Success Case | Automatic Oil Blending Scenario Selection with a Network of AI Agents
Global energy and chemical company committed to mobility and sustainability that develops its business on 5 continents, with a yearly turnover of 33 billion euros.
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The Challenge
The customer needed to simplify access to critical data and forecasting models at their refinery in the south of Spain. The challenge was to enable both technical and non-technical employees to easily retrieve and work with large volumes of complex information, such as sensor data, process methodologies, and regulatory documentation.
The Solution
Keepler built an AI agent system that cooperates to automate the process of forecasting blending scenarios. The agents interact with a wide range of data sources, integrating sensory data, advanced forecasting models, databases, and documentation on operational processes, regulatory standards, and work methodologies.
Business Impact
- Improved accessibility to critical refinery information for both technical and non-technical employees.
- Reduced the workload on staff who previously managed and retrieved this data manually.
- Enhanced operational efficiency and decision-making processes at the refinery.
Keepler is a full-stack analytics services company specialized in the design, construction, deployment and operation of advanced public cloud analytics custom-made solutions. We bring to the market the Data Product concept, which is a fully automated, public cloud services-based, tailored software that adds advanced analytics, data engineering, massive data processing, and monitoring features. In addition, we help our customers transition to using public cloud services securely and improve data governance to make the organization more data-centric.
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