HAKOM Sees Rising Importance of Data Management in the Energy and Commodity Industry
Data management is becoming an increasingly critical topic in the energy and commodity sectors. But is this solely due to the integration of AI applications into business processes? How important is it to incorporate AI-driven tools into data management? Or is data management an independent area of business, separate from the influence of AI?
These are some of the questions I recently discussed with Stefan Komornyik, the CEO of HAKOM, a company renowned for its data management platform PowerTSM®, particularly for its strong capabilities in time series management and connectivity tools. Stefan highlighted that there is growing momentum for data management solutions, but not necessarily because of the proliferation of AI.
Many energy companies have long recognized the importance of general time series management, often developing bespoke, in-house solutions to meet their needs. However, as data volumes continue to grow, these legacy systems are proving to be inadequate. They struggle with performance issues, lack scalability, and are not designed for cloud-native environments. As a result, the industry is increasingly seeking standardized solutions with modern architectures, Stefan explained.
Another significant driver behind this trend is the shift towards building ecosystems of best-in-breed applications, rather than relying on a single monolithic ETRM/CTRM system to handle all aspects of energy and commodity trading. According to Stefan, one of HAKOM’s clients is using approximately 40 different tools, all related to energy trading and retail operations. These tools require a unified data foundation to ensure a consistent, reliable “single version of the truth.” And this is not a standalone example, it is a trend. This growing demand for interoperability and efficient data management seems to create a favorable market environment for companies like HAKOM.
When discussing HAKOM’s business development priorities, Stefan emphasized a focus on improving usability and connectivity over immediate AI application deployment. That said, AI remains a key element of HAKOM’s roadmap. Two flagship AI-driven projects include the development of the Advisor and Reporter tools, both leveraging large language model (LLM) technology.
The Co-Pilot Advisor aims to assist with training and coding support, while the Reporter is designed to enable users to generate data extracts and build reports using natural language commands. These innovations demonstrate HAKOM’s commitment to integrating AI, but balancing immediate market needs with forward-looking technological advancements, as Stefan explained.
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