Services
Predictive AI & computer vision
Apply forecasting, anomaly detection and computer vision to planning, quality and operational decisions.
Manufacturing intelligence
Connect quality, traceability and the production floor.
Bring production signals, engineering changes and material records into decisions that improve plant operations.
The connected workflow
- 01Source information
- 02Validate and connect
- 03Review exceptions
- 04Approved action
A connected approach
Bring production signals, engineering changes and material records into decisions that improve plant operations. We start with the actual operating process and connect the records, validation and people required to move the work forward. AI is used where it helps interpret information; business rules remain explicit.
Visual quality inspection programme
Manufacturing quality head: defects are discovered too late.
Capture representative images, evaluate model performance by defect class, connect quality records; quality staff control disposition.
Pilot measures: Missed defects, false rejects, performance under lighting changes and inspection throughput.
Batch genealogy and containment workspace
Manufacturing head: a suspect component cannot be traced to finished goods.
Link receipts, lots, assemblies and shipments; extract legacy references; quality staff confirm containment/release decisions.
Pilot measures: Trace completeness, affected-stock identification time and incorrect associations.
Engineering change-control platform
Engineering head: design revisions do not reach procurement and production.
Join document versions, BOMs and purchase orders; summarise changes; authorised engineers approve releases.
Pilot measures: Obsolete-version use, missed affected orders and change-review time.
Reliability and maintenance intelligence
Plant/asset manager: faults recur despite closed maintenance tickets.
Combine telemetry, asset IDs, parts and work orders; forecast anomalies and retrieve previous fixes; engineers diagnose and authorise action.
Pilot measures: Repeat failures, false alarms, planned vs unplanned work and prediction lead time.
Start with a bounded pilot
Choose a business unit and a representative set of records. Measure today’s cycle time, errors and manual review. Validate unusual inputs, failed integrations and permission boundaries before expanding. Targets are agreed from that baseline rather than assumed from a generic savings percentage.
Common questions
What does this solution connect?
Bring production signals, engineering changes and material records into decisions that improve plant operations.
Will AI make the final decision?
The workflow defines which steps can run automatically and which need an authorised person. Financial approvals, clinical judgments and other consequential decisions remain under appropriate professional control.
How is business value measured?
Agree a baseline for the selected workflow, then compare quality, completion time, exceptions and operating cost during the pilot. Wider rollout follows demonstrated acceptance.