Industrial Quality Inspection Solution
Tencent Manufacturing × ADP - Self-Evolving, Stable Visual Inspection
Built for industrial quality inspection, the solution turns defect inspection, annotation, training, and evaluation into reusable AI Skills, enabling users to perform data validation, bad case analysis, and root cause reporting through natural language.
Training Models Is Easy. Scaling Them Is the Challenge.
- Manufacturing Know-How
- AI Expertise
- Reusable Business Skills
- Scalable Solutions
- Complex Configuration
- Limited AI Resources
- Experience-Driven Decisions
- Inconsistent Annotation
- Repeated Data Validation
- Cross-Team Coordination
- Complex Root Causes
- Incomplete Production Data
- Difficult Corrective Actions
Key Advantages
Turn expert inspection workflows into guided steps for frontline operators.
Capture Both Manufacturing and AI Expertise
Capture manufacturing know-how from defect definitions, process constraints, and imaging expertise, together with AI knowledge such as annotation rules, model selection, and tuning strategies as reusable business Skills.
Unify Every Role in One Workflow
Bring annotation, data validation, bad case analysis, engineering collaboration, and project tracking into a single AI-powered workflow, enabling one operator to drive projects forward efficiently.
Root Cause Analysis Without Waiting for Experts
With Claw Mode, AI interactively collects production insights across manufacturing, imaging, data, and AI, generating root cause reports and improvement recommendations in real time.
Customer Stories
Built on ADP, improving workforce productivity, report automation, changeover efficiency, and inspection consistency.
- Built reusable quality inspection Skills for small defect detection—including scratches, stains, and edge chipping—by combining manufacturing expertise with AI model training.
- AI agents provide annotation guidance, training data validation, and bad case analysis, reducing back-and-forth across teams.
- Claw Mode gathers imaging, fixture, and defect-standard details through interactive dialogue, automatically generating root cause analysis reports.
- Built specialized Skills for tab counting, overlap detection, imaging optimization, and anomaly verification using Tencent Cloud ADP.
- Operators use natural language to validate samples, analyze counting errors, and enrich training data.
- Claw Mode automatically generates root cause reports to pinpoint mechanical, imaging, or AI model issues behind counting anomalies.
- Built specialized quality inspection Skills for bottle types, labels, fill levels, caps, and printed codes with Tencent Cloud ADP.
- When new SKUs are introduced, AI agents automatically reuse similar inspection workflows, reducing manual reconfiguration.
- Missed and false detections are automatically classified to generate recommendations for reshooting, reinspection, and store improvements.
- Built specialized Skills for imaging standards, image quality inspection, region annotation, and follicle counting with Tencent Cloud ADP.
- AI agents automatically inspect image quality, recommend retakes, and assist with annotation and data management.
- Claw Mode uses interactive dialogue to capture pre- and post-procedure image differences, generating readable quality inspection reports.
- Built specialized Skills for camera module inspection by capturing annotation standards for micro defects and imaging expertise under different lighting conditions.
- AI agents automatically validate training data, identifying missing labels, incorrect annotations, and data distribution issues.
- Claw Mode generates root cause reports that distinguish between lens contamination, lighting variations, and AI model misclassification.
Scenario Capabilities
Turn expert decisions into guided tasks across every stage of quality inspection deployment.
Solution Design
Define inspection points, sample requirements, AI strategies, and delivery scope based on products, defects, production throughput, and acceptance criteria.
Data Preparation
Standardize defect definitions, dataset planning, data splitting, and quality validation to reduce rework throughout model development.
Model Iteration
Automate bad case feedback, sample enrichment, training optimization, and model validation, enabling routine model improvements without AI expertise.
Diagnosis, Optimization & Operations
With Claw Mode, AI interactively analyzes manufacturing, imaging, data, and model insights to generate root cause reports, optimization recommendations, and deployment checklists.
Two Delivery Modes
Use Workflows for structured, repeatable tasks, and Claw with Business Skills for expert reasoning and dynamic decision-making.
Free Quality Inspection Projects from Expert Bottlenecks
Capture manufacturing domain expertise and deep learning know-how as reusable business skills, enabling a single site manager to oversee data annotation, training data quality inspection, bad case analysis, and root cause reporting.