AI for manufacturing: quality inspection, safety, maintenance
In manufacturing, defects, injuries and downtime cost more than any software. We build computer vision and forecasting models that run on your cameras and machine data, on site if needed.
Typical tasks
- 01Visual quality inspection
A camera on the line checks every item for cracks, chips, wrong labels and missing parts. Defects are rejected or flagged for the operator. The model is trained on photos of your own defects.
- 02Safety monitoring on cameras
The system spots workers without helmets, vests or goggles, people in danger zones and skipped procedure steps. The supervisor gets an alert right away, not after an incident.
- 03Access control and timesheets
Entry is recorded by badge or by face, and hours flow into the timesheet. Biometrics are used only with written consent, and a non-biometric option is always offered.
- 04Predictive maintenance
The model analyses vibration, temperature, current and equipment logs. It warns when a unit behaves unusually. Maintenance is planned before a breakdown.
- 05Knowledge base for engineers
An assistant answers from manuals, equipment datasheets and repair logs. A new engineer finds the answer in the documents instead of hunting for a senior colleague.
- 06Reporting and ERP integration
Data on defects, downtime and hours flows into SAP, Odoo or your ERP. Managers see it in the reports they already use.
Data and access requirements
- Employee biometrics are special category data under GDPR: written consent, a non-biometric option and storage inside your perimeter. The EU AI Act bans emotion recognition at work, and we do not use it.
- Machinery and occupational safety rules: the system supports supervision but does not replace responsible staff or training.
- Plant networks are often isolated: video is processed on a local server with no internet access.
- Integration with SAP, Odoo, MES and machine data systems through API or OPC UA.
What we build for this industry
Questions
How many defect photos are needed?
It depends on the defect and how stable the product is. During discovery we collect samples from the line and assess whether they are enough. If defects are rare, we label more with your engineers and add samples during the pilot.
Does it work without internet?
Yes. For plants with closed networks we run processing on a local server. Video never leaves the site, and only aggregated data goes out if you want it to.
What if the AI misses a defect?
AI sometimes gets it wrong, especially on new defect types. So at the start the system runs alongside human inspection and we compare results. Thresholds and review steps are set with your quality team.
What does it cost and how long does it take?
From $5,000 for a turnkey project. Discovery takes 1-2 weeks, the estimate 2-3 days and the build 4-8 weeks with weekly demos. The pilot usually covers one line or area.
Describe the task. The first call is with the founder.
We reply within one business day. 30 minutes to tell you whether it is worth doing and what it costs.