Tylor McTaggart

Focal Systems

Focal Systems' platform helps retailers cut shelf scanning cost in half by switching from manual to automated shelf scans. The solution is based on low cost, discrete shelf cameras, a sophisticated computer vision model and a cloud-based machine learning platform that is tuned for complex retail environments. By providing automated, real-time insight into on-shelf product availability, retailers can repurpose store personnel to focus on customer experience and other higher value tasks. In addition, the real time data captured by the shelf cameras feeds into Focal Systems' AI engine which can help automate and optimize product availability and merchandising decisions. These optimizations have proven to save up to 50% on manual shelf scanning cost and significantly improve in-store customer experience via higher product availability which generates a 3-5% increase in sales compared to baseline stores. Focal Systems' platform is deployable at scale and will provide impactful results from day one. It also integrates with existing retail systems and applications to enable additional cost savings and insights from its real-time product availability and analysis. Focal Systems' shelf cams are deployed at scale with proven results at several major global retailers and every day process more than 10M shelf scan images.