VisioLab secures $11 million to expand its AI-driven iPad checkout solution.

      The camera-based self-checkout system developed by the Osnabrück startup can recognize food and beverages without barcodes in under 10 seconds. It is installed at 43 sales points in the Orlando Magic's NBA arena and at roughly a third of German university campuses. The Series A funding round was spearheaded by eCAPITAL and Simon Capital.

      VisioLab, a German company specializing in AI-driven self-checkout solutions for the foodservice sector, has successfully raised $11 million in a Series A financing round led by eCAPITAL and Simon Capital. Continuing supporters High-Tech Gründerfonds, APX (the joint fund from Axel Springer and Porsche), and the family office zwei.7 also contributed to this round.

      Founded in Osnabrück in 2019, the company plans to utilize the funds to speed up its international growth, expand its workforce from 25 to about 40 individuals, and establish a dedicated office in Boston, USA.

      The technology is intentionally designed to require minimal hardware. At a stadium concession stand or university cafeteria, customers simply place their food and drinks under a standard Apple iPad. AI technology identifies the items within seconds without the need for barcodes, specialized scanning tools, or long lines, displaying the prices and accepting payments via a compact Bluetooth terminal.

      The entire setup weighs under 25 pounds and can be assembled in just 15 minutes. According to the company, training the AI to recognize a new menu of around 150 items takes about four minutes. The model operates as an app directly on the iPad, meaning that it doesn't require replacement of proprietary hardware when Apple updates its devices.

      The US market has been the leading driver of growth for VisioLab. The company currently has 43 systems operating in the Kia Center, home to the NBA's Orlando Magic, covering almost the entire arena. NFL teams such as the Atlanta Falcons and the Carolina Panthers have implemented the system in their stadiums, while Inter Miami has chosen VisioLab as a launch partner for its upcoming NU stadium.

      Currently, the US contributes approximately 50% of VisioLab’s revenue, with the company reporting an annual growth rate of over 1,000% in the region. While this figure reflects a relatively small absolute base, it highlights rapid adoption within the sports and entertainment sectors. The company processes around one million transactions each month across all its installations.

      The other half of VisioLab’s business is more conventional yet arguably more sustainable, focusing on corporate canteens, university cafeterias, and employee dining facilities at major German companies. Approximately one-third of German university campuses have adopted VisioLab technology through student services organizations.

      The system is also deployed in staff dining areas at DAX-listed corporations and in sectors such as banking, insurance, and automotive. Global catering firms like Compass Group and Aramark are partners in both Europe and the US, providing a distribution advantage that integrates VisioLab into venues these companies already manage without the need for VisioLab to independently acquire each site.

      The funding will facilitate market entry into Australia, New Zealand, Austria, the Netherlands, and the United Kingdom. Iwo Gernemann, co-founder and president, will spearhead the US expansion from Boston.

      New executives from Klarna, SumUp, and Google are being recruited, and around 15 positions are currently available in market entry in Boston and engineering roles in Germany.

      The foodservice checkout market presents a genuine challenge, characterized by high volume, time sensitivity, and inadequate service from traditional barcode scanning, which can falter when staff must manage hundreds of diverse menu items and custom orders. VisioLab's vision-based approach avoids the barcode issue but presents its own set of challenges, including the need for the AI to swiftly differentiate between visually similar items, manage partially obscured products, and maintain accuracy under varying lighting conditions—from brightly lit corporate cafeterias to dimly lit indoor arena concourses.