Encord
Encord, founded in 2020 by Ulrik Stig Hansen and Eric Landau, is a London- and San Francisco-based company that provides an AI-native data infrastructure platform.
Profile
Encord sells a software platform that helps companies organize, label, and manage the data used to train and run artificial intelligence models, especially for physical-world AI like robots and self-driving vehicles.
Encord, founded in 2020 by Ulrik Stig Hansen and Eric Landau, is a London- and San Francisco-based company that provides an AI-native data infrastructure platform. The platform is designed to help enterprises manage, curate, and annotate multimodal data—including video, image, audio, LiDAR, text, document, geospatial, and HTML—for training and running AI models, particularly in physical AI applications such as autonomous vehicles, delivery drones, and robotics. In February 2026, Encord announced a $60 million Series C funding round led by Wellington Management, with participation from Y Combinator, CRV, N47, Crane Venture Partners, Bright Pixel, and Isomer Capital, bringing total funding to $110 million.
The company claims a customer base that includes Toyota Research Institute, Woven by Toyota, Zipline, Agility Robotics, Forterra, Hitachi Energy, UiPath, and others. Encord positions itself as a data layer for production AI, addressing the gap between legacy data infrastructure and the needs of modern AI workflows. The company's platform includes tools for data collection, curation, annotation, and model evaluation, with a focus on handling the scale and complexity of physical AI data.
The Series C funding is intended to accelerate development of a universal data layer for production-ready AI, as the company targets the growing market for physical AI applications. No revenue or headcount figures were disclosed in the available sources.
Who buys this
- Autonomous vehicle and robotics companies
- Enterprise AI teams building computer vision or multimodal models
- Defense and industrial automation firms
- Healthcare and life sciences organizations using AI for imaging or diagnostics
- Logistics and supply chain companies deploying AI for fleet management or delivery
Publicly disclosed clients
- Toyota Research Institute
- Woven by Toyota
- Zipline
- Agility Robotics
- Forterra
- Hitachi Energy
- UiPath
Strengths and what to watch
Strengths
- Encord's platform supports a wide range of data types (video, LiDAR, audio, text, geospatial) in a single workflow, which is rare among annotation tools and directly addresses the needs of physical AI companies.
- The company has secured a $60 million Series C round from a blue-chip investor (Wellington Management) and has backing from Y Combinator, indicating strong investor confidence in its market position.
- Encord's customer list includes well-known names in robotics and autonomous systems (Toyota Research Institute, Zipline, Agility Robotics), suggesting the platform is used in production by demanding, safety-critical applications.
Watch for
- Encord operates in a crowded market for AI data annotation and management tools, competing with companies like Scale AI, Labelbox, and Supervisely. Differentiation and market share gains are not guaranteed.
- The company has not disclosed revenue, profitability, or headcount figures. Without public financial data, it is difficult to assess its operational health or growth trajectory relative to competitors.
- The Series C announcement emphasizes physical AI as a growth driver, but this market is still nascent. If adoption of autonomous vehicles, drones, or humanoid robots slows, Encord's addressable market may be smaller than anticipated.
Recent moves
Key Information
- Industry
- Computer Vision
- Founded
- 2020
- Headquarters
- London and San Francisco
Frequently Asked Questions
What is Encord and what does it do?
Encord provides an AI-native data infrastructure platform that helps companies organize, label, and manage multimodal data for training AI models. It supports video, image, audio, LiDAR, text, and more, especially for physical AI applications like autonomous vehicles and robotics.
How much funding has Encord raised and who invested?
Encord raised a $60 million Series C round in February 2026, led by Wellington Management, with participation from Y Combinator, CRV, N47, Crane Venture Partners, Bright Pixel, and Isomer Capital. Total funding to date is $110 million.
What types of data does Encord's platform support?
Encord supports multimodal data including video, image, audio, LiDAR, text, document, geospatial, and HTML. This wide range allows companies to manage and annotate diverse data types in a single workflow, which is rare among annotation tools.
Who are some notable customers using Encord?
Notable customers include Toyota Research Institute, Woven by Toyota, Zipline, Agility Robotics, Forterra, Hitachi Energy, and UiPath. These companies use Encord for physical AI applications such as autonomous vehicles, delivery drones, and robotics.
How does Encord compare to competitors like Scale AI and Labelbox?
Encord competes in a crowded market with Scale AI, Labelbox, and Supervisely. Its differentiator is supporting a broad range of data types in one platform, targeting physical AI needs. However, market share gains are not guaranteed, and financial details are undisclosed.
What is physical AI and why is it important for Encord's growth?
Physical AI refers to AI systems that interact with the physical world, such as autonomous vehicles, delivery drones, and robots. Encord focuses on this nascent market as a growth driver, but if adoption slows, its addressable market may be smaller than expected.
Sources
- encord.com — Company description, product capabilities, and customer logos (Toyota Research Institute, Zipline, Agility Robotics, etc.)
- encord.com — Details of the $60 million Series C round, lead investor (Wellington Management), total funding ($110 million), and strategic rationale
- techcrunch.com — Context on Encord's prior funding and positioning as a data labeling platform for AI
- www.reuters.com — Broader AI venture funding trends in 2025, providing market context for Encord's Series C