Production-grade AI for predictive maintenance, computer-vision quality inspection, schedule optimization, and generative copilots for engineering and shop-floor teams. Built by a team that understands OEE, MTBF, and takt time — not just tensors and tokens.
We don't pilot AI for its own sake. Each of these is an engagement we ship end-to-end: model, data pipeline, deployment, monitoring, and the operational runbook.
Failure prediction on rotating equipment, hydraulics, presses, CNCs, and heavy-industrial assets. Tuned against real failure history — not simulated data.
Defect detection for surface, dimensional, and assembly faults at line speed. Deployed at the edge with cloud-side retraining loops.
Multi-objective scheduling across machines, orders, tooling, and labor. Heijunka-aware leveling with changeover minimization.
LLM-powered assistants for shift handoff, SOP lookup, engineering drawings, root-cause analysis, and maintenance troubleshooting.
Asset and process twins for layout planning, capacity analysis, and scenario testing — before the first bolt is turned.
Agentic workflows that move work orders, reconcile inventory, handle supplier exceptions, and close the loop with ERP — under human oversight.
Two-week assessment: historian inventory, failure history, quality records, ERP data, and business-case ranking against real KPIs.
Train against real failure/defect history. Build the data pipeline production-grade from day one — no Jupyter-notebook handoffs.
Wire into CMMS, MES, ERP, and dashboards. Validate against shadow-mode predictions before going live.
Monitor drift. Retrain on a cadence. Weekly review of model performance against operational KPIs. No fire-and-forget.
Most AI-for-manufacturing projects die in pilot because they're built by teams who've never stood on a plant floor at 2am. We've spent 20+ years there. When we ship a model, it runs a full shift — and the next one.
Let's talk about your next operational excellence or AI-for-Manufacturing engagement. No pitch decks — just a conversation about what you're trying to move.