Israeli-born robotics startup Enigma has officially emerged from stealth following a $70 million seed funding round led by Index Ventures and Ribbit Capital, with additional participation from Conviction Partners Sarah Guo. Co-founded by Jonathan Jacobi, Microsoft’s youngest-ever employee, and Gal Niv, both veterans of Israel’s elite Unit 8200 cybersecurity division, the less-than-one-year-old company is tackling a foundational challenge in artificial intelligence: creating intuitive interfaces for embodied AI systems. Rather than prioritizing raw computational dexterity, Enigma’s strategy centers on human-robot interaction, aiming to make controlling robotic arms as effortless as adjusting a car volume dial. To validate its approach, Enigma has launched a global online experiment allowing users to interact with over 100 of its proprietary AI robots housed in facilities across Israel and California. These systems, built from the ground up with custom hardware and underlying AI models, execute tasks ranging from painting and chemistry mixing to simulated combat. The startup will collect real-world interaction data to identify optimal communication modalities, whether through text, audio, video demonstration, or direct manipulation. Founders Jacobi and Niv argue that current AI robotics require overly verbose instructions that defeat their practical utility, making frictionless control a prerequisite for mainstream adoption. The funding will support the expansion of this interaction research and the development of a novel robotic brain capable of generalizing tasks without explicit programming. While specific commercial applications remain undisclosed, Enigma has already secured partnerships in healthcare, logistics, and entertainment. Index Ventures partner Shardul Shah noted that the founders’ outsider status in traditional robotics allows them to bypass industry conventions and focus entirely on the end-user experience. As the company scales its data collection and interface optimization, its ability to translate human intuition into machine-readable commands could redefine how humans and autonomous systems collaborate in both industrial and consumer environments.