Reimagine Robotics emerges with AI platform for workers

Reimagine Robotics has emerged from stealth with an AI robotics platform designed to let workers train robots directly. The company was founded by former leaders of Google DeepMind's Applied Robotics team.

Based in London and Sydney, Reimagine Robotics says its system allows factory-floor staff to show a robot a task, watch it attempt the work, and correct mistakes without specialist programming. It is targeting industrial and manufacturing settings, where processes often change and conventional robot deployments can be slow to adapt.

Chief Executive Officer Jonathan Scholz founded Google DeepMind's Applied Robotics team in London and led it for seven years before co-founding Reimagine Robotics in April 2025 with Oleg Sushkov, Akhil Raju, and Misha Denil. Its initial phase was backed by pre-seed funding from Fly Ventures, firstminute capital, and angel investors.

Scholz outlined the company's approach by describing how workers interact with the machines.

"A useful robot should be able to learn from the person doing the work. They should be able to show it a task, put it right when it makes a mistake, and move on to the next problem. That is what it means for a robot to learn on the job. It's a process we call 'monkey-see, monkey-do,'" said Jonathan Scholz, Chief Executive Officer of Reimagine Robotics.

He also described how a robot should fit into an existing workplace.

"A robot should arrive with the attitude of a new colleague: 'How can I help? What do you want me to do?' The people who understand the process should be able to answer those questions by showing the robot directly," Scholz said.

Factory use

Reimagine Robotics says its robots are already being deployed in advanced manufacturing and electronics disassembly facilities. In one project for a made-to-order plastics business, robots were trained to tend 3D printers overnight by removing print beds, operating latches, and pressing controls.

The customer's team then used the platform to automate other stages of the process, including washing, curing, and drying. The example is central to Reimagine Robotics' argument that workers, rather than software specialists, should be able to make incremental changes on site.

In another deployment, the company worked on recovering critical materials from used hard drives. It said it developed a three-robot disassembly cell with process engineers, allowing robots and people to work together while the workflow was adjusted in real time.

During that project, Reimagine Robotics said it cut the time needed to prototype and test a new robot behaviour from about one day to around 10 minutes. That, it said, allowed teams to suggest a new task for the robot and test it almost immediately, making robotics part of day-to-day process design rather than a separate technical exercise.

Growth plans

The past year focused on building the product, assembling a team, and testing the platform with customers. Reimagine Robotics is now seeking a new funding round while expanding staff and increasing the number of workplace deployments.

"We're excited to come out of stealth. This last year was about building a core product and a team, and working with customers to test the platform. After working with several partners, we're absolutely convinced it's not only viable, but that there is a need for this technology, and that it has massive potential across an array of industrial and manufacturing settings," Scholz said.

He said the next stage would focus on fundraising, hiring, and expanding deployments.

"This next stage is about a new round of fundraising, expanding our team for more deployment muscle, putting robots into more workplaces, and showing that each deployment can make the next one faster, more reliable, and more efficient," Scholz said.

Human role

Scholz said the company does not present the technology as a substitute for workers, but as a system that still relies on people to identify bottlenecks and shape the task. The position addresses a central tension in industrial automation, where companies are often pressed to explain whether new systems are meant to remove labour or reorganise it.

"For us, this is not about taking people out of the process. A robot that learns on the job depends on people. The worker identifies the bottleneck, shows the robot how to help, and corrects it until it is useful," Scholz said.

He linked that role to the transfer of tacit knowledge from staff to machines.

"The robot turns that person's knowledge into leverage. 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," Scholz said.

"I think of it more as a tool to amplify human labour," Scholz said.