IBM Acquires Prescinto for Renewable Energy Asset Performance Management

Today, IBM is announcing it has acquired Prescinto, a leading provider of asset performance management (APM) software-as-a-service (SaaS) for renewables. Prescinto’s capabilities leverage AI to enable advanced monitoring, analytics, and automation to streamline renewable energy operations and manage clean energy and storage assets.

Organizations are increasingly turning to alternative energy sources like wind, solar, and energy storage to help reduce emissions and lower energy costs. Yet, it can be daunting to effectively manage and maximize the performance of high-tech devices like turbines, solar panels and inverters, which generate power from renewable energy assets. In addition, environmental factors like weather and debris can contribute to reducing energy output, system effectiveness, and system uptime. According to Allied Market Research, the value of the global utilities asset management market is expected to grow from $4.3 billion in 2022 to $12.4 billion in 2031, with a CAGR of 11.3 percent.

The acquisition of Prescinto will enhance the capabilities of IBM Maximo Application Suite (MAS), IBM’s solution for asset lifecycle management. Moreover, it will further IBM’s leadership in the energy and utility space, an industry undergoing significant transformation and seeking solutions to manage and optimize wind, solar, and other renewable energy storage assets. Water, natural gas, oil, nuclear, and other energy and utility enterprises globally already utilize IBM MAS.

Today, IBM MAS was recognized as a market leader in Enterprise Asset Management (EAM) by the independent research and advisory firm Verdantix, receiving top marks in the report “Green Quadrant: Enterprise Asset Management Software 2024.” Earlier this year, Verdantix also named IBM MAS a leader in Asset Performance Management (APM) in the report “Green Quadrant: Asset Performance Management Solutions 2024.” IBM is the only vendor to be named a leader in both the APM and EAM reports.

The acquisition will further enable IBM to support clients’ sustainability initiatives and net-zero goals, allowing users to track and monitor the performance of solar, wind and energy storage assets in near real-time; identify root causes for underperformance; and recommend actions to optimize generation.

For example, a solar power plant can become less efficient over time due to accumulated dirt and debris on its panels. Renewable APM software can use visual recognition capabilities to help monitor these assets, identify issues before they become critical, and prompt the necessary actions to restore optimal efficiency. This would allow for real-time tracking of panel performance, streamline required cleaning, and enable organizations’ prompt response before energy output decreases.

Prescinto, founded in 2016 and headquartered in Bangalore, India, works with and services global customers across 14 countries with 16 GigaWatts under management. Prescinto’s APM capabilities help organizations simplify operations and maintenance to maximize ROI. It offers robust capabilities including: data capture – employing open-source protocols and a data governance layer
monitoring features – for centralized visualization of assets with high-definition maps, real-time monitoring, and custom alerts
analysis – using AI to identify losses, visualize data trends, and offer actionable recommendations to increase performance
action prompts – facilitating efficient management and deployment of site teams to repair and maintain assets

IBM MAS is an integrated asset lifecycle management (ALM) solution for asset monitoring, management, predictive maintenance, and reliability that uses AI, IoT, and analytics to optimize performance, extend the life of assets, and reduce operational downtime and costs. According to the IDC, Worldwide Asset Life-Cycle Management Applications Market Share, (doc #US52190725, June 2024) report, IBM is ranked number 1 for 2023 market share in ALM with a share of 10.8 percent in 2023.

Learn more about Prescinto’s solution by visiting https://prescinto.ai.