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.

Multiple/day
FMEA drafts versus one per week before Tacit AI
83%
work-order data-quality improvement under the customer method
26%
non-value-adding preventive maintenance removed after review

Where Tacit AI supports the decision

Move from fragmented evidence to review-ready FMEA faster.

Establish the risk baseline

Prepare candidate functions, failure modes, effects, causes, controls, and ratings from approved specifications, BOMs, drawings, process flows, and prior FMEAs. Each proposal retains its source and is held for qualified engineering review.

Design FMEA details

Trace design risk into process controls

Compare approved DFMEA characteristics with process flow, PFMEA, control-plan, and verification evidence. Tacit AI proposes links and exposes breaks; program owners decide the required classification, control, and PPAP content.

Process FMEA details

Bring field and supplier evidence into review

Relate warranty, 8D, test, return, and supplier records to affected FMEA content. Similarity is presented as evidence for review, with program, component, market, and configuration differences preserved.

Control every handoff

Route proposed row-level revisions through named reviewers, retain source citations and decision history, then export approved content to the customer’s quality or FMEA system. Tacit AI does not approve safety characteristics or customer submissions.

“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

Economic and technical owners

For leaders accountable for launch risk, engineering capacity, and customer acceptance.

Built for VP Engineering, Quality, Manufacturing, APQP, and Supplier Quality leaders at OEMs and Tier suppliers who need better evidence flow without bypassing design authority or customer-specific requirements.

Existing programs

Find risk hidden across disconnected records

Compare legacy FMEAs, engineering changes, supplier submissions, warranty evidence, and current controls. Reviewers see source-linked differences before deciding what should change.

New programs

Start reviews from a traceable draft

Use approved specifications, BOMs, DVP&R inputs, process definitions, and customer requirements to prepare a structured baseline. Your cross-functional team owns ratings, characteristics, controls, and release.

Methods and governance

Workflows can be configured around the applicable edition and customer program. Support for evidence preparation does not certify an organization, approve a PPAP, or satisfy an OEM requirement by itself.

AIAG & VDA FMEA Handbook
IATF 16949 context
AIAG APQP / Control Plan / PPAP
OEM customer-specific requirements
SAE J1739 where selected
ISO 26262 where applicable

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.

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.

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.

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.

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.

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.

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.

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