Embedd Raises $2.7M Pre-Seed to Build AI Infrastructure for Physical Machines

London-based physical AI startup Embedd has raised $2.7 million in pre-seed funding led by Seedcamp to build software infrastructure for robots, cars, drones and medical devices.

The round also saw participation from Cocoa, Connect Ventures, 2100 Ventures, Vesna Capital, U.ventures, Underline Ventures, Common Magic and Roosh Ventures.

Founded by Michael Lazarenko, Maxim Gorinov and Valentin Gololobov, Embedd is building an AI-powered platform that simplifies the software integration work required to connect different chips and hardware components.

The company says engineers currently spend four to six months manually writing code to make different chips work together. Embedd's platform aims to reduce that process to around three weeks while delivering production-ready software for specific chips significantly faster.

Embedd's platform converts chip documentation into a digital twin of the hardware, allowing software teams to work with a structured representation of the underlying hardware instead of manually going through technical documentation.

Co-founder and CEO Michael Lazarenko said the increasing use of AI in factories, vehicles, robots and critical infrastructure is creating greater complexity for software teams as hardware configurations continue to evolve.

The founders previously operated a hardware company together, where repeated component shortages and firmware rewrites exposed the challenges of integrating different hardware systems. The company's production facility was later affected by Russia's invasion of Ukraine, further shaping the founders' focus on reducing hardware-software integration complexity.

Embedd launched commercially in April 2026 and has since signed contracts with multiple semiconductor companies. Its customers include Microchip Technology, where the company is enabling support for the Zephyr real-time operating system.

The startup is targeting a growing physical AI market where software infrastructure remains a critical layer connecting intelligent machines with the hardware they operate on.

The new funding will be used to expand Embedd's platform and deepen partnerships with semiconductor companies. The company aims to make new hardware easier to integrate across software ecosystems and reduce the time required to bring chips into products.

Embedd's approach focuses on the software layer behind physical AI, addressing the integration challenges that arise as robots, vehicles, drones and other intelligent machines become increasingly hardware-dependent.