In the new retail era, Focal Systems uses AI to help offline supermarkets realize intelligence

With the gradual increase in labor costs and the development of new technologies such as mobile payment, more and more consumers are beginning to choose cost-effective ways to meet their shopping needs. At the same time, this environment has also brought unprecedented competitive pressure and difficulties to retailers.

Focal Systems, founded in June 2015 and headquartered in California, USA, is a technology company that provides artificial intelligence systems for large retail stores. Its core is to enable retail stores to manage and obtain relevant product and customer information by providing Focal tablets and independently developed applications on shopping carts, while also providing related navigation and positioning and other service functions to enable consumers to have a better shopping experience. . It is understood that Focal Systems was selected for YC in November 2015 and received US$120,000 in seed investment. Recently, it received US$2.5 million in investment from Zetta Venture Partners and SoftTech VC in May last year.

Judging from the current solution, in the hardware part, Focal Systems connects a universal Android tablet to the shopping cart, uses side cameras to capture images of the aisles and identify which items are out of stock, and there are two separate cameras to capture consumers For the items placed in the shopping cart, the data collected by these cameras are analyzed using computer vision and artificial intelligence related technologies to determine the items placed in the shopping cart, total and other related information and display them simultaneously on the tablet.

Overall, such a solution brings certain conveniences to retailers, advertisers, and consumers. For retailers, real-time monitoring of out-of-stock situations can be achieved by detecting inventory on shelves through tablets; for advertisers, an average increase of 8.8% can be achieved by providing promotions and other advertisements on tablets; and for consumers, Convenient and fast transactions can be achieved through accurate in-store navigation and product transaction search and voice interaction functions; in addition, Focal Systems is expected to launch "Just-Throw-It-In-The-Cart" technology in the third quarter of 2017 to achieve automatic Bill, please. This way, consumers can skip the checkout counter and have a better shopping experience.

According to public information, Focal Systems is working with major product companies such as Anheuser-Busch to charge retailers a monthly service fee of US$2,500 and split the advertising 50-50. It has been proven that it can help stores increase 100,000 per month. USD income. In the future, companies can also monetize data collected in stores.

When it comes to competition, most direct competitors will think of Amazon, but in fact many product companies and retailers do not want to cooperate with competitors. In contrast, Focal Systems is positioned as a neutral service provider. In addition, Chaubard also said that according to previous research, a Walmart store employs 238 people and has a monthly labor cost of US$572,000. This cost includes 24% salesperson manpower, 22% customer service, 11% scanning and 43% inventory. Focal Systems can reduce costs by approximately 57% by redeploying the entire process, which is a monthly saving of US$326,000. At present, typical domestic start-up companies such asNanjing Yimao, starting from smart shopping carts, we plan to build a DSP advertising platform for offline retail.

As for the team, it currently has 15 employees, most of whom are PhDs and masters from Stanford University from Apple, Google, and Facebook, specializing in the most advanced machine learning and computer vision research. Founder Francois Chaubard graduated from Stanford University and has extensive research in computer vision. He was also a researcher on Apple's secret project of deep learning; co-founder Adriano Quiroga is CTO, a researcher at Cornell University and studied for a doctorate at Stanford University. , is an expert in embedded systems, signal processing, and sensor networks.