The energy storage market is undergoing a seismic transformation, driven by policy breakthroughs and the accelerating demand for resilient, efficient energy systems. With a projected compound annual growth rate of 29% for utility-scale systems through 2030,Battery Energy Storage Systems or BESS have become an essential pillar of the global energy transition.

As BESS deployments accelerate, operators face mounting operational challenges. The complex interplay of batteries,inverters, transformers, and switchgear creates inherent vulnerabilities in system performance. Current monitoring approaches often miss early warning signs of degradation, leading to unexpected downtime and shortened component lifespans.The industry needs a shift from reactive maintenance to predictive insights.

We are developing an analytics platform to address these fundamental challenges in BESS operations. Our approach leverages advanced machine learning techniques to process real-time performance data across critical subsystems. By identifying subtle patterns that precede component degradation, we aim to provide operators with actionable insights before issues impact system performance.

Our development roadmap focuses on key operational priorities: early detection of performance anomalies, automated root cause analysis, and optimization of maintenance schedules. We are building our solution in close consultation with industry experts and potential users to ensure it addresses real-world operational needs.

We are currently seeking partners for our initial pilot program. If you operate BESS assets and are interested in shaping the future of predictive maintenance, we would welcome a conversation about potential collaboration.