CUT RETAIL LOSSES
«Partnering with NtechLab introduced flawless facial recognition technology into our software. Every step of the way, we felt the support of top-notch professionals. Today, retail chains prevent and solve dozens of crimes every day. On average, retail chains see a 2−3% annual reduction in their losses, while it only takes 2−4 months to receive a full return on the cost of acquiring the software. Integrator costs for acquiring a FindFace license are usually recouped after the first deal».
THE PROJECT IN NUMBERS
The Stop Shoplifter Enterprise Information System (EIS) powered by NtechLab’s facial recognition solution searches a database of some 10,000 offenders and analyzes video stream data in under 2 seconds. FindFace’s unique algorithm at the heart of NtechLab’s solution makes facial recognition nearly 100% accurate. An unlimited number of cameras can be connected to perform facial recognition on video streams. These are the unique selling points that make this software so effective. As a result, the technology has seen an increased demand in retail, where theft is especially high.
Large grocery and perfume retailers in Yekaterinburg were the first clients to embrace the solution. The results are impressive: theft attempts are prevented every day while over 15 repeat offenders are handed over to the police each month. Theft cases that previously went unsolved due to not being able to find or identify the offenders are now being successfully investigated. Shortly after launching the program, customers decided to scale the project.
The Urals-based company BIT has offered software and consulting services for over 5 years, specializing in security issues.
In their efforts to create their own facial recognition software product for retailers, BIT employees spent a long time testing various algorithms before selecting a partner that would oversee the facial biometrics.
The company has partnered with NtechLab since 2016.
1. To create a security software solution for retailers.
2. To have the software process video feeds from multiple video cameras, to quickly and accurately detect offenders, and maintain high recognition accuracy in difficult conditions. To implement the software using existing equipment at retail centers.
3. To offer a solution that requires only minimal restructuring of the customer’s current business processes.
The approach to meeting these objectives employed the FindFace Enterprise Server SDK.
BIT employees used it to create the Stop Shoplifter EIS software solution that, in addition to performing facial recognition and video archive searches, supports separate data storage for a number of retail chains.
The program also includes unified offender database search capabilities and the ability to trace and transmit information on any crime committed to the police.
TO A NEW LEVEL