Aug 7, 2026

AI for spare parts startup Intropy raises $11M

Intropy will use the funds to speed up product development, expand its team, and set up a New York office. A London-based AI for…

Intropy will use the funds to speed up product development, expand its team, and set up a New York office.

A London-based AI for spare parts startup has raised $11m in new funding, as it targets US expansion. Intropy has raised a seed round from lead investor Felix Capital, with participation from Quiet Capital and existing investors General Catalyst and Firstminute Capital. General Catalyst led the pre-seed investment for an undisclosed amount.

Founded in 2024 by two former researchers at UK AI insurtech Tractable, Intropy automates inventory, pricing and other key decisions for spare parts businesses. It uses AI to help distributors, manufacturers, and recyclers speed up their decision-making, replacing spreadsheets and outdated legacy software and manual systems.

Intropy’s technology aggregates fragmented structured and unstructured data, automating decisions directly within a customer’s existing operations in an ERP (enterprise resource planning) system rather than presenting recommendations for employees to review. 

It says it helps businesses move from periodic, reactive reviews to proactive decisions that update continuously as market conditions change. In the automotive industry alone, more than $4bn in spare parts are estimated to be transacted every day.

Since its launch, Intropy’s technology has processed more than $10 billion in spare parts demand, the startup, which was founded by YihKai Teh and Franziska Kirschner, said.

It says it will use the funds to speed up product development, expand its team, and set up a New York office.

Teh, co-founder and CTO, said: “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.”

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