Machine downtime costs up to €50,000 per hour in sectors such as automotive and logistics. To address this challenge, Synthavo, a Stuttgart-based startup, offers an AI-driven solution for automated spare part identification. By leveraging synthetic CAD data, the technology enables parts to be identified from a simple photo, eliminating the need for additional applications or complex integrations.
Founded in 2019 by Sebastian Stöcklmeier, Alexander Illg, and Benedict Lindner, Synthavo primarily targets the automotive, machine tools, and logistics industries, where downtime has a significant impact on production lines. The platform has demonstrated the ability to reduce spare part identification times by 60% on average, allowing manufacturers to resume operations faster.
Unlike traditional systems requiring manual mapping or third-party tools, Synthavo automates the process and provides an intuitive experience for technicians. “Our AI allows manufacturers to identify and order spare parts quickly, unlocking unprecedented levels of efficiency for the industrial sector,” says Sebastian Stöcklmeier, CEO of Synthavo.
With a team of 15 employees, Synthavo aims to reach 50 industrial clients by the end of 2025. The funds raised will be used to double its workforce across sales, engineering, and customer support departments, supporting its European expansion and preparing for entry into the U.S. market.
To fuel its growth, Synthavo secured €4 million in a Seed round led by Samaipata and Senovo.
