ClearQuality
Vision AI for Smart, Efficient Manufacturing
Automate and augment manufacturing operations with Vision AI. Vision AI captures and analyzes image data from the production floor to increase automation, drive continuous improvement, and empower better decision-making.
Why Vision AI for Manufacturing?
Compared to manual inspection, Vision AI detects issues faster and more reliably, while continuously capturing data that supports quality improvement, process optimization, and safer, more productive operations.
Vision AI for Quality ControlUnderstanding the stack
From lens to dashboard, one partner.
Physical AI
Engineered and procured with ClearObject
Lighting & Optics
Lighting and lens selection engineered for a consistent, repeatable image
Cameras & Positioning
Industrial cameras, mounting and enclosures designed to your line geometry
Hardware Procurement
We spec it, you own it. No proprietary ClearObject hardware
Edge Compute
Ruggedized GPU appliance sized to run at full line speed
Software Intelligence
Built and managed by ClearObject
Inference Engine
ClearVision models detect defects in real time at the edge
Line Integration
Verdicts to your PLC and reject gate over OPC UA
ClearVision Hub
Dashboards, cross-line insight and audit-ready quality records
Operationalization
Value comes from Physical AI and software intelligence working together.
Top-to-bottom support
We support every layer, from hardware to software, to keep your model running.
Mutual success
Our agreements are structured around shared outcomes and a model that returns.
Performance envelope
Every unit inspected, at line speed.
- Inference time
- < 100 ms
- Throughput
- 10–20 fps
- Reject signal
- < 30 ms
- Edge to Hub
- < 500 ms
- Units inspected
- 100%
- To Line 1 go-live
- 5 months
Typical envelopes, not fixed specifications. Maximum bounds are agreed at implementation onset and validated on your own imagery before production.
Inspection modules
Eight modules, one edge platform
Every module publishes into the same PLC signal set and ClearVision Hub, and modules can be combined on a single line.
- 01
Defect Detection
Segmentation and classification on every frame: where the defect sits, how large it is and what kind it is. Scratches, dents, cracks, voids, seal and fill faults, surface contamination.
- 02
Code Date & Label
Confirms every printed code and label is present, readable and where it belongs before product leaves the line, with an optional OCR read.
- 03
Operator Quality Control
Your best operators’ accept and reject calls become training labels, so criteria that resist written rules are applied to every unit, every shift.
- 04
Dimensional Analysis
In-line length, width, diameter, gap, position, fill height and count from a calibrated camera, checked against tolerance bands you configure.
- 05
Anomaly & Foreign Material
Trained on good product only. Foreign objects, debris, unseen defect types and process drift are flagged with no library of defect examples.
- 06
SOP & Human Behavior
Verifies people follow the procedure: the right steps, in the right order, with the right PPE. Step compliance per cycle, with an event clip and alert.
- 07
Sensor Fusion: Vision + LiDAR
For harder use cases. Vision’s semantics plus LiDAR’s geometry catch volume, shape, depth and low-contrast faults either sensor alone would miss.
- 08
Custom Complex Module
Multi-stage pipelines for problems beyond a single model: multi-camera fusion, sequenced checks, assembly completeness and kit verification.
Process monitoring
Catch a clogged nozzle before it costs a batch
Spray nozzles that apply glue or binder drift and clog, and the first sign is usually bad product. ClearVision measures the angle of every spray fan as it runs and alerts the line when a nozzle falls out of range.
- Measures both edges of every nozzle’s spray fan, continuously
- Flags a narrowing or lopsided spray as soon as it drifts out of tolerance
- Alerts operators at the line, so the nozzle is cleaned before a batch is ruined
Vision AI Use Cases for Manufacturing
Vision AI from ClearObject turns video streams into actionable data to make manufacturing more efficient, safer, and more profitable.
Quality Control
Real-time quality control across continuous or batch production with Vision AI - If you can see it, we can see it better, faster, and more consistently.
Operations Efficiency
Vision and sensor data help AI understand material waste, work interruptions, downtime, and more to help predict and improve workflows.

Worker Safety
Enhance worker safety by ensuring proper PPE, alerting workers in danger zones, and monitoring dangerous equipment.

Assembly Verification
Track small batch assembly operations to ensure products are complete and accurate according to specifications.
Waste Reduction
Catch errors early and identify the root cause to increase efficiency and reduce waste.
Inventory Tracking
Automate inventory visibility using Vision AI to track materials, parts, and finished goods in real time.
How we get there
A repeatable path from first use case to scaled deployment.
Value-focused discovery · 1–2
Opportunity assessment
Frictionless data integration · 3–4
Integration analysis
Rapid solution delivery · 5–7
Minimum viable product
Scalable managed solution · 8–10
Cloud deploy for product
Outcome
Scalable managed vision system
- 1Identify opportunities
- 2Define business use case
- 3Install hardware
- 4Data pipeline and features
- 5Build the vision model
- 6Evaluate
- 7Product onboarding
- 8Plan and scale deployment
- 9Operationalize model to PLC
- 10Monitor
Three-phase timeline
Five months to Line 1 go-live
Capture happens on-site in the first phase, and ClearObject does the annotation and training: no data science team is needed on your side. Lines 2 and beyond compress by roughly 70%, because models, network topology, PLC templates and OPC UA maps carry directly across.
- Design & procurement (2 months): line survey, footage capture, hardware BOM, model training and an accuracy assessment on your own defects
- Installation (1 month): cameras, lighting and edge provisioning, with the PLC in monitoring-only mode
- Training & calibration (2 months): tuning on live variation, threshold recommendations and operator training; the closed loop activates on your written sign-off
Case Study
Knauf Improves Quality and Safety
ClearObject provided Knauf with a highly available and reliable Vision AI system with real-time deep learning prediction capabilities, allowing users to monitor and be alerted if manufacturing lines deviate from standards.
Since launching, Knauf has seen immediate and dramatic impacts for both the bottom line and towards reaching their ESG (environmental, social and governance) goals. Knauf is realizing millions in savings.
Read the Full Case Study- ROI in year one for Knauf Insulation
- 511%
Vision AI for Manufacturing Benefits
- 01
Quality
Vision AI deployed at the edge provides real-time analysis to identify defects and eliminate false-positives, improving both quality and efficiency.
- 02
Efficiency
ClearVision reduces downtime and increases throughput with insights into operations. Lines run faster, longer, and with higher accuracy than those monitored by human eyes.
- 03
Profits
Reduce waste, cut labor costs, increase throughput, and minimize downtime so QA professionals can focus on solving quality concerns, not on monitoring the lines.
- 04
Safety
ClearVision Inference Engine will identify PPE violations, monitor hazardous work areas, and reduce emergency shutdowns to increase worker safety and keep operations running.
- 05
Connected
ClearVision integrates seamlessly into your existing systems, and can often use images from existing cameras.
Artifacts
Take ClearQuality with you
- 01
ClearQuality product specification (PDF)
The full stack, all eight inspection modules, platform capabilities, PLC output signals, the performance envelope and the three-phase timeline.
- 02
Vision AI for Quality Control
Why automated inspection catches what manual checks miss.
- 03
Knauf case study
511% ROI in year one with ClearVision at the edge.
Can’t Wait? Contact Us Today
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