Manufacturing industry
Quality control of serial products, detection of assembly defects and dimensional deviations on production lines.
Models learn from your production process data without the need to involve AI specialists.
PredictCore models as an analytics module connected to your PLC, SCADA or MES — enriching the existing system with autonomous quality control without replacing the infrastructure.
We design a complete quality control system with PredictCore models at the core — from sensors and cameras, through line integration, to dashboards and reporting. One partner, full responsibility.
The result is a production system that assesses the quality of every product on its own in real time — without interrupting the process and without subjective operator evaluation.
Data from sensors, cameras and measurement systems collected in real time from inspection points on the production line.
The model learns the pattern of a correctly manufactured product based on reference samples — without an AI expert.
Each product is compared against the model. The product receives an OK or NON-CONFORMITY status along with an indication of the type and location of the defect.
Non-conformities appear on the quality dashboard and trigger automatic alerts. Quality reports generated automatically without manual data collection.
Detection of scratches, cracks, inclusions, chips and other surface defects invisible to the naked eye — with accuracy unavailable to a human inspector.
Checking for the presence and correct placement of components, connections, markings and labels on the final product or subassembly.
Verification of geometric dimensions, distances and tolerances directly from the camera image — without contact measuring instruments.
Automatic classification of products into quality categories and directing them to the appropriate storage locations or rework lines without operator involvement.
Industrial camera
Live image from the production line
PredictCore AI model
Image analysis and comparison with reference
✓ OK
Conforming product — passes through
⚠ NOK
Non-conformity — alert and segregation
Real-time assessment of product and process quality — every product assessed automatically without interrupting production.
Autonomous analysis of process data without the need for expert knowledge — the model learns quality criteria from reference samples on its own.
Ability to record and process data from any number of different sensor types — for both small-batch production and continuous industrial processes.
Full versatility — for both small-batch production and continuous industrial processes. The system grows with the plant.
Display of quality data on production dashboards and HMI panels — product statuses, trends and reports in one place.
Simple integration with MES, ERP and SCADA supervisory systems and industrial networks and devices from multiple manufacturers via the IO-Link standard.
Every product assessed automatically — objectively, repeatably and without subjective operator evaluation regardless of shift or fatigue.
Non-conformities detected in real time on the production line — immediate response before a defective product reaches the customer.
AI model training on reference samples without a data engineer — the system learns your product's quality criteria on its own.
Quality control of serial products, detection of assembly defects and dimensional deviations on production lines.
Autonomous quality control of subassemblies, gearboxes and drivetrain components in production for the automotive industry.
Monitoring of quality parameters in continuous production processes — detecting process deviations before they affect product quality.
Quality control of components and subassemblies for the energy sector with high reliability and certification requirements.
Quality control of chemical and pharmaceutical products — verification of process parameters and compliance with regulatory requirements.
Visual inspection of food products, packaging completeness control and process parameter verification in sanitary environments.
Analysis of experimental data and quality control in research and development projects requiring precise results verification.
Automatic inspection and classification of products in picking, sorting and shipping processes at distribution centers.
Every implementation starts with a needs analysis — model selection and configuration, process assessment and project pricing.