Detect defects and prevent downtime with AI vision and IoT
Computer‑vision and predictive‑maintenance agents that spot issues early, reduce waste and cut costs.
Who it’s for
Plant managers, operations leaders and QA teams aiming to reduce defects, avoid downtime and optimize maintenance.
What it looks like in the field
- Downtime reduced; maintenance costs lowered; visual inspection improves defect detection vs. manual methods.
- Predictive maintenance extends asset life and improves scheduling.
Capabilities
- Real‑time visual inspection
- Anomaly detection on sensor data
- Maintenance scheduling & parts recommendations
- Operator dashboards & alerts
How it works
- Instrument equipment (sensors, cameras)
- Train detection models
- Monitor & alert
- Analyze & optimize processes
Common integrations
MES, SCADA, PLCs, CMMS, ERP.
KPIs
OEE, downtime hours, defect rate, cost of quality, MTBF.
Security & compliance
On‑prem within your plant; integrates with OT security controls.
Rollout (6–10 weeks)
Pilot one line; integrate sensors/cameras; tune models; expand.
Recommended Utlyze tier & pricing
Autonomy Suite
Setup: — —/month
Vision + predictive maintenance at scale
FAQs
Can AI handle variability in production?
Models learn over time and can be re‑trained as processes change.
How is false‑positive rate managed?
Thresholds are adjustable; human review incorporated for edge cases.
On‑prem deployment with OT alignment. Results vary by line and data quality.