Intropy, an AI-native platform automating inventory, pricing, and obsolescence decisions for spare parts businesses, has raised $11 million in seed financing. The round, led by Felix Capital with participation from Quiet Capital, General Catalyst, and firstminute capital, was announced July 31, 2026. The company targets a $4 billion-per-day automotive spare parts market that still runs largely on spreadsheets and decades-old software.
The spare parts problem
Spare parts keep vehicles on the road, machinery operating, and critical infrastructure functioning. Yet the industry's most important decisions - how much stock to hold, where to place it, when to adjust a price, which inventory is becoming obsolete - still depend on manual reviews of hundreds of thousands of individual SKUs. Teams pull fragmented information from ERP systems, warehouse platforms, spreadsheets, images, documents, and phone conversations.
These challenges are intensifying. Tariffs, rising fuel and operating costs, uncertain repair volumes, and increasingly complex vehicles and machines put more pressure on operations teams that lack the tools to respond in real time.
How Intropy works
"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," said Franziska Kirschner, co-founder and CEO. "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."
Intropy's technology aggregates structured and unstructured information and executes decisions directly within a customer's existing ERP, rather than presenting recommendations for employees to review. The platform dynamically adjusts inventory levels and pricing, manages obsolescence, and shifts businesses from periodic, reactive reviews to continuous, proactive decisions that update as market conditions change.
Since launch, the platform has processed more than $10 billion in parts demand. Customers have reported returns on investment exceeding 10x. The company was founded in London in 2024 by Kirschner, a University of Oxford-trained physicist whose research appeared in Nature, and YihKai Teh, an AI academic from University College London. Both previously worked at Tractable, where they became inventors on more than 10 patents applying AI to the spare parts sector.
"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," said YihKai Teh, co-founder and CTO. "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."
The funding and what's next
Intropy will use the $11 million to accelerate product development, expand its engineering and machine learning teams, and open a New York office to grow its U.S. presence. The company also plans to continue expanding across Europe. Open roles in London and New York are listed at intropy.ai/careers.
Fabian Burnett Small, investor at Felix Capital, said the firm sees AI fundamentally transforming 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."
Why this matters for operations
For operations teams managing spare parts, the shift from manual SKU-by-SKU reviews to automated, continuous decision-making changes the nature of the work. Instead of reacting to stockouts or pricing gaps after the fact, systems like Intropy's adjust in real time. The result is less working capital tied up in excess inventory, fewer obsolete parts written off, and faster repair turnaround for customers.
Operations professionals who understand how AI-driven inventory and pricing tools integrate with existing ERP systems will be better positioned as these technologies spread beyond early adopters. Intropy's approach - embedding decisions directly into operational systems rather than adding another analytics layer - signals where industrial AI is headed: toward autonomous execution, not just recommendations.
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