Sector — Manufacturing
AI for Manufacturing.
Predictive maintenance for production equipment, vision based quality inspection, agentic scheduling for OEE optimisation. Production grade, not demo grade.
Australian manufacturing sits in the gap between an enormous AI opportunity (35.3% CAGR sector) and a track record of pilots that stall. We exist to close that gap.
Most manufacturers we meet have run two or three AI pilots. Few have one in production. The reason is rarely the model. The reason is the gap from prototype to a system the operations team can run on day shift, swing shift, and night shift without an AI specialist on call.
AI in manufacturing lands first where the constraint is most felt: equipment downtime, line-speed quality inspection, and OEE drift. The specific, the measurable, the operator-actionable.
Where AI lands first.
Three to four AI opportunities specific to Manufacturing operations. We start with the one most ready for production.
Predictive maintenance
Production equipment downtime
Anomaly detection on PLC and SCADA telemetry. Targets 25 to 40% downtime reduction on the equipment most exposed to wear. Adapter library for common stacks.
Vision QC
Line-side quality inspection
Computer vision on existing line cameras. Defect detection, label verification, packaging integrity. Runs at line speed; escalates marginal cases.
Scheduling
OEE optimiser
Agentic scheduling and constraint analysis. Surfaces the operator-actionable changes, not the executive dashboard.
Document intelligence
Compliance and quality records
Automated reading of incoming material certs, audit reports, and quality records. Trend detection across batches.
Why us, for Manufacturing.
We build production grade systems. XP discipline, full test coverage, deployment your operations team can run, observability that surfaces the right alerts, not all alerts.
And we ship in weeks. Six to eight weeks to a working agent in production is the norm, not the exception. The first measurable outcome lands inside the first 90 days.