AMMP launches AI coworker for renewable energy asset managers
AMMP introduces Ray, an AI coworker designed to automate routine tasks for renewable energy asset managers handling expanding portfolios across multiple sites and systems.
AMMP, a data platform for renewable energy, has launched Ray, an AI coworker aimed at assisting asset management teams. Ray integrates directly into existing tools like Slack, Microsoft Teams, and AMMP OS to monitor solar, wind, and battery portfolios. It proactively identifies issues, explains their causes, and drafts necessary reports, claims, and decisions without requiring manual intervention. The goal is to reduce the growing workload on asset managers overseeing increasingly large and complex renewable energy portfolios.
Renewable energy portfolios are expanding rapidly, often spanning hundreds of sites across multiple continents, each with distinct contracts and data systems. Despite the availability of monitoring tools, much of the follow-up work—such as performance reviews, contract compliance checks, and investor reporting—remains manual. Ray is designed to bridge this gap by automating these repetitive tasks, allowing teams to focus on higher-value activities while ensuring timely and accurate responses to operational issues.
AMMP’s strategy shifts the platform from a monitoring tool to an AI partner for asset management. Ray operates autonomously within the tools teams already use, flagging problems, coordinating responses, and completing tasks without waiting for prompts. This approach aims to address the challenge of doing more with limited resources, particularly as the energy transition accelerates and asset management teams face increasing demands.
Svet Bajekov, CEO and Co-Founder of AMMP, emphasized the need for AI to support asset management teams in managing renewable energy portfolios more efficiently. Ray represents the first step in this strategy, functioning as a coworker that immediately takes on real work. Bajekov highlighted the importance of using trusted data and ensuring safe, reliable AI integration to meet the demands of the energy transition.