Vision quality control
Defect detection, measurement verification, and inline rejection with human review queues.
Industry · Manufacturing
AI for the plant floor
We build AI for manufacturers and job shops — computer vision quality inspection, predictive maintenance scheduling, supply-chain document processing, and operator copilots that reduce downtime and scrap without massive ML teams.
98%+QC accuracy
−47 minDowntime/shift
70%Less manual OCR
6–8 wkPilot typical
Industry context
AI on the production line
Manufacturing AI must work with noisy environments, legacy MES/ERP systems, and tight tolerances. We deploy vision models at the edge, maintenance predictors on sensor data, and document pipelines for BOLs, POs, and quality records.
Predictive maintenance
Sensor and usage signals to schedule service before unplanned downtime.
Document automation
BOLs, invoices, COAs, and customs docs — extract, validate, sync to ERP.
Operator copilots
Voice and chat assistants for work instructions, safety checklists, and exception reporting.
Use cases
Where manufacturing AI delivers
Use cases for discrete manufacturing, process plants, and supply-chain ops.
Quality Inspection
Computer vision for surface defects, assembly verification, and dimensional checks at line speed.
- Edge deploy
- HITL review
- MES integration
Predictive Maintenance
Vibration, temperature, and runtime models to predict failures and optimize work orders.
- Sensor ingest
- CMMS sync
- Downtime KPIs
Supply-Chain Documents
Automated processing of BOLs, POs, packing lists, and COAs with validation against ERP.
- OCR + rules
- Exception queues
- SAP/Oracle sync
Process Anomaly Detection
Multivariate monitoring on batch and line data with alert routing to supervisors.
- Real-time streams
- Root-cause hints
- Dashboards
Operator Copilots
Hands-free work instructions, safety procedures, and downtime reporting from the floor.
- Voice option
- Offline mode
- Audit logs
Production Planning Assist
Demand-supply alignment, bottleneck forecasting, and schedule recommendations.
- ERP data
- What-if sim
- Planner review
Proof of work
Manufacturing delivery
Vision and document automation with measurable quality and uptime impact.
Vision Inspection Pipeline
Multi-modal vision + NLP pipeline for damage and defect assessment — architecture proven at production scale.
68%Faster processing
$1.1MAnnual savings
Document Extraction
High-volume OCR and entity normalization applicable to supply-chain and quality records.
82%Faster processing
$1MAnnual savings
Real-Time Scoring
Sub-100ms anomaly scoring architecture transferable to line monitoring and sensor alerts.
47msLatency
68%Detection lift
How we help
Related services
Production AI capabilities we bring to every industry engagement.
01Can vision AI run on the plant floor without cloud?
Yes — edge deployment on industrial cameras and gateways with optional cloud training and model updates.
02Which ERP and MES systems do you integrate with?
SAP, Oracle, Microsoft Dynamics, Plex, and custom MES via API, OPC-UA, and file drops.
03How accurate is automated quality inspection?
Typical 95–99% detection on defined defect classes after calibration — with human review queues for borderline cases.
04What's the ROI timeline?
Document automation: 3–4 months. Vision QC: 6–9 months including calibration. Maintenance AI: 4–6 months on critical assets.
Next step
Ready to optimize your plant?
Tell us about your lines and systems — we'll design vision QC, maintenance AI, and document automation with clear KPIs.