BeMyEye Acquires Computer Vision Firm Metaliquid

BeMyEye-acquires-Computer-Vision-company-Metaliquid

BeMyEye’s clients will now obtain, in real-time, corrective actions from complex retail scenes at scale

BeMyEye has announced the acquisition of Metaliquid, a Computer Vision company specialising in audio and video analysis based on deep-learning technology.

With the integration of Metaliquid’s cutting edge Computer Vision technology, BeMyEye’s clients will now obtain, in real-time, corrective actions from complex retail scenes at scale. Metaliquid’s AI technology dramatically improves the performance and ROI of field teams at a time when CPGs are under significant pressure to improve efficiency across the board.

Metaliquid has developed an innovative deep-learning solution designed explicitly for extracting descriptive, time-coded metadata from audio, image, and video contents in real-time. Leveraging proprietary deep-learning frameworks and neural network architectures, Metaliquid’s solution is proven to deliver production-grade AI applications with exceptional accuracy levels to a broad range of industries including media and broadcasting, retail and security.

“Most of our clients already experience up to 20% improvements in key store execution metrics like Assortment Compliance and Share of Shelf, which result in double-digit revenue growth. Leveraging Metaliquid’s real-time Computer Vision capabilities will take our clients’ in-store execution to the next level, significantly boosting their market share. We’ve worked with Metaliquid for over 18 months and have been impressed with the way their tech and capabilities have improved success in-store,” Luca Pagano, CEO, BeMyEye.

Simone Bronzin, formerly CEO of Metaliquid and now CTO of BeMyEye, said: “We are very excited to join a company with such a great product and portfolio of clients like BeMyEye. Moreover, BeMyEye’s crowd can be a game-changer in Computer Vision. It enables the labelling and annotation of datasets on an enormous scale, thus reducing the time and cost of deployment on an AI-based solution.”