the finding, the evidence, and the next decision in one workflow.
This capability lands best when the product proof is concrete. SentinelAI pairs findings, comparison context, reviewer ownership, and portfolio visibility so teams can move from detection to action without rebuilding the story manually.
Portfolio signal
Start from a governed portfolio view
Portfolio metrics and governance posture make it easier to spot where duplicates, inconsistencies, or unresolved follow-up deserve attention first.
Planned: findings feed and triage
Review findings with explainability and side-by-side context
The dedicated findings feed and comparison workspace are the core new surfaces: confidence-aware triage, linked evidence, compare views, reviewer comments, and auditable outcomes in the same flow.
Step 1
Findings feed
Duplicate use case
92% confidence
Owner missing
Next
Step 2
Compare context
Use case A ↔ B
Shared model
Taxonomy overlap
Next
Step 3
Review outcome
Escalate
Add rationale
Audit event
Done
ExplainabilityReviewer ownershipDecision trail
Planned: comparison workspace
Compare overlapping AI initiatives before you merge, harmonize, or dismiss.
The comparison workspace gives reviewers the side-by-side context they need to see where overlap is real, where specialization is valid, and what action should happen next.
Side-by-side review
Compare overlapping copilots before taking action
Candidate 1
Invoice assistant
Finance ops
Shared summarization flow
Same model family
Linked policy corpus
Candidate 2
Vendor review copilot
Procurement
Overlapping drafting flow
Same vendor base
Similar reviewer path
overlap
AcceptDismissEscalateAdd rationale
Similarity reviewAsset contextGovernance recommendation
Core capabilities
Built for explainable detection, not opaque AI advice.
These capability areas define what SentinelAI adds on top of governed records, workflows, and semantic context.
Capability
Duplicate and overlap detection
Surface likely duplicate use cases, overlapping copilots, and repeated AI functions using metadata, taxonomy, and explainable similarity logic instead of exact-name matching alone.
Capability
Explainable findings
Every finding includes rationale, contributing evidence, confidence, and linked records so reviewers can understand why SentinelAI raised it.
Capability
Findings feed and triage workflows
Work from one queue for risks, gaps, duplicates, and rationalization opportunities with assignment, status tracking, comments, and review actions.
Capability
Human-reviewed rationalization guidance
Turn overlap into actionable merge, harmonize, or keep-separate recommendations while preserving human approval and auditability.
Review workflow
A practical operating flow from detection to governance action.
The governance intelligence loop is intentionally human-centric so findings become trustworthy decision support rather than autonomous enforcement.
Step 1
Surface findings
Analyze governed records across use cases, models, LLM assets, datasets, controls, approvals, and linked metadata to detect gaps, duplicates, and overlap.
Step 2
Review with context
Open finding details, inspect explainability, compare affected assets, and route work to the right reviewer with status and ownership.
Step 3
Act with auditability
Accept, dismiss, escalate, or turn a finding into remediation or rationalization follow-up while preserving evidence and override rationale.
What trust looks like
Explainability, override control, and auditability are part of the product story.
This capability should be presented as enterprise-safe governance intelligence, not generic AI automation.
Explainability
Deterministic evidence, not black-box prose
Show why a finding was raised, which attributes matched, which records were compared, and how confidence was determined.
Human control
AI stays advisory until a reviewer acts
Reviewers can accept, dismiss, escalate, or challenge a finding with structured rationale and override capture.
Auditability
Every outcome stays traceable
Preserve analysis provenance, reviewer actions, override reasons, and downstream decisions in an audit-ready trail.
Enterprise-safe by design
Position the capability as decision support that compliance teams can defend.
The story is stronger when the product makes its safety model explicit: findings are explainable, reviewer actions are accountable, and no portfolio change happens without human governance.
Tenant-scoped analysis and evidenceDeterministic match logic and confidence cuesHuman approval before portfolio actionImmutable override and review history
Recommended proof cue
Pair every surfaced finding with visible rationale, reviewer ownership, and the resulting audit event so trust is demonstrated in-product instead of claimed in copy alone.
Audit timeline
Every finding becomes a traceable governance record.
1
Finding created
SentinelAI records the trigger, matched assets, confidence score, and evidence snapshot.
2
Reviewer assigned
Ownership, SLA, and queue routing are attached so triage work is visible and accountable.
3
Decision captured
Accept, dismiss, escalate, or rationalize actions require structured rationale and supporting context.
4
Downstream follow-up linked
Remediation tasks, portfolio changes, and oversight artifacts stay connected to the original finding.
Related SentinelAI capabilities
Connect governance intelligence to adjacent product workflows.
This capability is strongest when it is presented as part of the broader SentinelAI operating model.
Next step
See how governance intelligence fits into your AI portfolio review process.
Use a live walkthrough to see how SentinelAI surfaces duplication, control gaps, and rationalization opportunities while keeping explainability, human review, and auditability intact.