Snowflake (NYSE: SNOW) has announced new Energy Solutions, an offering designed for the energy sector that combines Snowflake’s data governance capabilities, partner-developed solutions, and industry-specific datasets. This initiative aims to assist power, utilities, and oil and gas companies in establishing a secure data foundation for AI by integrating data across IT, OT, and IoT systems, thereby modernizing infrastructure, improving efficiency, and supporting a transition to a more reliable and lower-carbon future.
Organizations such as ExxonMobil, Expand Energy, IGS Energy, Powerex, PG&E, Siemens, and Sunrun are currently utilizing Snowflake to secure critical infrastructure, enhance operational resilience, and manage volatile markets with real-time insights. The launch of Energy Solutions also follows Snowflake’s new partnership with SAP, which enables energy companies to integrate SAP finance and supply chain data with operational and field data on Snowflake. This integration ensures that insights derived from both business and operational systems can directly inform grid operations, asset planning, and commercial performance.
To further support its customers, Snowflake is introducing over 30 new partner-built solutions that operate natively on the AI Data Cloud. These solutions are designed to address various critical energy use cases, including grid planning, asset health, and operational forecasting.
CARTO, for instance, is delivering new cloud-native spatial analytics built directly on Snowflake. This allows energy companies to conduct geospatial analysis and create interactive maps without transferring data between systems, embedding spatial intelligence into existing Snowflake workflows to better understand assets, infrastructure, and geographic risks in daily operational decisions.
Itron, a global utility technology provider, is introducing an advanced Grid Planning solution developed on Snowflake. This solution aids utilities in managing the complexities of modern grids, featuring an industry-leading 8,760-hour power flow analysis. It can model grid performance years into the future at highly granular levels, delivering results in hours rather than months, which allows utilities to plan infrastructure more accurately, avoid unnecessary costs, and enhance long-term reliability.
Siemens, a global technology company, is highlighting its joint Siemens Industrial Edge integration with Snowflake. This integration allows energy and industrial companies to securely transfer data from decentralized industrial assets into Snowflake for advanced analytics and AI. Building on this, Siemens is introducing new analytical capabilities that enable teams to interact with operational data using natural language, providing faster insights into performance, maintenance, and operational issues. These combined capabilities help energy companies improve reliability, reduce costs, and make more informed decisions across complex, distributed operations.
Fred Cohagan, Global Head of Energy at Snowflake, stated, “Data is the control plane for the future of energy. Whether it’s keeping the grid secure, protecting critical assets, or balancing supply and demand in volatile markets, energy companies need a trusted data foundation that can activate AI everywhere.” He added that Snowflake is assisting energy leaders in modernizing data management and harnessing AI to make insights accessible, allowing anyone, not just data scientists, to act on intelligence in real time. This approach aims to help organizations optimize existing assets and achieve stronger sustainability and shareholder outcomes.
Snowflake Intelligence allows both technical and non-technical employees, from field engineers to analysts, to use natural language to obtain trusted answers in seconds. This capability aims to make decision-making accessible across organizations.
Abhay Gupta, Founder and CEO of Bidgely, noted that combining Bidgely’s vertical AI with Snowflake’s data and AI platform makes insights immediately accessible through natural language. This helps utilities understand consumption patterns, customer behavior, and distributed energy impacts, leading to faster, more informed decisions.
Alex Read, Senior Enterprise Product Manager – Data at EDF, commented that building their Intelligent Customer Engine on Snowflake has unified sensitive data securely and accelerated the conversion of insights into action, from improving energy efficiency to identifying vulnerable customers and delivering personalized support.
Justin McCammon, VP of Engineering at EnergyHub, stated that Snowflake provides the low-latency telemetry, accurate forecasts, and reliable performance essential for Virtual Power Plants (VPPs) to achieve parity with traditional infrastructure. The goal is to provide utility clients with the data-driven confidence to integrate VPPs into core grid planning.
John Christ, Chief Information Officer at Expand Energy Corporation, noted that their data platform built on Snowflake provides a single, trusted view of operations across business and field systems. He highlighted that automating monitoring, streamlining M&A integrations, and applying machine learning through Snowpark reduces complexity and saves thousands of hours annually.
Dan Shah, Product Manager at IGS Energy, indicated that Snowflake simplifies the process of building and running AI models, reducing costs and accelerating insights without compromising accuracy. This simplicity enables their team to focus on customer experiences and progress towards a sustainable future.
David Leach, Senior Vice President and Chief Data & Analytics Officer at PG&E, mentioned that meeting customer expectations for affordable and reliable energy requires simplifying their data landscape and enabling intelligence across the business. He explained that Snowflake helps consolidate siloed legacy environments, govern sensitive regulatory and operational data, and deliver timely analytics to teams in the field and control center, supporting service reliability and affordability.
Ian Mathieson, Director of Data Systems and Application Development at Powerex, stated that migrating from legacy systems to Snowflake provides the speed and scalability to power AI-driven forecasting and LLM-powered market insights, enhancing decision-making and trading performance.
Horst J. Kayser, CEO Factory Automation at Siemens, noted that solutions combining Siemens Industrial Edge with Snowflake offerings help unify decades of operational data in a trusted, secure, and scalable manner. This empowers energy industry customers to manage decentralized assets, predict equipment failures, and optimize energy production, which is crucial for navigating sustainable energy generation complexities.
Rohit Ayyagari, Vice President of Enterprise Technology at Sunrun, affirmed that Snowflake provides the scalable foundation powering analytics and innovation across their business, reducing latency, improving accuracy, and enabling faster insights for over 7,500 users.
