Tacit AI connects work orders, inspection findings, equipment data, and engineering sources to proposed FMECA and maintenance decisions. Every material statement remains traceable to evidence and subject to authorized review.
Rank candidate systems using customer-approved production-deferment, consequence, recurrence, and cost logic. Each ranking exposes its source data, boundary, and assumptions for operations and reliability review.
Prepare source-linked failure modes, effects, criticality inputs, and candidate mitigating tasks. Tacit AI can use ISO 14224 taxonomy where the operator selects it, while equipment boundaries and final FMECA content remain customer-controlled.
Structure reliability-block and availability scenarios from agreed boundaries and inputs. Decision owners review model assumptions before using results for redundancy, shutdown, or spares choices.
FMECA evidence can inform—but does not perform—RBI, degradation assessment, fitness-for-service, or integrity-management approval. Corrosion, inspection effectiveness, probability-of-failure, and consequence models remain within the applicable integrity workflow and Technical Authority remit.
Proposed tasks, intervals, and work content retain supporting sources and approval status. Exports to SAP or another system of record follow customer mapping, validation, change control, and authorization before release.
Define data residency, access, integration, and model boundaries with IT and operational technology owners. Isolated or disconnected deployment can be assessed against customer infrastructure and security requirements.
Run a scoped baseline evaluation on one deferment or maintenance decision, measuring source coverage, Technical Authority corrections, review effort, and decision value.
Built for asset and operations executives, integrity and reliability leaders, maintenance managers, and Technical Authorities who need to reduce backlog and deferment while preserving engineering accountability.
Bring available work orders, inspection histories, existing studies, OEM sources, and equipment boundaries. Tacit AI identifies conflicts and gaps and prepares proposals for engineering review; it does not treat record volume as evidence quality.
Prepare an initial FMECA and maintenance baseline from approved design, vendor, commissioning, and project sources. Taxonomy choices and assumptions are explicit until operating evidence supports revision.
Tacit AI supports customer-selected methods; it does not certify compliance or replace the analyses and approvals each method requires.
The operator defines the asset boundary, evidence set, Technical Authority, baseline, and acceptance method.
Customer-defined
Select one critical system and deferment, maintenance, or backlog decision. Agree taxonomy, system boundary, source rights, reviewers, and current effort.
Gate
Proceed when the Technical Authority approves scope, sources, and acceptance criteria.
Bounded evaluation
Prepare source-linked FMECA and task proposals. Record corrections, unresolved evidence gaps, review effort, and effect on the selected decision.
Gate
Expand only when reviewers accept the evidence quality and decision value.
Approved rollout
Add systems under approved boundary, integration, revision, and approval controls. New evidence creates proposed changes for review rather than changing controlled records directly.
Gate
Continue while measured value and governance remain acceptable to the operator.
Bring one system boundary, approved evidence sources, and the deferment or maintenance decision under review.
