L Square Labs
Data, learning, adaptation: building next gen robotics pipeline
The Problem
Robots are still far from being everyday tools. Despite decades of progress, most remain too expensive, fragile, and difficult to deploy outside controlled environments. Building and maintaining them requires expert knowledge, and they still rely heavily on hand-tuned control and calibration.
At l square labs, we're tackling this head-on: how to make advanced robots practical, affordable, and safe for real-world use. We believe the way forward isn't more manual tuning or rigid programming — it's smarter, data-driven intelligence built into the system itself.
Our goal is to lower the barrier to real-world robotics — to make capable machines that anyone can use, not just research labs or industrial giants. This matters because robotics should scale like computing did: from complex prototypes to ubiquitous, reliable tools that amplify human capability everywhere.
Our Approach
Our approach is a data-driven robotics pipeline — a unified framework that connects learning, control, and hardware into one feedback system.
Traditional robotics depends on fixed models and manual calibration. We replace that with a pipeline where robots learn from data, improving performance, safety, and efficiency through experience.
We develop our own hardware because real intelligence requires tight integration between mechanics, sensors, and algorithms. By controlling the full stack, we can co-design systems for learning-based control — faster iteration, better feedback, and safer operation.
Our first product, Rumi, demonstrates this philosophy in locomotion — the foundation of embodied capability. In parallel, we're developing manipulation systems, extending our approach toward more general-purpose, adaptive robotics.
In short, we're not just building robots that work — we're building robots that learn to work better, making advanced robotics accessible, robust, and ready for the real world.