Incident & Near-Miss Intelligence
Screen high-volume event backlogs, identify potentially serious cases, normalize event context and route the right cases for deeper review.
Operations · PSM
Use cases
One evidence layer. Multiple decision environments.
AI-PSM can support operations, reliability, process safety, assurance and executive risk review using the same governed enterprise evidence plus relevant industry knowledge.
Request a DemoAI-Assisted RCFA
Prepare chronology, similar events, missing evidence and candidate causal/contributing factors so investigators start with a stronger evidence package.
Investigation
API RP 754 / 1186 Intelligence
Support consistent process-safety indicator workflows and connect Tier 1–4 information to underlying assets, barriers and causes.
Performance
Asset Integrity + Bad Actors
Connect incident history with maintenance, inspection and barrier condition to expose recurring equipment-centered risk.
Reliability · MI
Corrective-Action Governance
Identify overdue, recurring or potentially ineffective actions and maintain the decision trail behind closure.
Assurance
Enterprise Intelligence & Cross-Site Systemic Learning
Normalize and compare multi-site event and RCFA histories to expose recurring causal patterns, shared equipment and barrier vulnerabilities, lesson-transfer gaps, repeat events and corporate OFIs.
Leadership · Learning
PSE Intelligence Hub · Cooperative Industry Learning
Future participating clients can opt into governed comparison against permissioned, anonymized and aggregated peer PSE and near-miss patterns — expanding learning beyond any one enterprise without exposing another operator’s proprietary event records.
Future · Cooperative Learning
RAGAGEP & Industry Lessons Intelligence
Bring relevant good engineering practice, public incident findings, technical guidance and comparable industry lessons into investigations and enterprise risk reviews so teams can evaluate internal practice against a broader knowledge base.
Assurance · Learning
A practical starting point
Begin with a Five-Year PSE Intelligence Assessment before asking for a full platform commitment.
Test AI-PSM on a known historical dataset: compare prior RCFA findings and corrective actions with additional cross-event patterns, systemic OFIs and relevant industry/RAGAGEP context surfaced by AI-PSM.
Designed for staged adoption.
Early deployments can stay one step removed from immediate operational control: retrospective analysis, decision preparation, SME review and portfolio intelligence first; higher-consequence automation only after validation, governance and client approval.
A practical first experiment
Let AI-PSM challenge five years of known history.
Use your own prior investigations as the benchmark, then extend successful learning across sites and into continuous Sentinel monitoring.