Robotics Power a $750 Billion Revolution
Robotics Layer powers the rise of autonomous robotics. By transforming user-submitted videos and technical documents into structured motion datasets, we equip next-gen robots and control systems with the intelligence to move, adapt, and operate in the real world, bridging human experience and autonomous execution.
Roadblocks for Autonomous Robotics
Despite the trillion-dollar robotics opportunity, autonomous systems still struggle with one core limitation: access to rich, diverse, real-world motion data. Robotics Layer solves this by crowdsourcing videos and technical documents from humans, then structuring them into high-fidelity datasets, which gives robots the context, experience, and intelligence they need to operate autonomously.
Big Tech Is Moving Into AI-Driven Finance
Figure AI
Figure AI, valued at over $2.6 Billion and backed by investors like Microsoft and OpenAI, is building general-purpose humanoid robots designed to work alongside humans. Their focus on robotics models capable of performing real-world tasks autonomously across factories, logistics, and service environments.
Agility Robotics
Agility Robotics, creators of the bipedal robot Digit and backed by DCVC and Playground Global, is a fast-growing robotics company building robots for warehouse automation. Their core mission is developing legged robots that can handle dynamic environments and execute human-like mobility tasks at scale.
TX Technologies
1X Technologies, backed by OpenAI and valued at over $1 Billion, is building advanced humanoid robots designed to operate safely in everyday environments. Their robots focus on dexterity, mobility, and human-assist tasks, with the goal of creating scalable general-purpose robotic labor that can integrate directly into homes and workplaces.
Robotics Layer: The Data Engine Behind Autonomous Robotics
Teaching Robots to Think and Improve
Robotics Layer transforms human-submitted videos and technical files into high-fidelity motion intelligence for the next wave of autonomous robots. These datasets give machines the ability to perceive, understand, and act within the physical world.
Rather than chasing bigger models, Robotics Layer builds clarity—turning chaotic real-world movement into a unified learning signal. The result is robots that move with intent, adapt instantly, and operate with precision in environments that never sit still.
