Encord
"Train and Run AI on the Right Data"
London-based AI data platform for physical AI teams — annotate, curate, and evaluate multimodal datasets for robots and autonomous systems.
Encord is a London-headquartered AI data infrastructure company founded in 2021 by Ulrik Stig Hansen and Eric Landau (Y Combinator W21), providing the end-to-end data layer for physical AI development. The platform enables computer vision and robotics teams to annotate, manage, version, and evaluate large-scale multimodal datasets — spanning images, video, DICOM, LiDAR, and 3D point clouds — within a single collaborative environment. Encord's toolset includes AI-assisted labeling with temporal interpolation and object tracking for video, Encord Index for petabyte-scale dataset search and curation, and model evaluation pipelines.
The company serves 300+ teams including Toyota, Skydio, and Maxar, supporting use cases from humanoid robot training to autonomous vehicles and medical imaging. In February 2026, Encord raised a $60 million Series C led by Wellington Management, bringing total funding to $110 million. Data volume on the platform grew from 1 petabyte to 5+ petabytes within 18 months.
Encord is SOC 2 Type II certified and HIPAA/GDPR compliant.
Primary type & automation activities this supplier delivers:
Encord Annotate
- Model: Encord Annotate
- Launch Year: 2021
AI-assisted video and image annotation platform with temporal interpolation and object tracking for physical AI and computer vision teams.
Contact Encord
WEBSITE
https://encord.comHEADQUARTERS
United Kingdom
Company Facts
Founded
2021
Primary Role
Software/Algorithm
Company Size
-
Primary Region
Europe
Annual Sales
-
Funding Stage
-
Funding Total
-
Certifications & Memberships
CASIA's Peiyan Li Brings Two VLA Papers to IROS 2026
CASIA Ph.D. candidate Peiyan Li co-authored two IROS 2026 papers on VLA models for long robot tasks. We also cover his BridgeVLA and SpatialVAM work.
LG Electronics Showcases Robotics at 2026 First Global Challenge in Incheon
LG Electronics is actively participating in the 2026 First Global Challenge, an international youth robotics competition taking place at Songdo Convensia in Incheon. The event, which runs from Wednesday to Saturday, gathers youth teams from 185 countries to design and build robots aimed at addressing global challenges, particularly focusing on wildfire prevention and recovery due to climate change. This year's competition, themed “Igniting Innovation,” emphasizes the importance of robotics in tackling pressing issues like wildfires. LG's involvement includes sponsoring the event and showcasing its latest robotics technologies at an exhibition booth. The company also features its humanoid robot, LG CLOiD, allowing visitors to engage with the technology and learn about the innovative solutions being developed by young participants. As LG increases its investment in robotics as a key growth area, it aims to integrate physical AI into its strategy. The company recently launched LG Data Factory to enhance data management for robotics training. No further timeline was disclosed at the time of publication.
All News
Zhiyuan's Data Business Struggles to Support Robotics at $20 Per Hour
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Robotics Automation AI
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Robotics Automation AI
Huawei Unveils XMFS Prototype for Cross-Node Shared Memory at LPC 2026
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Xiaomi Expands Apple Device Integration with HyperOS 4 Features
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News Feed
Mecka Secures $60 Million in Series B Funding to Enhance Robotics Data Infrastructure
Mecka has successfully raised $60 million in Series B funding, led by Sequoia Capital, to enhance its robotics data infrastructure and commercial deployments. The company specializes in capturing human demonstrations using proprietary multi-sensor hardware, converting this data into training signals for robotic systems, and collaborating with researchers on the EgoVerse study. This funding is significant as it positions Mecka to bridge the gap between available AI training data and the real-world operational needs of robots. With a reported run-rate revenue exceeding $100 million as of June 2026, Mecka anticipates reaching $300 million by year-end, indicating strong growth in the robotics sector. Looking ahead, Mecka plans to utilize the new capital to develop more data-capture hardware and expand its research and deployment capabilities. The company aims to provide tailored training data for various robotic applications, emphasizing the importance of human-like learning for future robotic systems.
