Industry
Manufacturing
Production scheduling, supplier intelligence, and quality-control workflows that sit on top of MES and ERP, never replacing them.
What the work usually looks like.
A multi-plant manufacturer running on SAP S/4 or Oracle E-Business with a tangle of MES, EAM, and quality systems. Production planning is half ERP, half spreadsheet. Quality issues take days to root-cause because the data lives in five places.
Where we tend to find the constraint.
- Plant managers spending hours per week reconciling ERP and MES numbers by hand
- Engineering changes that take weeks to propagate from CAD into the production system
- Quality teams firefighting in spreadsheets long after a defect has shipped
~30%
of plant-management hours we typically see lost to manual reconciliation between MES and ERP before any AI work begins.
What we typically build for operations like yours.
Supplier scoring and on-time-delivery prediction
Quality root-cause assistant: plausible causes from historical defect, line and lot data
Production plan adjustments under demand or supply shock
Maintenance scheduling against historical failure data
Compliance and audit-trail summarization for ISO / FDA / IATF cycles
Where the human gate goes, specifically for this industry.
In manufacturing, the cost of a wrong autonomous decision is measured in scrapped lots, recalled product, or shut lines. Every consequential action (pulling a lot, adjusting a recipe, flagging a supplier) routes through the operator or quality engineer responsible for it.
Sample approval surface
Pull lot #LR-2204 from line 3, suspected supplier defect
Flagged- Defect rate 4.2x baseline this shift
- Supplier on watch since prior incident
Quality engineer
Talk to us
Have an operation in this shape?
We'll start with a 2-week Discovery against your real systems. If we're not a fit we'll say so on the call and point you somewhere useful.