Tacit AI connects delay attribution, work orders, defects, OEM sources, and engineering records to governed reliability decisions. Fleet, route, duty, depot, and configuration boundaries stay visible, and authorized engineers approve every revision.
Connect asset-attributable cancellations, delay minutes, defects, removals, and maintenance effort using operator-approved attribution rules. Source records and assumptions remain visible to performance and engineering owners.
Tacit AI prepares traceable RAMS evidence for authorities to assess within a defined lifecycle activity. Applicable duty holders and independent assurance arrangements retain system-safety, risk-acceptance, and safety-case decisions.
Compare evidence across vehicles and infrastructure without assuming equivalence. Proposed reuse respects fleet variant, software and hardware baseline, duty, route, environment, depot practice, and modification state.
Compare current regimes and recovery guidance with defects, failures, sources, and operational context. Tacit AI proposes task, interval, diagnostic, or recovery changes for engineering and operations approval.
Build an evidence pack linking failures to part, batch, configuration, warranty, repair, and service consequence where identifiers support it. Commercial and engineering teams decide supplier action and recovery.
New evidence creates a proposed revision with citations, assumptions, configuration applicability, reviewer comments, and status. Controlled FMEAs, maintenance instructions, and assurance records change only through the operator’s authorized process.
Start with one configured system and a scoped baseline evaluation of attribution quality, source coverage, engineering corrections, review effort, decision usefulness, and compatibility with configuration and change control.
Built for rail operating and asset executives, fleet and infrastructure directors, engineering and RAMS leaders, maintenance delivery, performance teams, configuration managers, and commercial owners managing whole-life cost and supplier recovery.
Use available work orders, delay records, defects, fleet configuration, modifications, prior analyses, and OEM sources. Tacit AI exposes missing identifiers and attribution uncertainty rather than merging unlike assets.
Prepare an initial reliability evidence baseline from requirements, design, supplier, test, and commissioning sources. Lifecycle and safety approvals remain within the project assurance process.
Standards apply by system, lifecycle activity, jurisdiction, contract, and safety classification. Tacit AI supports controlled evidence preparation; it does not confer conformity, authorization, or safety acceptance.
The operator defines boundaries, baselines, assurance interfaces, evidence rights, reviewers, and acceptance criteria before evaluation.
Customer-defined
Select one configured rolling-stock system or infrastructure asset and one availability, delay, maintenance, or supplier decision. Agree attribution and configuration rules.
Gate
Proceed when engineering, performance, and assurance owners approve the evaluation method.
Bounded evaluation
Produce source-linked analysis and proposed revisions. Record attribution disputes, configuration exceptions, engineering corrections, review effort, and decision value.
Gate
Expand only when operator reviewers accept evidence quality and service relevance.
Approved rollout
Add fleets, routes, or depots with approved applicability, integration, revision, and assurance controls. New evidence remains a proposal until authorized.
Gate
Continue while measured service value and governance remain acceptable.
Bring one configuration boundary, the sources you trust, and the availability or delay decision under review.
