Reimagine Robotics emerges from stealth with robots that learn on the job

Reimagine Robotics Ltd., a London and Sydney-based startup, launched today after developing technology that allows factory workers to train robots through direct demonstration. The company was founded in April 2025 by Jonathan Scholz, Oleg Sushkov, Akhil Raju, and Misha Denil. Scholz previously founded and led Google DeepMind's Applied Robotics team in London for seven years.

The core innovation centers on what Scholz calls "monkey-see, monkey-do"—a process where workers show a robot a task, observe it attempting the work, and correct it in real time rather than relying on specialist programmers to rewrite code whenever a production process changes. "A robot should arrive with the attitude of a new colleague: 'How can I help? What do you want me to do?'" Scholz said. "The people who understand the process should be able to answer those questions by showing the robot directly."

The company has already deployed robots in active manufacturing and recycling facilities. In one made-to-order plastics business, Reimagine Robotics trained robots to tend 3D printers overnight by removing print beds, operating latches, and pressing controls. The customer's own team then used the platform to automate additional stages, including washing, curing, and drying, demonstrating that non-specialist workers could extend the robot's capabilities. In a second deployment focused on recovering valuable critical materials from used hard drives, Reimagine Robotics developed a three-robot disassembly cell in collaboration with process engineers, optimizing the workflow in real time by combining robotic and human labor.

A key performance metric emerged from the hard-drive recovery project: Reimagine Robotics reduced the time required to prototype and test a new robot behavior from approximately one day to about 10 minutes. This acceleration allows teams to propose a new robot use and validate it almost immediately, removing a significant friction point in the deployment cycle. The company received pre-seed financing from Fly Ventures, firstminute capital, and a group of angel investors. Scholz emphasized that the model keeps workers central to the process: "Instead of someone having to repeat a tedious physical task thousands of times, they can teach the robot, and apply that ability wherever it is needed. I think of it more as a tool to amplify human labor." The startup is now entering a fundraising phase while expanding its team and planning further deployments across industrial and manufacturing settings.