Deplace AI's Motion2Text API Aims to Solve the Data Problem in Robotics

The Paris-based startup, backed by Berkeley SkyDeck, converts human video into language to train and benchmark Physical AI systems.

About Deplace AI

Published

The data problem in robotics is a bottleneck measured in years. Deploying a robot for a new task can take months of manual programming and thousands of hours of trial-and-error data collection. Deplace AI, a Paris-based startup founded in 2025, is betting that the solution is already being recorded on millions of smartphones. Its core proposition: turn ordinary human motion videos into the structured language needed to train and evaluate so-called Physical AI [F6S, 2025].

The Wedge: From Video to Vocabulary

Deplace AI's initial product surface is a platform that benchmarks multiple AI robots on real-world workflows, claiming to help companies select the right hardware [Deplace AI, 2025]. The deeper technical wedge, however, is the data pipeline underneath. The company is building a Motion2Text API designed to ingest raw human video and output detailed, language-level descriptions of the actions performed [LinkedIn, 2026].

The Team and Technical Credentials

The founding trio brings a mix of technical and entrepreneurial focus. CEO Pedro Milcent leads the company [F6S, 2025]. Co-founder Elie Chelly is a PhD candidate in robotics, tactile sensing, and dexterous manipulation at ISIR Sorbonne [LinkedIn, 2026]. Both Chelly and co-founder Nathan Kammoun studied at EPFL [LinkedIn, 2026].

Founder Role Key Background
Pedro Milcent Co-founder, CEO Mission focus on human data for robotics [F6S, 2025].
Elie Chelly Co-founder PhD candidate in robotics & dexterous manipulation at ISIR Sorbonne [LinkedIn, 2026].
Nathan Kammoun Co-founder Studied at EPFL [LinkedIn, 2026].

Early Traction and Claims

Deplace AI's public traction is anchored in a single, named case study and a set of self-reported performance metrics. The company states it achieved measurable throughput gains for a leading e-commerce fulfillment company by identifying and deploying the right AI robot [Deplace AI, 2025]. Its broader platform claims are ambitious:

  • Performance lift. Robots evaluated on actual workflows see 40% higher performance [Deplace AI, 2025].
  • Deployment speed. The data-backed selection process leads to a 6x faster time-to-deployment [Deplace AI, 2025].

The Competitive and Technical Hurdles

The space for robot simulation and evaluation is not empty. Established players like inVia Robotics offer integrated robotics-as-a-service for fulfillment. Startups like Antioch operate in the physical AI simulation arena. Deplace AI's differentiation rests on its proprietary data translation layer, the Motion2Text API, rather than on building robots themselves.

The Next Twelve Months

With a disclosed $200,000 pre-seed from the Berkeley SkyDeck Fund, the company is in the earliest stage of proving its thesis [Berkeley SkyDeck]. The immediate milestones are clear: move beyond the initial e-commerce case study to publicly name additional pilot customers, release technical details for the Motion2Text technology, and secure a seed round to scale the data collection and engineering effort.

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