Deepen AI vs Prodigy

Deepen AI provides connected data infrastructure for Physical AI, linking sensor calibration, capture, curation, annotation, and validation. Deepen Calibrate aligns camera, LiDAR, radar, and IMU sensors to a shared frame; the site reports under 0.8-pixel reprojection error and sub-1° angular error. Deepen Curate deduplicates sensor data, searches clips and frames, and surfaces rare or long-tail scenarios before labeling. Deepen Annotate handles 2D and 3D labels, including boxes, segmentation, keypoints, point clouds, and multi-frame tracking. Deepen Validate scores scenario coverage, audits and compares labels, prioritizes risky frames for review, and records signed audit trails. REST APIs and SDKs connect products to customer pipelines. Supported formats include ROS 2, MCAP, nuScenes, HDF5, Parquet, COCO, Rosbag, Zarr, KITTI, ORC, Pascal, WebDataset, and ASAM OpenLABEL. Deployment spans managed cloud, VPC, on-premises, and air-gapped environments. Pricing is on request.

Prodigy is a downloadable developer tool for creating training and evaluation data for machine learning models. Its browser-based app supports annotation of text, images, audio, video, relations, and multiple choice. Computer vision workflows include image classification, segmentation, and object detection; built-in recipes cover named entity recognition, text classification, dependency parsing, transcription, speaker diarization, training, and evaluation. Active learning models are included for named entity recognition, text classification, part-of-speech tagging, and dependency parsing. Users can create workflows with Python recipes and build interfaces using HTML, CSS, and JavaScript. Prodigy supports spaCy, has plugins for Hugging Face models, and integrates with major LLM API providers. Data is accessible through Python and the command line, and can be stored in SQLite, MySQL, or PostgreSQL, or exported to JSON. It runs on the user's own machines, including air-gapped machines, and its Python web server can be deployed in the cloud or on-premise. Personal costs $390, paid once, excluding tax; Company costs $490, paid once per seat in packs of five, excluding tax. Both include 12 months of free upgrades. Prodigy assumes basic Python and command-line familiarity; trials are not offered to individuals.