Roboflow

Build vision detectors and agents from a few labeled examples.

Build vision applications with a labelling-light workflow — point at examples, get a deployable detector. Recently extended into vision agents that reason over images and PDFs without bespoke training.

Data platform to curate, label, and manage AI training data.

An enterprise data development platform for preparing high-quality training data across images, video, documents, audio, DICOM, and 3D point clouds. It pairs AI-assisted labeling (SAM auto-segmentation, object tracking) with data curation, model evaluation, and workflow tooling, plus LLM-powered data agents for document tasks. Used heavily in medical imaging, robotics, and other physical-AI domains.

YOLO models for real-time object detection and vision.

The open-source PyTorch framework behind the YOLO (You Only Look Once) family of vision models. One unified API covers object detection, instance and semantic segmentation, image classification, pose estimation, and oriented bounding boxes, with both a CLI and a Python interface. The 2026 flagship, YOLO26, is an end-to-end, NMS-free architecture tuned for edge and low-power deployment.

All-in-one computer vision platform to curate, label, and train models.

A unified computer vision platform covering data curation, annotation, model training, and deployment across images, video, 3D point clouds, and medical imagery. AI-assisted labeling, experiment tracking, and a large catalog of installable apps make it customizable for most CV workflows. Free for researchers and small teams; Pro and self-hostable Enterprise editions for companies.