We have discontinued our cloud-based data annotation platform since Oct 31st. Contact us for private deployment options.
Data Annotation for Manufacturing Industry
Scalable, Precise and Optimized Training Data for Manufacturing and Industrial Automation AI
Process Optimization
Optimizing manufacturing and industrial processes through AI and computer vision leads to reduced costs and accelerated efficiency. By tirelessly analyzing data with precision, AI systems boost productivity, cut waste, and improve the speed and reliability of operations. The key to enabling this transformation is annotated training data.
Inventory Management
Computer vision algorithms employ techniques like object detection and instance segmentation to accurately track inventory levels in warehouses and detect shortages in real-time. High-quality annotated training datasets with bounding boxes, segmentation maps, and object counts for all products enable models to recognize various items and quantities with precision. This allows organizations to optimize inventory and reduce waste.
Bounding Box Annotation
2D/3D Cuboid Annotation
Semantic Segmentation
Object Tracking Annotation
Industrial Robot
Industrial robots can optimize repetitive manufacturing tasks and workflows through computer vision and deep reinforcement learning. Annotated datasets with grasping points, trajectory waypoints, manipulation demos, and task simulations for sample industrial tasks allow robots to quickly and safely learn complex skills with minimal explicit programming.
Key Point Annotation
2D/3D Cuboid Annotation
Semantic Segmentation
Object Tracking Annotation
Supply Chain Management
AI enhances supply chain resilience by adapting to real-time changes and predicting disruptions. Annotated images and videos providing visual context of supply chain operations help train AI models to understand the flow of goods. Object detection and tracking annotations on footage of warehouses and transportation routes enable models to monitor operations and identify inefficiencies. This improves logistics agility.
Poly-line Annotation
Polygon Annotation
Semantic Segmentation
Object Tracking Annotation
Productivity Monitoring
Computer vision powered video analytics and workflow monitoring systems can track production processes, detect bottlenecks, and identify process inefficiencies. Annotated videos of ideal workflows and step-by-step operations train models on proper process execution. Multi-object tracking, fine-grained action recognition, scene classification, and detailed environment annotations then enable precise productivity analytics and optimization.
Bounding Box Annotation
Scene Classification
Skeleton Annotation
Object Tracking Annotation
Personalized Product Customization
AI can enable product customization to individual customer specifications by leveraging annotated product configuration data. Bounding box and segmentation annotations on product images and videos can train models to recognize customizable features. Audio and text transcription of customer requirements provides further personalization signals. This increases the value of finished customized products.
Bounding Box Annotation
Key Point Annotation
Semantic Segmentation
Skeleton Annotation
Site Safety and Compliance Monitoring
AI assisted systems can aid in overseeing safe practices, hazard identification, and regulatory compliance adherence. Annotated videos and images of proper safety procedures train models to proactively identify risks and violations. Tight bounding boxes identifying PPE, precise scene and environment labels, granular action recognition, and natural language SOPs enable automated audits and compliance oversight at scale.
Polygon Annotation
Key Point Annotation
Semantic Segmentation
Object Tracking Annotation
Quality Control
AI-powered quality control and inspection ensures product standards are met, reduces costly errors, and improves customer satisfaction. By rapidly and accurately assessing products and processes, AI systems enhance quality through increased detection speed, efficiency, and precision. Annotated data is essential for training models that make robust quality control possible.
Defect Detection
Deep learning defect detection algorithms can reliably identify product flaws, imperfections, and anomalies that may impact quality. Annotated defect examples across various product types, materials, and environments improve generalization of detection models. Pixel-level segmentation maps precisely localizing defects supplemented by tight bounding boxes, descriptive attribute labels, and detailed annotations further enhance accuracy.
Bounding Box Annotation
Semantic Segmentation
Polygon Annotation
Object Tracking Annotation
Automated Product & Packaging Inspection
Computer vision systems empower automated optical inspection for packaging and labeling errors, inconsistencies, and cosmetic defects at high volumes. Annotated images of properly packaged products train models to check for issues. Object localization, text reading, barcode and date code scanning, fill level detection, and image comparison against specs enable automated visual quality assurance and control.
Key Point Annotation
2D / 3D Cuboid Annotation
Text Annotation
Semantic Segmentation
Predictive Maintenance
AI predicts machinery maintenance needs, reducing downtime. Annotated sensors and equipment data enable the model to recognize early signs of wear and tear. Annotated infrared images highlighting temperature fluctuations, vibration spectra analysis from sound recordings, and scene labels from maintenance footage enable earlier failure prediction and proactive maintenance.
Poly-line Annotation
Bounding Box Annotation
Semantic Segmentation
Audio Clips Annotation
Asset Inspection
Drones and crawling robots equipped with cameras and sensors can autonomously inspect critical infrastructure and capital assets for damage, corrosion, and faults. Annotated data from sample inspection routes, example assets in various conditions, and domain environments optimize automated inspection. Object detection, surface defect segmentation, and 3D environment reconstruction annotations enable safe, comprehensive autonomous oversight.
Polygon Annotation
Key Point Annotation
2D / 3D Cuboid Annotation
Object Tracking Annotation
