Israeli Robotics AI Startup Enigma Raises $71 Mn Seed Funding to Build Smarter Robots
Jul 28, 2026 | By Nguyen Minh

Israeli startup Enigma has come out of stealth mode after raising $71 million in Seed funding. The company will use the investment to develop artificial intelligence (AI) technology for robots.
SUMMARY
- Enigma has raised US$71 million in Seed funding.
- The round was led by Index Ventures and Ribbit Capital.
- The startup is developing a general AI platform for robots.
- The funding highlights growing investor interest in AI-powered robotics.
The funding comes as investors are showing growing interest in AI for the physical world. Enigma aims to build AI that helps robots perform real-world tasks more intelligently and efficiently.
The funding round was led by Index Ventures and Ribbit Capital. Other investors included Conviction Partners, along with technology leaders and AI researchers from companies such as OpenAI, Anthropic, Thinking Machines, xAI, and Cognition.
The company wants to build an AI platform that can work with many different types of robots. Its goal is to reduce the time and engineering effort needed to train and adapt robots for different tasks and environments.
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“AI’s next chapter is moving beyond chatbots and screens into systems that can understand, adapt to, and operate in the physical world,” Jacobi said.
AI has made rapid progress in areas like language, coding, and image generation. However, using AI to control robots in the real world is still a major challenge.
Most robots today need to be specially customized for the tasks they perform. They also require a lot of manual data collection and engineering work before they can be used.
Because of these challenges, many robots work well only in controlled environments. Making them operate reliably in different real-world situations is still difficult.
Founded in 2025 by Jonathan Jacobi and Gal Niv, Enigma is building a general AI platform that can work with many different types of robots instead of creating software for just one robot.
Its goal is to reduce the time and engineering work needed to train robots for new tasks and environments, making them easier to develop, scale, and use in the real world.
















