Intropy, a spare parts decision automation startup, has raised £8 million in seed financing. The round was led by Felix Capital, with participation from Quiet Capital and early investors General Catalyst and firstminute capital.
Distributors, manufacturers and recyclers use Intropy to improve profitability and operational efficiency across decisions that have historically depended on spreadsheets, outdated legacy software and extensive manual review. Structured and unstructured information spread across ERP systems, warehouse platforms, spreadsheets, images, documents and phone conversations is aggregated, and decisions are then automated directly within a customer's existing ERP rather than presented as recommendations for employees to review. Inventory levels and pricing are adjusted dynamically and obsolescence is managed continuously, moving parts businesses from periodic, reactive reviews to decisions that update as market conditions change.
In the automotive industry alone, more than $4 billion in spare parts are estimated to be transacted every day, yet much of the industry still runs on software designed decades ago, with teams manually reviewing hundreds of thousands of individual SKUs to decide how much stock to hold, where to place it, when to change a price and which inventory is becoming obsolete. Those challenges are becoming more acute as parts businesses contend with tariffs, rising fuel and operating costs, uncertain repair volumes and increasingly complex vehicles and machines.
Founded in 2024 by Franziska Kirschner and YihKai Teh, Intropy has processed more than $10 billion in parts demand since launch, enough to buy new spark plugs for every passenger car in North America. Customers using the platform have achieved measurable improvements, including returns on investment of more than 10x. Kirschner is a University of Oxford-trained physicist whose research has been published in Nature, and Teh is an AI academic from University College London; the pair worked together at Tractable, where they became inventors on more than 10 patents applying AI to the sector.
The funding will accelerate product development, expand the engineering and machine learning teams, and establish a New York office as Intropy grows its presence in the United States, alongside continued expansion across Europe. Engineers and AI researchers are being hired in London and New York.
The physical economy is sustained not only by what we build, but by our ability to keep it working. Spare parts make that possible, yet many of the industry's most important decisions still rely on fragmented systems and manual work. We are not interested in adding another dashboard on top of that complexity. We are building an AI-native operating system that can make and execute decisions autonomously, at scale and speed. The future is here, and we are ready to serve an industry that technology has overlooked for far too long.
Every machine made from multiple components will eventually need spare parts, whether it is a car on the road today, an autonomous vehicle of tomorrow or a robot supporting humanity on Mars. We're building the intelligence layer that understands the extraordinary complexity of spare parts: what fits, how it performs and when it is needed, so parts businesses can make better decisions. Our goal is to make that complexity invisible, with intelligence working quietly in the background. The best user experience is when the user needs to do nothing at all.
Every product is designed with components, or spare parts, yet the systems managing those parts remain remarkably manual and fragmented. At Felix, we believe AI will fundamentally transform product design, and how the physical economy operates. Intropy is building the intelligence layer that can make supply chains faster, smarter and significantly more efficient, ultimately bringing a better product faster in the hands of the end user. We were immediately impressed by Fran and YihKai's technical depth, domain expertise and ambition, and are excited to support them in building a new intelligence layer for the physical world.
