Where AI earns its keep

Real outcomes. Not demos.

Every engagement starts with a specific operational outcome — fewer unplanned stops, faster operator response, less variance in a recipe. No "let's just try AI." The engineering team picks the model, defines the success metric, and ships.

Use cases

Use case 01

Predictive maintenance
Combine LANAWARE asset telemetry with historian data to forecast bearing wear, motor degradation, lubrication intervals.

Use case 02

Anomaly detection
Detect off-baseline traffic, off-hours OPC-UA activity, recipe deviations, alarm storms — before they cascade.

Use case 03

Operator guidance
In-cab / in-control-room AI assistants that surface the right procedure, alarm context, or vendor documentation — at the moment of the alarm.

Use case 04

Production optimisation
Recipe parameter tuning across historical batches, energy-aware scheduling, throughput optimisation under quality constraints.

Use case 05

Audit / compliance drafting
Generate first-draft NERC-CIP / IEC 62443 evidence packages from raw telemetry. Engineers approve; AI does the typing.

Use case 06

Knowledge capture
Codify retiring-engineer knowledge into searchable, AI-queryable runbooks tied to your specific environment.

Pilot one outcome. Then scale.

Most engagements start with a 30-day pilot scoped to a single specific operational outcome.