Facts

• Segment: Data Infrastructure
• Country: Germany
• Founded: 2026
• Website: https://www.formove.de/

Profile sections

• Summary
• Market context
• Facts
• Context / Market Position
• Context tags
• Sources

Summary

FORMOVE develops data infrastructure for physical AI, using human motion and interaction data to help robots learn real-world behavior. The German startup focuses on scalable training data for robot learning rather than building a single robot product line.

Market context

Physical-AI progress depends on high-quality interaction data, not only models. FORMOVE matters because it sits in the data layer that can teach robots from human motion and manipulation traces. FORMOVE provides robotics training-data infrastructure by capturing and transforming human motion and interaction data for physical-AI model development.

Facts

• Website: https://www.formove.de/
• HQ: Munich, Bavaria, Germany
• Founded: 2026
• Segment: Data Infrastructure

Human-motion data pipeline for physical AI

FORMOVE is focused on real-world data capture and transformation for robot training.

• Target environment: Embodied-AI and robot-learning programs that need human motion and interaction data.
• Deployment model: Data-infrastructure provider supplying captured and processed training data rather than robot hardware.
• Customer context: Robot builders and physical-AI model teams that need demonstrations, motion traces, or interaction data.
• Workflow context: Captures human motion and interactions, then transforms them into usable data for robot model training.
• Commercial maturity: Early data-infrastructure company focused on human-motion and interaction datasets for physical-AI training.
• Market position: Physical-AI data provider in the European embodied-intelligence stack.
• Adoption constraints: Adoption depends on dataset quality, task coverage, privacy/compliance, and proof that the data improves robot policies.
• Adjacent context: Adjacent context includes robotics data vendors, embodied-AI dataset companies, teleoperation data pipelines, and robot-learning infrastructure.
• Source confidence: high

Context tags

• Physical AI data infrastructure - Stack Layer - FORMOVE positions itself as a real-world data pipeline for Physical AI.
• Physical AI training data - Stack Layer - FORMOVE captures and transforms human motion and interaction into training data for robots.
• Teleoperation and data collection - Workflow - FORMOVE is adjacent to human demonstration data capture, though its site emphasizes motion and interaction data rather than remote operation.