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kWantera: Dealing Best Price on Energy with Analytics and Data Science
The growing conflict between the lack of transparency in the ‘rules of the game’ and ever-increasing amounts of freely available and relevant energy data has led to the energy buyers, sellers and consumers harvesting vast volumes of disparate data to make smarter decisions in real-time. “The challenge is the regulatory and competitive rules that have not kept pace with this reality. We help industrial and commercial customers in making real-time choices about the optimal time for buying, selling and consuming energy every day,” asserts Mark DeSantis, CEO, kWantera. Headquartered in Pittsburgh, PA, kWantera provides energy management software services to large commercial buildings, industrial manufacturers and various other business segments in order to mitigate their energy usability issues.kWantera’s platform is a continuous, real-time predictive analytic loop, drawing in huge amounts of varied real-time data. It is consumed by the real-time analysis algos which generate real-time and highly customized daily recommendations,” extols DeSantis. Furthermore, the recommendations inform the next analytic cycle, making kWantera a self-learning platform. “We rely on pattern-recognition concepts not unlike that used by Amazon and Google,” says DeSantis. kWantera relies on an intricate combination of advanced technologies. Its core technological lineage is machine learning and related pattern recognition technologies. Taking in vast amounts of real-time data, the company uses technologies like Hadoop, and develops additional proprietary technology in the form of ‘ensemble analytics’. The analytics allows kWantera to give accurate, precise and consistent daily recommendations to the customers. The company offers pricing service that uses all the publically available data to generate sensible buying and selling prices. “The trend for ‘deregulated’ wholesale markets will continue and benefit everyone. The smart deregulation equals efficient markets results in better price discovery –sensible daily energy prices,” asserts DeSantis.
The firm also renders its collective expertise ‘Energy Data Science’ that involves the commitment of ‘Energy Data Scientists’ in enhancing the discipline and insights needed to model electricity markets. Getting best possible energy price for industrial and commercial buyers on a daily basis, kWantera optimizes the time and pace of the energy consumption for the consumers. Consequently, it lowers the energy cost for the clients by five percent. “One could call it Six Sigma or maximally optimized energy purchasing and consumption. We’ve just entered the sell side and are helping renewable generators optimize their participation and their offering into the market,” reckons DeSantis.
“There are a lot of mid-sized and larger buyers, sellers, and consumers of energy, making daily energy choices without any real capability to know where a particular market is proceeding. The day-to-day business-end of energy utilization is a local and real- time phenomenon,” claims DeSantis. Marking on this, kWantera envisages being an outstanding outsourced price optimization service in the U.S. within three years. “Our customers have far more experience in energy markets than we do. But they still lack analytics capacity to make best decision. Reason that we succeed our competitors is our unique approach in the business of building or maintaining an energy data science platform. Therefore, we will continue doing the same for our clients so that they can concentrate on being the best steel, beer or paper company in the world,” concludes DeSantis.
kWantera’s platform is a continuous, real-time predictive analytic loop, drawing in huge amounts of varied real-time data that is consumed by the real-time analysis algos
“There are a lot of mid-sized and larger buyers, sellers, and consumers of energy, making daily energy choices without any real capability to know where a particular market is proceeding. The day-to-day business-end of energy utilization is a local and real- time phenomenon,” claims DeSantis. Marking on this, kWantera envisages being an outstanding outsourced price optimization service in the U.S. within three years. “Our customers have far more experience in energy markets than we do. But they still lack analytics capacity to make best decision. Reason that we succeed our competitors is our unique approach in the business of building or maintaining an energy data science platform. Therefore, we will continue doing the same for our clients so that they can concentrate on being the best steel, beer or paper company in the world,” concludes DeSantis.
