Vesoma Launches with 60+ Team and Vesoma 1 Humanoid

Recap

Source: Humanoids Daily, report of Sept. 23, 2026

According to the report, the startup previously known for its boxy Kyle prototype has officially launched as Vesoma. The company states it has assembled a team of more than 60 people and secured over 3,500 square meters of laboratory and office space in Munich, Germany, and Limassol, Cyprus. Vesoma claims it began operations in December 2025 and is currently building the first units of its initial product, Vesoma 1.

The company’s announcement highlights a central technical thesis: that humanoids must learn through direct interaction with the physical world to achieve reliability, rather than relying solely on demonstrations. Vesoma identifies manufacturing, logistics, and warehousing as its initial target markets. The leadership team includes CEO Nikolai Ensslen, co-founder of Synapticon; Chief AI Officer Martin Riedmiller, formerly a research director at Google DeepMind; and Chief Strategy Officer Peter Skoromnyi, co-founder of Easybrain. The company explicitly rules out military, weapons, and surveillance applications.

Context

Vesoma’s emergence adds a new player to Europe’s growing humanoid robotics sector. The inclusion of Martin Riedmiller, a prominent figure in reinforcement learning and control systems from Google DeepMind, signals a strong emphasis on advanced AI capabilities. The company’s focus on learning through interaction aligns with a broader industry shift away from pure imitation learning, aiming to address the reliability gap that has hindered humanoid adoption in industrial settings. Vesoma’s background in industrial robotics and consumer software provides a unique combination of hardware expertise and scalable software development.

Robot's take

Vesoma’s approach is promising but faces significant challenges. The transition from locomotion to complex manipulation and whole-body coordination is a major technical hurdle. The company’s claim that interaction-based learning will outperform demonstration-based methods is a strong thesis, but it lacks empirical evidence in the form of success rates or full-shift performance data. The next critical test will be Vesoma 1’s ability to perform useful tasks reliably in changing environments, moving beyond impressive walking demonstrations to practical industrial applications.