Cosmo Oil and GE Vernova Sign MoU Aimed at Enhancing Refinery Asset Maintenance ~Advancing Next-Generation Asset Maintenance Utilizing Generative AI and Data Analysis~

October 8, 2026

Cosmo Oil Co., Ltd.

Cosmo Oil Co., Ltd. (hereafter, “Cosmo Oil”) and GE Vernova Software Japan Co., Ltd. (hereafter, “GE Vernova”) have signed a Memorandum of Understanding (MoU) concerning GE Vernova’s asset performance management (APM¹) software beta program². Under the MoU, Cosmo Oil will gain early access to new APM software features to be developed by GE Vernova and conduct validation testing in real-world refinery maintenance. By reflecting the needs of Cosmo Oil's refineries and the validation findings in the development of the new features, the two companies seek to enhance asset maintenance, increase operational efficiency, and further boost asset reliability and safety.

1. Collaboration Background and Features to be Validated

Refineries must accurately monitor asset conditions and operational risks while enhancing maintenance operations with limited resources in order to continue operating aging equipment safely and reliably. Cosmo Oil is promoting digital transformation (DX) and working to advance asset maintenance utilizing artificial intelligence (AI) and other digital technologies to further strengthen the foundation underpinning safe refinery operations and stable petroleum product supply.

GE Vernova’s APM software combines data on asset operating status and operational risks with expert knowledge to support the monitoring of asset conditions and maintenance-related decision-making. Under this beta program, the parties will focus on validating the following new features.

(1) Health 2.0

This feature assesses and quantifies asset conditions from the perspective of operational risks and helps prioritize maintenance responses. Cosmo Oil will leverage this feature to enhance condition-based maintenance (CBM), clarify maintenance priorities, make effective use of resources, and improve operational efficiency.

(2) Analytics Builder

This feature enables Cosmo Oil’s data scientists, engineers, and operators to build, validate, and operate custom analytical models linked to GE Vernova’s APM software monitoring and workflows. By streamlining the development of analytical models and strengthening predictive maintenance capabilities, Cosmo Oil aims to further enhance asset maintenance.

(3) Generative AI Agent

This feature leverages generative AI built into GE Vernova’s industrial Software as a Service (SaaS) platform to support the collection and analysis of asset maintenance-related information, as well as decision-making.

◾️Key Agents to be Utilized

・Strategy Agent:
The Strategy Agent supports the creation and standardization of failure mode and effects analysis (FMEA) and asset strategy templates.

・Natural Language Query (NLQ) Agent:
The Natural Language Query (NLQ) Agent enables queries of APM data using natural language, streamlining information retrieval.

・Document Intelligence Agent:
The Document Intelligence Agent imports inspection reports, organizes and visualizes key points and anomalies, and supports the consideration of response options.

・Inspection Agent:
The Inspection Agent extracts and summarizes inspection data, supporting increased document analysis efficiency and improvements in inspection operations.

2. Future Policy

The Cosmo Energy Group has identified “bolstering our financial and operational strength through productivity improvements and the comprehensive use of AI and other digital technologies” as a priority initiative under its Eighth Consolidated Medium-Term Management Plan. The initiatives under this MOU are positioned as opportunities to verify the effectiveness of APM software features leveraging the latest digital technologies for addressing frontline maintenance challenges. Cosmo Oil will work closely with GE Vernova’s engineers to improve and enhance the features by providing feedback on on-site needs and validation findings.

The Cosmo Energy Group will continue to proactively utilize AI and other digital technologies to increase refinery asset reliability and safety while ensuring operational excellence, thereby contributing to safe and stable energy supply.