Visual spare parts search for mechanical engineering





    Imagine this: Damaged machine parts in industrial manufacturing plants can result in millions of euros in downtime costs per part. It can take days for suppliers to identify, order, and deliver these parts. Three young people from the Baden-Württemberg and Bayern regions got to thinking: Is there a way to streamline this process and increase productivity?

    It was for this reason that Synthavo was born. Based in Stuttgart, the well-known production city in Germany, Synthavo, a team of three experts and enthusiasts from mechanical engineering, computer science and business administration was founded. 

    With a great passion for artificial intelligence and a sensitivity to current trends, Sebastian, Benedict, and Alexander, decided to set up this company. They want to provide products and after-sales services to small and medium-sized mechanical engineering companies and automation component suppliers in the fields of (process) automation, manufacturing, and construction engineering. 

    How does it work? Synthavo has developed an API for machine part recognition based on artificial intelligence and cameras. By taking pictures, spare parts can be recognized in seconds. With this technology, machine downtime at manufacturing sites can be significantly reduced, after-sales revenues of mechanical engineering OEMs and parts suppliers can be increased, and labor costs can be reduced. 

    However, this fledgling sapling faces its first critical moment. From the very beginning, the three founders encountered problems from three aspects: refinement of the target customer base, technical optimization, and investment. They first validated the AI idea via prototypes, tests, and customer interviews to overcome these problems. After confirming that the concept was feasible, they decided to join the KI-Garage Network Accelerator with a great visions of the future. We look forward to their success!

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