Reimagine Robotics has begun operating publicly with technology designed to let factory workers teach and correct robots without specialist programming. The London- and Sydney-based company is developing robotic systems that can be trained through demonstrations. Workers show a robot how to perform a task, observe its attempt and make corrections as production requirements change.
“A useful robot should be able to learn from the person doing the work,” co-founder and Chief Executive Jonathan Scholz said. “They should be able to show it a task, put it right when it makes a mistake and move on to the next problem.”
Scholz previously founded Google DeepMind’s Applied Robotics team in London and led it for seven years. He established Reimagine Robotics in April 2025 with former colleagues Oleg Sushkov, Akhil Raju and Misha Denil.
The company’s initial development was financed through pre-seed funding from venture capital firms Fly Ventures and firstminute capital, along with several angel investors. Reimagine Robotics is now seeking additional funding and plans to expand its workforce and deploy its systems in more industrial facilities.
The company has tested its robots in manufacturing and electronics-disassembly operations.
At a made-to-order plastics business, the robots were trained to tend 3D printers overnight. Their tasks included removing print beds, operating latches and pressing machine controls. Employees at the customer later used the platform to automate further stages of the production process, including washing, curing and drying.
In another project, Reimagine Robotics worked with process engineers on a three-robot cell for dismantling used hard drives and recovering critical materials. The workflow combined robotic systems with human operators, allowing the process to be modified while it was being developed.
Reimagine Robotics said it reduced the time needed to prototype and test a new robotic behaviour during the project from about one day to approximately 10 minutes. The shorter testing cycle allowed engineers to propose and evaluate potential robotic tasks more quickly.
The company positions workers as the primary source of operational knowledge in its model. Employees identify production bottlenecks, demonstrate tasks and correct the robots until they can perform the required work.
“For us, this is not about taking people out of the process,” Scholz said. “The worker identifies the bottleneck, shows the robot how to help and corrects it until it is useful.”
