
Machenta
ACTIVEBritish AI company building a robot foundation model that lets robots learn new tasks from a single demonstration, without further training.
Machenta
Founded 2025 · London, United KingdomMachenta is a British AI company based in the King’s Cross district of London that describes itself as a frontier AI company building a new kind of robot foundation model. Its goal is “Instant Robot Learning”: a robot that learns a new task from a single demonstration, with no further training, through in-context learning and pre-training entirely in simulation, scaled by compute. The company grew out of the Robot Learning Lab at Imperial College London; its co-founders are Edward Johns (CEO) and Vitalis Vosylius (CTO), and the team includes authors of works such as Instant Policy (ICLR 2025) and “Learning a Thousand Tasks in a Day”, as well as researchers from DeepMind, Dyson, Huawei and Stability AI. In 2026 the company announced a USD 40M Seed round co-led by Creandum and Union Square Ventures. The model has not yet been publicly released and is offered via early access.
Founders
Professor of Robot Learning at Imperial College London. In 2020 he started a research group dedicated to one-shot robot learning and developed many of the early methods in the field, bringing that team and six years of research into Machenta.
PhD from Imperial College London. Built the first generalist in-context learning models for robotics trained entirely in simulation — Implicit Graph Alignment (CoRL 2023) and Instant Policy (ICLR 2025). Awarded Imperial’s PhD Prize for Outstanding Achievement in Robotics.
Domain of activity
2 areas · 4 technologies · 3 industries- Embodied AI
- Simulation & training environments
- Foundation Models
- Embodied AI
- Robotics
- Simulation
- Robotics
- Software & Technology
- Research & science
Global presence
HQ London · 2 regionsScale & funding
founded 2025 · SeedProfile & metadata
4 classification · 1 external linksClassification
- Statusactive
- Development stageearly
- Listed onNo
- Organization typeAI Lab
External links