AUTOMOTIVE
Engineering decision cockpit for a global Tier-1 automotive supplier
Engineers spend their time gathering data from PLM, ERP and supplier portals instead of engineering. Wexa designed a cockpit with three governed agents for change impact, product carbon footprint and parts reuse, on one context graph.
- annual value, one pilot division, year 1 (estimate)
- days per engineering change (target)
- per product carbon footprint vs 2–6 weeks (target)
- new part numbers (target)
- CLIENT
- Global Tier-1 automotive supplier
- REGION
- Europe
- WHEN
- 2026
- ENGAGEMENT
- Solution design
- WEXA COMPONENTS
- Wexa · PLM, ERP and supply-network connectors · 3 governed agents · approvals · audit
01Case 39
The challenge
- Engineering changes consume a third to a half of engineering capacity
- Product carbon footprints take weeks and are now required by customers
- Duplicate parts across PLM systems and ERP
What Wexa built
- Change-impact agent: traces assemblies, plants, stock and orders; checks engineering vs manufacturing BOM; prices the change; drafts the change-board brief
- Carbon-footprint agent: maps the BOM to emission factors per the industry rulebook; hotspots and lower-CO₂ options; sign-off by the footprint lead
- Parts-reuse agent: finds look-alikes across PLM and ERP and ranks duplicates by spend and stock
- Starts read-only; approval and audit on every write; EU cloud or on-premise; 12-month gated programme
02Case 39
How it runs on Wexa
03Case 39
Results
| Measure | Before / without Wexa | With Wexa |
|---|---|---|
Engineering cost of change impact, footprints and parts search (one division) | $9M a year | $4.5M a year |
Annual cost of the process | $9M | $4.5M |
Days per engineering change | 17 | 9–10 |
Time to implement the AI solution | 9 months | 16 weeks |
AI build cost (one-time) | $1.2M | $177K |
AI operating cost per year (models, infrastructure, upkeep, platform) | $704K | $336K |
Total AI cost in year 1 | $1.9M | $513K |
With Wexa
net annual value to the client after Wexa's own operating cost
faster to implement
lower AI operating cost
less AI spend in year 1
Value figures are planning estimates from industry benchmarks, to be re-baselined in a four-week discovery phase.
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