“We're on a mission to deliver the best AI based analytics technology experience to consumers of electricity, in the commercial real estate(CRE) market”
Our energy analytics software offers predictive capabilities to simulate the customer environment by analyzing the consumption data, trends & patterns, user behavior, anomalies causing inefficiencies, and make accurate forecasting on the future outcomes. The platform offers tools to forecast future energy demand scenarios and estimating related energy costs for CFOs/CXOs. In addition, we offer game mechanics to engage and influence end-consumers for driving behavioral change towards energy sustainability.
"The zero-carbon energy is not a viable supply yet to meet the demand."
Economic expansion and rapid urbanization in India is expected to five-fold increase the commercial building stock to several billion square meters in the coming decade. While zero-carbon energy sources like solar, wind are still evolving, it is not expected to address the increasing energy demand in the near future.
Today, consumers are not measuring, monitoring and pivoting their energy consumption and thus unaware of their behaviors and inefficiencies resulting in significant unneeded energy costs. They cannot predict faults and anomalies in advance and do reactive maintenance when a breakdown happens resulting in increased costs for maintenance. Since there are no intelligent and predictive systems, consumers are not able to make informed decisions on energy sustainability. Deploying intelligent, reliable and affordable technology for energy demand management and sustainability is the need of the hour.
"Data-driven, Scientific, Sustainable outcomes"
At Turiyatree, we aspire to deliver the best AI based Analytics technology experience to consumers of electricity, in the CRE market. By leveraging Analytics technology, commercial businesses can now measure, pivot and pinpoint their energy consumption trends, predict future demand and conserve energy through real-time actionable intelligence. Machine learning algorithms can predict faults and anomalies to recommend preventive maintenance tasks for decreasing maintenance costs. We help you to make informed decisions for energy sustainability resulting in improved ROI.