From images and videos to LiDAR and multisensor data, we help machines see with accuracy, scale, and confidence.
DDD is a global leader in AI data services, delivering high-quality computer vision data training at scale. Our mission is to help organizations build reliable, ethical, and production-ready AI systems while creating meaningful digital employment worldwide.
Enable real-time identification and categorization of objects across images and video streams to support accurate perception and decision-making.
Train autonomous systems to reliably detect lanes, vehicles, obstacles, and pedestrians in dynamic and safety-critical environments.
Power AI models that understand human actions, movement patterns, and interactions across various environments, including surveillance, sports, and smart spaces.
Support advanced human-centric vision applications by training models to recognize facial features, body poses, and natural gestures with precision.
Enable machines to understand depth, distance, and spatial relationships using LiDAR and 3D sensor data for accurate reconstruction of the environment.
Identify defects, irregularities, and outliers in visual data to improve quality control, safety monitoring, and risk detection.
Train vision systems to recognize products, monitor shelf availability, and improve inventory visibility across physical retail environments.
Support geospatial intelligence by training models to analyze satellite and drone imagery for mapping, monitoring, and situational awareness.
Training perception systems to safely detect, predict, and navigate complex driving environments.
Training and evaluation data that strengthens monitoring, alerting, and safety-assist features for modern vehicles.
Powering robots with visual intelligence for navigation, manipulation, and human interaction.
Supporting vision systems that enable human-like perception, gestures, and interactions.
Supporting surveillance, public safety, and infrastructure monitoring applications.
Enhancing satellite and aerial imagery analysis for mapping, defense, and environmental insights.
Enabling document vision, fraud detection, and visual verification workflows.
Digitizing, restoring, and preserving historical artifacts and archives using computer vision.
Analyzing player movements, performance metrics, and in-game strategies through video data.
Our highly trained annotation teams combine human judgment with AI-assisted workflows to deliver accurate, consistent, and edge-case-ready computer vision data.
We support complex vision systems with integrated annotation across images, video, LiDAR, radar, and multisensor fusion data.
Multi-layer quality assurance processes ensure every dataset aligns with model performance goals and deployment standards.
Optimized workflows and automation reduce annotation cycles and accelerate model iteration and deployment.
Author: Umang Dayal The promise of automation has always been efficiency. Fewer delays, faster decisions, reduced human error. And yet, as these systems become more autonomous, something interesting happens: risk…
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Your computer vision datasets are protected at every stage through globally recognized security standards and secure operational infrastructure.
Verified controls across security, confidentiality, and system reliability
Comprehensive information security management with continuous audits
Ensuring responsible handling of personal and medical data
DDD provides end-to-end computer vision services, including image annotation, video annotation, 3D LiDAR labeling, and multisensor fusion to support AI model training and deployment.
We support bounding boxes, polygons, semantic and instance segmentation, keypoints, cuboids, tracking, and 3D point cloud annotation across images, video, and sensor data.
We use multi-layer quality assurance frameworks, including inter-annotator agreement, validation sampling, and performance-based quality metrics aligned with model outcomes.
Absolutely. We specialize in multimodal computer vision workflows, including synchronized annotation of camera, LiDAR, radar, and fused sensor datasets.
We support ethical and responsible AI by curating diverse datasets, applying balanced annotation strategies, and implementing bias-aware quality checks.
Delivery timelines depend on dataset complexity and volume, but our optimized pipelines are designed to accelerate annotation cycles and reduce time-to-model deployment.
