Predictive maintenance
A remaining-life estimate for each asset, so the fix lands in a planned window instead of an unplanned stoppage.
All solutionsManufactINS
Manufacturing intelligence
The intelligent operating system for manufacturing
A vertical AI operating system that connects the ERP, MES, historian, quality and maintenance systems you already run, and predicts machine failure, quality loss and OEE drops before the shift feels it — each with the governed action to take.
Capabilities
Quality prediction and traceability
SPC and inline vision catch drift at the source rather than at the end of the line, with lot and serial traceability behind every finding.
Demand and production planning
AI demand forecasting and a production plan sequenced against real capacity, changeovers and the material on hand, with procurement weighed against supplier risk.
Real-time OEE, from shop floor to boardroom
Production against plan, equipment effectiveness and machine health in one live command center, with critical assets flagged.
How it works
- 1Connect MES, historian, quality and maintenance systems
- 2Failure, quality and OEE risk surface continuously
- 3Each recommendation shows its evidence and owner
- 4Reversible steps run; the rest wait for a named approver
Best for
Predictive maintenance on a critical linePlant & maintenance managers · Explore use caseInline quality drift detectionQuality managers & process engineers · Explore use caseProduction scheduling against real capacityProduction planners · Explore use case
Without it
Plant data stays scattered across ERP, MES, SCADA, maintenance and the shop floor, so late orders, unplanned downtime, quality drift and margin loss surface only after they have already hurt.
See what InsAI would look like inside your operation.
Start with the question you are asking today, or talk to the team about a scoped pilot on your own data. No generic AI presentation — start with the business problem.
Customer evidence
The engagements this product came out of, each with the document and page its figures were published in.
All ten case studies