Encord

Encord is a data development platform for AI that lets teams curate, annotate, and manage multimodal data (images, video, audio, documents, medical imaging, and sensor data) across the model lifecycle. It targets demanding, high-stakes domains such as computer vision, medical imaging, robotics, and physical AI, integrating annotation, curation, and model-assisted labeling. Encord serves hundreds of enterprise AI teams (including Toyota, Skydio, and Zipline) and has raised about $110M in total funding.

Encord provides an integrated platform for the data side of AI development: importing and curating datasets, annotating them (with support for complex modalities like video, DICOM medical imaging, LiDAR, and audio), managing labeling workflows and quality, and evaluating data and model performance. Its aim is to give AI teams a single system for turning raw multimodal data into high-quality training and evaluation sets. Encord has increasingly positioned itself around 'physical AI' and demanding, high-stakes domains, including robotics, autonomous systems, and healthcare, where accurate annotation of video, sensor, and medical data is critical. It emphasizes handling large-scale, complex data and integrating annotation, curation, and model-assisted labeling into one workflow. The company reports serving hundreds of enterprise AI teams, with named customers such as Toyota, Skydio, and Zipline. It has raised about $110 million in total funding, including a $30 million Series B led by Next47 (2024) and a $60 million Series C led by Wellington Management (2026), with participation from investors including Y Combinator, CRV, and others. Pricing is generally sales-led and not fully published, so teams should request a quote based on their data volumes and modalities.