Enigma Raises $70 Million to Train AI Robots Using Real Human Interactions

Enigma Raises $70 Million to Train AI Robots Using Real Human Interactions

Enigma emerged from stealth with a $70 million seed round and unveiled an online research initiative that will let people around the world interact with more than 100 of its proprietary AI robots. Rather than concentrating solely on improving robotic capabilities, the startup says its primary goal is to understand how people naturally communicate with machines and use those insights to shape future robotics interfaces and foundation models.

The seed financing was led by Index Ventures and Ribbit Capital, with participation from Sarah Guo of Conviction Partners. Enigma said the funding will support its effort to gather large-scale human interaction data instead of launching a traditional commercial product.

As part of the experiment, users will be able to remotely control robots housed in hangars in Israel and California. The systems can complete a range of activities, including painting with a brush, fencing with swords, and carrying out simple chemistry experiments by picking up and mixing liquid-filled flasks. According to the company, it developed both the robotic arms and the AI models that power them from the ground up.

Enigma was founded by Jonathan Jacobi and Gal Niv, longtime friends who first met in teenage hacking competitions before serving together in Israel's Unit 8200. Jacobi was previously Microsoft's youngest-ever employee after being recruited by Wiz founder Asaf Rappaport. The founders entered robotics without prior industry experience, assembling a team that includes former AI lab researchers, math Olympiad winners, and several recruits who left PhD programs to join the company.

That unconventional background attracted investors who believe approaching robotics from outside the field could produce different ideas. "There are a lot of robotics industry insiders participating in the next wave of embodied intelligence, but Jonathan and Gal are outsiders — they’re not roboticists. It affords them more room for originality," said Shardul Shah, partner at Index Ventures. "Someone who’s an insider may start with the capability of teleoperation or dexterity, but Enigma is starting from a very different place: 'What’s the ultimate experience?'"

Enigma's central premise is that today's robots remain difficult to use, even as underlying AI models improve. Jacobi argues that reducing the effort required to communicate with machines is just as important as expanding what those machines can do.

"If you had to do your dishes and spent 15 minutes explaining to a robot where to put everything, everyone reaches the point of 'Forget it, I’ll just do it myself,'" Jacobi said. "Right now, everyone is at that point — even with the most capable models."

He compares the experience to adjusting a car's volume knob, arguing that people expect simple, intuitive controls rather than complicated instructions. Enigma hopes its public experiment will reveal an equivalent interaction model for robotics by testing different ways people naturally direct machines.

"We’re going to learn a lot about what is the right way to interact with robots," Jacobi said. "Do we want to just talk to them over text or audio? Do we want to show them an example as a video? Or maybe do we want to tap, drag, and drop?"

The company acknowledges that the research is exploratory. By analyzing how participants communicate with its robots, Enigma hopes to identify interfaces that not only make robots easier to operate but also improve how its foundation AI models are trained.

While the long-term commercial direction remains undefined, Jacobi said Enigma is already partnering with companies in healthcare, logistics, and entertainment, though he declined to discuss specific use cases.

This analysis is based on reporting from TechCrunch.

Image courtesy of Enigma.

This article was generated with AI assistance and reviewed for accuracy and quality.

Last updated: July 27, 2026

About this article: This article was generated with AI assistance and reviewed by our editorial team to ensure it follows our editorial standards for accuracy and independence. We maintain strict fact-checking protocols and cite all sources.

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