The global spare parts industry is enormous, fragmented, and still heavily reliant on spreadsheets. Intropy, a London-based AI startup founded in 2024, is betting that's about to change — and investors are backing that thesis with $11 million in fresh capital.

The Round

Intropy has closed a seed round led by Felix Capital, with participation from Quiet Capital and existing backers General Catalyst and Firstminute Capital. General Catalyst had previously led an undisclosed pre-seed round. The new capital will go toward accelerating product development, growing the team, and establishing a New York office as Intropy makes its push into the US market.

Who Built It and Why

The company was founded by YihKai Teh (CTO) and Franziska Kirschner, both former researchers at Tractable, the UK-based AI insurtech that built machine learning tools for insurance claims. Their background in applied AI for complex, data-heavy industries clearly informs Intropy's approach.

The problem they're solving is real and underserved. Spare parts businesses — distributors, manufacturers, and recyclers — operate across a maze of product data, demand signals, and pricing variables. Most still rely on periodic manual reviews and legacy ERP systems that can't adapt quickly to market shifts.

What Intropy Actually Does

Intropy's platform automates inventory, pricing, and operational decisions for spare parts businesses. A few things set its approach apart:

  • It aggregates fragmented structured and unstructured data from across a customer's operations
  • It integrates directly into existing ERP systems, automating decisions rather than just surfacing recommendations for humans to review
  • It enables a shift from periodic, reactive reviews to decisions that update continuously as market conditions evolve

That last point matters. Traditional software tells you what happened; Intropy is designed to act on what's happening now.

"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." — YihKai Teh, Co-founder and CTO, Intropy

Early Traction

Since launching, Intropy says its technology has processed more than $10 billion in spare parts demand — a striking figure for a company less than two years old. The automotive sector alone sees an estimated $4 billion in spare parts transacted every day, and that's before accounting for aerospace, industrial equipment, and the emerging robotics supply chain Teh references in his quote.

Why This Matters

For founders and operators in adjacent verticals, Intropy is a useful case study in a specific kind of AI opportunity: industries where the data exists, the stakes are high, and the existing tooling is genuinely bad. Spare parts businesses aren't lacking information — they're drowning in it, with no coherent layer to turn it into action.

The ERP integration angle is also strategically smart. Rather than asking customers to replace their core systems, Intropy slots in as an intelligence layer on top of infrastructure that's already entrenched. It's a faster path to adoption and a stronger moat once embedded.

The broader vertical AI-for-operations space is getting crowded, with startups targeting procurement, logistics, and supply chain across dozens of industry niches. But spare parts specifically — with its complexity around fitment, condition, demand forecasting, and pricing — has seen relatively little focused AI investment. Intropy is moving to claim that ground early.