Data annotation involves labelling raw data, such as images, video, text, or audio, to train machine learning models to identify patterns and make predictions. For example, the self-driving car model requires thousands of labelled images of pedestrians and road signs to safely recognize them in the real world.
Converting raw images to precise and model ready training data for object detection and classification.
Accurate 2D and 3D bounding boxes, including orientation, for autonomous driving and robotics.
Classify pixels and Segment complex boundaries for medical imaging, Retail and Aerial analysis.
Comprehensive vector labelling of lanes, cartography and infrastructure monitoring.
Supporting Spatial intelligence and Multi-modal perception systems for complex physical environment.
Multi-frame object tracking, segmentation and classification in dynamic point clouds.
Land-use classification, identification of crop health and urban mapping at a large scale.
Organizing temporal, auditory and textual information for powerful multi-modal AI systems.
Event detection, activity recognition and tracking per frame through complex timelines.
Speech-to-text Transcription, Acoustic Event Tagging, Sentiment/Intent classification.
Why AI and computer vision engineering leaders choose our managed workforce:
Multi-layered quality assurance workflows that use expert human review coupled with automated validation scripts.
Easily ramp up from 5 domain-trained annotators to hundreds.
Enterprise-level data security systems, NDA-compliant processing and limited access to sensitive workstations.
We seamlessly integrate with your own annotation platforms or industry tools.
We analyze your technical documentation, edge cases and schema rules to create a bulletproof Standard Operating Procedure (SOP).
A calibrated sample run is conducted to ensure that our team is in line with your specific standards.
Production starts, with constant supervision and multi-phase quality assurance.
Output in the desired format that can be used for model training.
Find answers to the most commonly asked questions about our annotation services.
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