Intelligent Inspection
Smarter Vision-Based Inspection. Right at the Edge.
Industrial manufacturers are under constant pressure to improve quality while maintaining throughput.
Manual inspection struggles to keep pace and introduces human error. Traditional machine vision systems fail when products, lighting or tolerances change.
Cloud-based AI adds latency, increases costs, and introduces unacceptable data risk on the factory floor.
Consult Red enables AI-powered industrial visual inspection at the edge
Consult Red designs and deploys Edge AI enabled vision systems that automatically detect defects, anomalies and compliance issues in real time.
Models run locally on industrial-grade hardware, analysing image and sensor data directly at the point of inspection. No cloud dependency. No production delays.
Fast, reliable, privacy-safe inspection
Decisions are made in milliseconds. Sensitive production data never leaves your site.
Retrofit ready deployment
Extend the life of existing cameras and PLC systems without ripping out your line.
Scalable across plants
Repeatable AI models and deployment pipelines support multi-site rollouts with consistent quality standards.
End-to-end delivery
From model training and hardware selection to integration and long-term support
Designed for industrial reality
Our systems are trained on your real production data, tuned to your tolerances, and validated in live conditions. We integrate with existing cameras, PLCs and control systems, and deploy using hardened, long-lifecycle hardware suitable for factory environments.
Benefits of Intelligent Inspection
Detect cosmetic, dimensional and assembly defects missed by manual checks
Reduce scrap, rework and unplanned downtime through early anomaly detection
Improve audit readiness and safety compliance while keeping data on-site
Roll out standardised inspection across multiple lines and factories
RedSight: validating against the design, not just the pattern
RedSight is our Edge AI vision solution for industrial inspection. Where most vision AI flags anomalies against a learned “normal,” RedSight compares what the camera sees against the actual design specification, so it knows exactly what should be there, not just whether something looks different.
RedSight Wire, an application of the solution, uses a camera-equipped cobot to inspect wiring cabinets and verify their assembly against design specifications in real time, flagging defects without cloud dependency and with minimal operator oversight.
High-mix manufacturing (such as wiring cabinet assembly) is exactly where most vision systems fail. Too many product variants, too much retraining, not enough time between changeovers. Validating against a design specification rather than a trained baseline is what lets RedSight handle that variability, which is why the same approach extends beyond wiring cabinets to other high-mix inspection applications.
Why Choose Consult Red for Intelligent Inspection
Full-stack expertise
Hardware, software, connectivity & cloud
Industrial focus
Specialists in long lifecycle products
Independent partner
No vendor lock-in
Regulatory confidence
EMC, RF, safety, CRA ready cybersecurity
Flexible, low risk delivery
Staged process from audit to certification
The Edge AI Advantage
- Low Latency
Detect defects instantly, not after the product has moved on. - Data Security
Images and IP remain on your factory floor. - Cost Efficiency
No cloud bandwidth or ongoing operating costs (inference fees). - Scalability
Consistent inspection performance across sites.
Frequently Asked Questions
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What is automated visual inspection in manufacturing?
Automated visual inspection uses cameras and AI models to check products for defects, deviations or compliance issues as they move through production. Unlike manual checks, it operates continuously at line speed, improving consistency while reducing scrap, rework and inspection labour.
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How does Edge AI inspection differ from traditional machine vision?
Traditional machine vision relies on fixed rules and thresholds, which break down when products, lighting or tolerances change.
Edge AI inspection uses trained models that adapt to real-world variation, identifying subtle or previously unseen defects. Running these models at the edge also removes latency and avoids reliance on cloud connectivity. -
What is an on-premise AI inspection system?
An on-premise AI inspection system processes images and sensor data locally on industrial hardware within your factory. All analysis happens on-site, giving predictable performance, full control over data, and easier compliance with security, IP and regulatory requirements.
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How accurate is AI-based industrial defect detection?
Accuracy depends on data quality, training and validation, not just the algorithm. Industrial defect detection AI is trained on real production data and tuned to your specific tolerances. This allows it to reliably detect cosmetic, dimensional and assembly defects that are difficult to capture with rules-based systems or manual inspection.
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Can AI inspection work with existing cameras and production lines?
Yes. Most Edge AI inspection systems can be retrofitted to existing cameras, PLCs and control systems. This allows manufacturers to improve inspection capability without replacing production equipment or disrupting established processes.
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Is AI inspection suitable for regulated manufacturing environments?
When deployed on-premise and engineered correctly, AI inspection systems are well suited to regulated environments. Local processing supports data sovereignty, while validated models and controlled deployment help meet quality, safety and cybersecurity requirements.
Start with an intelligent inspection feasibility assessment
We’ll review your inspection challenges, data availability and production constraints, then outline a practical Edge AI approach with clear costs, risks and timelines.
Related Insights
Webinars
On-Demand Webinar: Edge AI, Real Results: How We Built a Visual Anomaly Detection Solution
We lift the lid on the development of a production defect detection system that combines object and anomaly detection
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News
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