Connected operating context
Normalize and link event, asset, barrier, maintenance, inspection, action and operating evidence.
AI-PSM Sentinel brings fragmented operational evidence and governed external knowledge into one contextual decision-support layer without requiring clients to replace their existing systems of record.
Request a DemoInputs can include incidents, work orders, inspection/RBI, barriers, historian signals, asset hierarchy, appropriately licensed standards and curated public industry knowledge. AI-PSM applies controlled domain logic, retrieval and AI assistance to turn those inputs into event, asset, barrier, action and learning intelligence.
Normalize and link event, asset, barrier, maintenance, inspection, action and operating evidence.
Apply deterministic classifications, screening criteria, taxonomies and governed site logic wherever rules should control.
Retrieve applicable external knowledge with source provenance and permissions so internal evidence can be interpreted against a broader experience base, including future permissioned and anonymized PSE Hub patterns where available.
Use models for similarity, pattern finding, narrative interpretation, evidence preparation and decision support while preserving source traceability.
Combine potential consequence, recurrence, barrier condition, asset criticality and other approved signals to focus review.
Keep SMEs responsible for safety-critical conclusions, investigation depth, corrective actions and approvals.
Preserve source evidence, system outputs, reviewer overrides, rationale, approvals and action history.

AI-PSM can sit above and across EHS, maintenance, inspection, reliability and operating systems. The objective is to create contextual intelligence and follow-through while preserving established enterprise workflows.
Compare what AI-PSM finds with what prior investigations already concluded, then decide whether continuous enterprise intelligence is worth operationalizing.