AI startup Embedd raises £2m pre seed led by Seedcamp with support from Cocoa
This article covers Embedd, a London-based AI startup, raising £2m in a pre-seed funding round to build the software infrastructure that connects AI systems to the physical hardware they run on. The funding is intended to speed integration between AI models and diverse chips, supporting semiconductor partners, device makers and startups deploying robotics, vehicles and other intelligent machines.
London-based Embedd, an AI startup, has raised £2m in a pre-seed funding round to build the software infrastructure that connects AI systems to the physical hardware they run on. The funding arrives as Embedd expands commercial work with semiconductor partners and aims to reduce the engineering overhead that currently slows deployment of robotics, vehicles and other intelligent machines.
Why it matters
Investment into robotics and physical AI is growing quickly — nearly £13.9bn has been invested in the space so far this year — but a persistent integration bottleneck remains. Hardware vendors offer many different chips and interfaces, and software teams still hand-write large volumes of integration code or pore over dense hardware documentation. That friction delays product launches and raises costs for manufacturers and device makers.
Embedd’s approach tackles that middle layer: the glue between AI models and the dozens of chips inside a device. By automating parts of that work it promises faster time to production for embedded systems and to ease the practical rollout of physical AI across industries from manufacturing to healthcare.
Inside the product
Embedd builds a digital twin and agentic platform that models hardware and generates the integration code needed to make chips usable by higher-level software. The company says customers have achieved production-ready software for chips up to six times faster than with traditional methods.
Since launching commercially in April 2026, Embedd has signed contracts with multiple semiconductor companies. One public example is Microchip Technology, where Embedd is helping enable Zephyr support, a common real-time operating system used in embedded development. That integration is intended to make it easier for developers to use Microchip silicon within existing software ecosystems rather than adapting to new toolchains.
In the announcement, Rodger Richey, Vice President of Development Systems and Academic Programs at Microchip Technology, said:
The competitive question in embedded is no longer whose silicon is fastest, it's whose silicon is easiest to build on. Our work with Embedd is about meeting developers inside the software ecosystems they've already committed to, rather than asking them to come to ours.
Who are the investors?
Embedd closed a £2m pre-seed round. The round was led by Seedcamp and included participation from Cocoa, Connect Ventures, 2100 Ventures, Vesna Capital, U.ventures, Underline Ventures, Common Magic and Roosh Ventures.
The funding will be used to continue development of Embedd’s platform and to expand partnerships with semiconductor companies so more devices can be integrated into mainstream software ecosystems.
In the announcement, Carlos Eduardo Espinal MBE, General Partner at Seedcamp, said:
AI’s next chapter will play out in the physical world, but today’s software stack was never designed for that reality. Embedd is tackling one of the fundamental challenges facing industries from robotics and manufacturing to healthcare and automotive, and we’re excited to back Michael and the team as they build the infrastructure underpinning the next generation of intelligent machines.
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Founder perspective
Embedd was founded by Michael Lazarenko, Maxim Gorinov and Valentin Gololobov. The team’s experience building hardware during the Covid chip shortages and then coping with disruption after Russia’s invasion of Ukraine exposed a recurring problem: repeatedly rewriting software to support newly sourced components. That practical pain point shaped Embedd’s focus on automation and repeatability.
In the announcement, Michael Lazarenko, co-founder and CEO at Embedd, said:
The promise of physical AI is enormous, but today’s hardware fragmentation is slowing innovation. This funding enables us to expand our platform and help more semiconductor companies bring their devices into emerging software ecosystems
The bigger picture
Embedd sits at the intersection of AI, embedded systems and semiconductor tooling. As machine learning models move off the cloud and into devices, the industry needs a more standardised way to connect software to diverse hardware. Tools that reduce the manual work of low-level integration can shave months off development cycles and lower the barrier for smaller teams to build hardware-enabled products.
The company’s commercial traction with chip vendors and focus on developer experience reflect a broader shift: competition in embedded markets is increasingly about the software ecosystem around silicon, not just raw chip performance.
This deal underscores growing interest from AI investors in infrastructure for the physical world and highlights how UK startups and European partners are positioning themselves to supply the tooling that will make physical AI practical at scale.
They've invested in Embedd
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