London-based Intropy raises €9.5 million to build the AI-native operating system for the spare parts industry
Intropy, a London-based AI-native platform automating inventory, pricing and other critical decisions for spare parts businesses, has raised €9.5 million ($11 million) in Seed financing.
The round was led by Felix Capital, with participation from Quiet Capital and early investors General Catalyst and firstminute capital.
Franziska Kirschner, co-founder and CEO, said, “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.”
Founded in 2024 by Franziska Kirschner and YihKai Teh, Intropy is building the AI-native operating system for the spare parts industry. The company states that it helps spare parts distributors, manufacturers, and recyclers increase profitability and operational efficiency through AI-powered decision-making processes that have historically depended on spreadsheets, outdated legacy software and extensive manual review.
Intropy enables spare parts businesses to automate critical workflows across demand prediction, inventory distribution, obsolescence management and dynamic pricing using AI.
According to the company, much of the spare parts industry still runs on software designed decades ago. It notes that critical decisions, including how much stock to hold, where to place it, when to change a price, and which inventory is becoming obsolete, often require teams to manually review hundreds of thousands of individual SKUs.
It further notes that with tariffs, rising fuel and operating costs, uncertain repair volumes and increasingly complex vehicles and machines, the challenges are becoming more critical. The information needed to make better decisions is often fragmented and spread across ERP systems, warehouse platforms, spreadsheets, images, documents, and phone conversations.
Intropy claims that its technology aggregates fragmented structured and unstructured information to automate decisions directly within a customer’s existing operations in an ERP rather than simply presenting recommendations for employees to review.
This includes dynamically adjusting inventory levels and pricing, managing obsolescence, allowing businesses to move from periodic, reactive reviews to proactive decisions that update continuously as market conditions change.
The company highlighted that by connecting directly with existing ERP and other operational systems, its parts-specific AI transforms fragmented information into decisions that can be executed automatically.
“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,” said YihKai Teh, co-founder and CTO.
Since its launch, Intropy reported that its technology has processed more than €8.7 billion ($10 billion) in parts demand. Its customers have achieved measurable improvements, including returns on investment of more than 10x.
The company plans to use this capital to accelerate product development, expand its engineering and machine learning teams, and establish a New York office as it grows its presence in the United States. The company will also continue expanding across Europe. It is hiring engineers and AI researchers in London and New York.
