Energy Management Careers of a Major Bank Embrace AI for Building Systems
Across the energy management sector, the adoption of artificial intelligence models to monitor life support engineering systems in large facilities has delivered substantial savings. In a recent presentation at the Urban ESG congress in Moscow, Tatyana Zavyalova, senior vice president for ESG at Sberbank, highlighted that these advances have helped the bank reduce costs by approximately 600 million rubles over three years. The figure reflects a broad program to optimize energy use and maintain safe, reliable building operations through intelligent monitoring and automated control.
During the event, the bank disclosed plans to bring the Andromeda software and hardware complex to wider market adoption. At present, Sber reports that the Andromeda solution is installed across the bank’s extensive footprint, including about 3,000 offices and 200 administrative buildings. This scale underscores the system’s capacity to manage energy resources and automate routine technical tasks in diverse settings.
According to Zavyalova, the system is already being piloted in SberCity, a smart city initiative located in the Rublevo-Arkhangelskoye district just west of Moscow. Commercial replication of Andromeda has begun, and the bank anticipates entering a larger market soon, driven by demonstrable efficiency gains and predictable cost savings. The ongoing rollout reflects a strategy to leverage automated intelligence to streamline operations and deliver measurable returns on energy investments.
The Andromeda complex focuses on automating a range of technical processes that previously required manual oversight. Its capabilities extend to the accounting and management of energy resources, enabling precise tracking of electricity consumption at individual facilities. Beyond monitoring, the system supports staff in crisis scenarios by providing rapid, data-driven guidance and automated responses where appropriate.
In addition to basic consumption management, Andromeda is designed to identify price categories for electricity customers and to detect anomalies in fuel and energy utilization. By analyzing consumption patterns, the platform aims to reduce nighttime electricity use and lessen overall energy expenses through improved forecasting of peak load hours. The overarching aim is to deliver smarter, more resilient energy management for large organizations while maintaining high standards for safety and reliability across distributed sites.