Automotive

Late risk discovery turns engineering change into launch cost.

Tacit AI prepares source-linked FMEA evidence from approved design, process, supplier, and field records. Engineers review every proposed rating, control, and change before it enters the program record.

Review one subsystem
See how it works

1–10/day vs 1/week
structured FMEAsper engineer

100% source-linked
every rating and controltraces to an approved record

DFMEA → CP
design risk throughprocess controls

Where Tacit AI supports the decision

Move from fragmented evidence to review-ready FMEA faster.

Establish the DFMEA baseline

Draft from specs, BOMs, drawings, and prior FMEAs. Every proposed rating and control links to its source.

Design FMEA details

Trace design risk into process controls

Map DFMEA characteristics to PFMEA, control plan, and DVP&R. Expose gaps before program review.

Process FMEA details

Match supplier FMEA evidence

Compare supplier FMEAs and PPAP elements against OEM requirements. Flag misalignment before it enters the record.

Connect field and warranty data

Link warranty, 8D, test, and return records to affected FMEA content. Configuration differences preserved.

Prepare PPAP-ready output

Export control plans, SC/CC/HIC classification, DVP&R, and work instructions in the required OEM format.

Close the Reverse FMEA loop

Structure shop-floor findings back into PFMEA and control-plan content. Full trail from finding to disposition.

R-FMEA details

The platform

Characteristic-level traceability, from design risk to process controls.

Click to pause

“We evaluated Tacit AI for Design FMEA on a critical power electronics subsystem. The structured output and the approach to connecting information exceeded expectations.”

Design Engineer, Top 10 Global OEM — separate DFMEA evaluation, Europe

Who it’s built for

Teams who own launch risk.

VP Quality, APQP, Supplier Quality, and Manufacturing Engineering leaders at OEMs and Tier suppliers. 2.7 million automotive workers retiring this decade — the FMEA knowledge leaves with them.

Existing programs

Surface risk across legacy records

Compare prior FMEAs, engineering changes, supplier evidence, and warranty data. Source-linked differences shown before reviewers decide.

New programs

Draft from approved sources

Specs, BOMs, DVP&R, process definitions, and customer requirements structured into a baseline. Your team owns ratings, controls, and release.

Methods and governance

Configured around the applicable edition and customer program. Ford, GM, Stellantis, and BMW each enforce different expectations on the same AIAG-VDA framework — Tacit AI supports OEM-specific templates and CSRs. Does not certify, approve a PPAP, or satisfy an OEM requirement by itself.

AIAG & VDA FMEA

IATF 16949

APQP / CP / PPAP

Ford CSR

GM CSR

Stellantis CSR

BMW CSR

SAE J1739

ISO 26262

Controlled engagement

Prove value on one decision before expanding.

The customer defines the baseline, source set, reviewers, output template, and acceptance criteria before work begins.

Scope

Set the boundary

Customer-defined

Select one subsystem or process, identify authoritative documents and data rights, record OEM requirements, and name engineering and quality approvers.

GateSources, owners, exclusions, and baseline approved

Validate

Review traceable output

One bounded use case

Prepare a draft and coverage review. Measure reviewer effort, source traceability, accepted versus rejected proposals, and material gaps found against the agreed baseline.

GateNamed reviewers confirm usefulness and control

Expand

Integrate approved workflows

Only after validation

Agree system-of-record handoff, permissions, change control, and program-specific reuse rules before adding products, suppliers, plants, or integrations.

GateBusiness owner authorizes the next scope

Review one subsystem

Bring the governing requirement, one approved FMEA, and the source evidence you want traced.

Questions

Automotive governance questions, answered.

Can Tacit AI update an approved FMEA?

Tacit AI proposes source-linked changes in a controlled queue. Named engineering and quality owners approve or reject each change under the customer’s document-control process before an approved record is revised.

What does “review-ready” mean?

It is not a universal quality threshold. For a pilot, the customer defines required fields, source coverage, format, exclusions, and reviewer checks. The output remains a draft until authorized personnel approve it.

Does Tacit AI satisfy OEM or PPAP requirements?

No software can confer customer acceptance. Tacit AI can structure evidence and templates around the applicable OEM requirement, while the supplier and customer retain responsibility for content, approval, submission, and acceptance.

How does it integrate with our systems?

The pilot starts with controlled import and export. Any PLM, QMS, FMEA-tool, ERP, or CMMS integration is scoped against available interfaces, data ownership, validation needs, and system-of-record controls.

Is program and supplier data isolated?

Access, tenancy, retention, permitted reuse, and deployment boundaries are agreed before ingestion. Evidence is not reused across customers, suppliers, or programs unless the data owner explicitly authorizes it.

How does it support customer-specific Reverse FMEA requirements?

Tacit AI structures shop-floor findings, links them to potentially affected PFMEA and control-plan content, and records reviewer disposition. Comparable equipment can be screened with configuration and applicability differences visible. Your team remains responsible for the applicable OEM CSR, audit evidence, ratings, controls, and document approval. Review the R-FMEA workflow and OEM sources.

What effort does a pilot require?

Provide one bounded subsystem or process, its approved source pack, the target template, and named engineering and quality reviewers. Effort and timing are estimated after source condition, permissions, and acceptance criteria are understood.