AI Funding & Investment Physical AI Startups AI Data deployment
IROS 2026 Best Paper Finalists: South Korea Leads
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IROS 2026 Category Award Finalists: All 22 Papers
From humanoid tennis to bin picking and farm robots: the 22 finalists for IROS 2026's eight category awards, and what each one means for industry.
Microsoft Unveils New AI PCs Featuring Nvidia's RTX Spark Chip and Enhanced Windows 11
Microsoft has announced the specifications and pricing for its new Surface Laptop Ultra and Surface RTX Spark Dev Box, powered by Nvidia's RTX Spark chip. The Surface Laptop Ultra starts at $2,600, while the Surface RTX Spark Dev Box is priced from $6,000, designed for on-device AI model execution with enhanced hardware capabilities. These new devices are significant as they cater specifically to developers, offering advanced features like superior cooling and a revamped Windows 11 with 'Execution Containers' for easier AI agent sandboxing. Microsoft CEO Satya Nadella emphasized the need for orchestration and memory management in AI applications, highlighting the platform's future direction. Looking ahead, Microsoft is positioning these PCs as versatile tools not only for developers but also for content creation and gaming. The company is incentivizing trade-ins of MacBook Pros, reflecting the competitive landscape in the developer community. No further timeline was disclosed at the time of publication.
AI Hardware TC Microsoft nvidia
China’s Dexterous Hand Industry, 2026 Part 2 — The Technology
Linkage, tendon, direct drive or hybrid — and why hardware is converging while the DL1–DL5 manipulation scale decides who wins. Part 2 of 3.
China’s Dexterous Hand Industry, 2026 Part 1 — The Demand Picture
MIR Databank puts China dexterous hand shipments above 30,000 units in 2026, yet only 3.5% of 2025 demand came from factory production. Part 1 of 3.
WRC 2026 Core Components: 137 Robot Parts Suppliers
The third report in the WRC 2026 series. Report 1 mapped all 248 exhibitors by category and Report 2 covered the 139 that build finished robots. This one covers the 137 that build what goes inside them.
How a Robot Should Die: Phase 5, Lifecycle KPIs, and One Welding Arm's Four Years
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Your Three-Shift Robot Is on a One-Shift Maintenance Plan: Phase 3 and the PM System
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WAIC Review 2/4: World Models vs. VLA: Robotics' Next 'ChatGPT Moment'
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WAIC Review 4/4: From Port AGVs to Hospital Night Shifts: What WAIC 2026 Reveals About Real Robot Deployments
From 530+ AGVs at a Singapore port to robots on Apple's line, WAIC 2026 speakers shared concrete data on where embodied AI robots are actually working today.
Encord and Zander Labs Use EEG Data to Advance Physical AI Training Techniques
In a warehouse in San Leandro, California, a worker is participating in an experiment that combines a data collection helmet with EEG sensors to train robots. This collaboration between Encord and Zander Labs aims to address the scarcity of real-world training data for physical AI, which is a significant challenge in the field. The importance of this experiment lies in its potential to generate valuable training data by capturing the neural activity of operators during tasks. This data can inform robot models about operator states, such as confusion or focus, enabling more efficient training and resource allocation. Encord is also collecting remote control data and first-person videos to create a comprehensive data production system. Looking ahead, the integration of EEG helmets, muscle sensors, and detailed annotations could revolutionize how robots are trained, providing the necessary real-world data that is currently lacking. No further timeline was disclosed at the time of publication.
Physical AI Robot Training Data Collection EEG Technology
Encord Explores Brain Wave Data to Enhance Physical AI Training in California
Encord, a data tooling company, is pioneering the use of brain wave measurement to enhance physical AI training. Located in San Leandro, California, the company is conducting trials with a brain wave headset developed by Zander Labs, aiming to create a unique data set that captures mental states during robotic training tasks. This initiative is significant as it addresses the critical shortage of real-world training data for humanoid and warehouse robotics. Encord's approach could potentially revolutionize how robotics companies generate and utilize training data, moving beyond traditional methods that often fall short in fidelity and scale. Looking ahead, Encord plans to evaluate the effectiveness of the brain wave-tagged data set in improving robotic performance. The outcome of this trial could determine whether the company will expand this innovative data generation method, which is seen as essential for overcoming the current data bottleneck in robotics.
AI Robotics Exclusive
