Trustible — Monitor

Monitor

AI lifecycle oversight

Approved doesn't mean governed. What happens after is what matters.

Most organizations can tell you what AI they've approved. Very few can tell you whether those systems are still operating under the conditions that made them approvable. Trustible gives governance teams the structured workflows, scheduled reviews, and real-time portfolio visibility to prove oversight is ongoing — not just a moment in time.

Continuous AI governance lifecycle

Intake

Manage Risk

Monitor

Comply

The problem

Approval is treated as the finish line. It isn't.

Risk doesn't freeze at the moment of approval. Models change, data drifts, scope expands, and regulations evolve — and most programs have no structured way to catch the gap.

You're running AI that was reviewed once, under conditions that may no longer hold

New data, new users, new scope — and no structured way to catch when the original approval no longer fits.

You can't answer which approved systems are overdue for review right now

The answer lives in a spreadsheet, if it lives anywhere at all.

You rely on use case owners to raise their hand when something changes

They don't — not out of negligence, but because nothing prompts them on when to look or what to look for.

Your program treats approval as the finish line

Regulators under the EU AI Act, NIST AI RMF, and ISO 42001 treat it as the starting line for ongoing oversight obligations.

You have no documented evidence that post-deployment oversight happened

When your next audit arrives, you'll be reconstructing governance history instead of producing it.

Your AI portfolio is growing, with no unified view of its state

Last quarter's systems run alongside two-year-old ones, and you can't see what state any of them are in.

How it works

Here's how Trustible keeps oversight current.

Four capabilities keep governance active after approval — scheduled reviews, structured attestations, real-time portfolio dashboards, and a structured path to re-govern anything that changes.

01 — Scheduled periodic review workflows

Reassessments trigger themselves, on the cadence your program requires.

Trustible automatically triggers reassessment workflows when configured review dates arrive, routing each review to the right owners with full governance context already populated — prior approvals, risk scores, documentation history, and open mitigations — so reviewers focus on judgment, not reconstruction.

Overdue reviews auto-flagged and routed daily
Full context pre-loaded: approvals, scores, mitigations
Cadence matches what your governance program requires

Review queue — Q3

!Resume screening AIOverdue 6d

!Fraud detection modelDue in 4d

Credit risk model — reassessedJun 1

Chatbot v3 — upcomingJul 28

Reviews on schedule88%

02 — Structured attestation check-ins

Capture human judgment at scale — timestamped and linked to the record.

On a configured cadence, Trustible sends performance and quality attestation forms directly to use case owners, capturing structured judgment about whether the system still performs as intended, whether scope or data use has changed, and whether any issues have surfaced. Responses are timestamped and linked permanently to the use case record.

Attestation forms sent to owners on a configured cadence
Confirm performance, scope, and data-use changes
Responses timestamped and linked to the use case record

Attestation — Fraud detection model

Operating within original approved scope?Yes

Any change to data sources or inputs?No

Performance issues since last review?1 noted

Recommend continued operation?Yes

Attested by D. ParkJun 2, 2026

03 — Real-time AI portfolio dashboards

A live view of your entire AI portfolio, board-ready on demand.

Trustible's executive dashboard gives governance leaders a live view of their whole portfolio: risk distribution by department, review status across use cases, overdue reviews, framework readiness, and mitigation coverage. Configurable thresholds trigger alerts when review windows are breached — so your team acts before your auditor asks.

Live portfolio view: risk, review status, coverage gaps
Framework readiness across EU AI Act, NIST, ISO 42001
Threshold alerts fire before review windows are breached

Portfolio oversight

312

Active systems

Reviews overdue

96%

Coverage

EU AI Act

82% ready

NIST AI RMF

74% ready

3 high-risk reviews breach the 30-day SLAAlert

04 — Incident & substantial modification tracking

When something changes, there's a structured path to re-govern it.

A new model version, expanded data use, a scope change, a vendor disclosure, or a reported incident — Trustible provides a structured re-governance path. Substantial modifications trigger new assessment workflows. Incidents are logged, linked to the relevant use cases in the AI Inventory, and tracked through to resolution with a full audit trail.

Substantial modifications trigger reassessment automatically
Incidents logged, linked to use cases, tracked to resolution
Field-level history, time-travel queryable to any point

Change log — Fraud detection model

Model v2.3 deployed

Substantial modification detected automatically

Reassessment triggered

Routed to risk owner · prior context attached

Incident logged: false-positive spike

Linked to use case · tracked to resolution

Re-approval — pending owner review

Full audit trail preserved

60%

shorter governance cycles

100%

of active use cases overseen

12→2h

documentation time per report

Where Trustible fits

Governance-layer oversight, built by practitioners

Ongoing AI oversight isn't just a workflow problem — it's a judgment problem. Trustible's AI governance experts help organizations configure review cadences, attestation questions, and threshold alerts that reflect how risk actually evolves after deployment, not just what a framework checklist requires. They bring experience from regulated industries where ongoing oversight obligations are examined closely, and they stay current as those expectations shift.

That expertise is embedded in the platform itself. Trustible's continuously updated risk taxonomies, incident database, and regulatory mappings mean the intelligence behind your periodic reviews doesn't go stale between your annual policy refresh and the next EU AI Act guidance update.