SCATI

Video surveillance and security solutions using bleeding edge technology

SCATI is a manufacturer of video surveillance technology with a wide range of solutions focused on security, business intelligence and operations. With over 20 years of experience in the electronic security sector, they have established themselves as leaders in innovative IP video systems, specialists in offering intelligent integral solutions that adapt to large security projects and business processes. At the forefront of technology, they have a wide variety of solutions that guarantee the protection of any installation. A complete platform that encompasses surveillance cameras, recording servers, video analytics, business intelligence and operation software for control centres. It is designed to simplify video management at all levels, including deployment, operation and maintenance. Having undertaken numerous projects tailored to clients, certain solutions have become part of their portfolio to replicate a successful solution to meet similar needs in different sectors.
Sustainable
The commitment to sustainability is reflected tangibly in its corporate headquarters in Zaragoza. This is an energy efficient building with an architectural and constructive base designed to minimise the use of energy for air conditioning, allowing work under conditions of natural lighting in virtually all rooms through the elimination of opaque walls and the use of glass as an internal partition element. They also have policies for the treatment and recycling of waste generated.
Creative
The company has developed capacity management systems to guarantee the sanitary measures imposed on hospitality and catering as a consequence of COVID-19. With this system, both the managers of these establishments and their customers have real time knowledge of the level of occupancy of the facilities and can manage resources. SCATI has developed tools for the retail sector to link receipts to security cameras to prevent fraud and discrepancies. Similarly, they have applied deep learning technologies to measure the periods of greatest influx of customers in establishments, identify the busiest areas, and define average profiles to take decisions based on data and measure their effectiveness.