Success Story · Artificial Intelligence

AI-Driven Automation of Internal Reporting in the Energy Sector


  • Client: A multinational energy-sector company operating in several European countries, responsible for the generation, distribution, and retail of energy. The company handled hundreds of internal reports every month.

  • Challenge: The company produced more than 350 internal reports per month covering areas such as energy production, facility maintenance, regulatory compliance, operational performance, financial analysis, and environmental reporting.

    Producing these reports was largely manual: the leads of each department gathered data from multiple sources (SAP, Excel, internal databases, SCADA platforms), processed it, generated charts, and wrote up conclusions. This process consumed more than 1,200 working hours per month spread across different teams, generated frequent human errors, and caused delays that affected decision-making.

    In addition, the lack of standardization across departments meant that reports varied widely in format, metrics, and level of detail, making it difficult for management to get a global view.

  • BePart Innova Solution: We implemented a reporting automation platform powered by Artificial Intelligence:

    Unified data connectors: We integrated all data sources (SAP, SCADA, Excel, SQL databases, internal APIs) into a centralized data lake, eliminating manual data gathering.

    Automatic generation engine: We developed a system that automatically generates the reports in a standard format, including tables, charts, and KPIs, from the ingested data. Reports are scheduled to be generated at the required frequency (daily, weekly, monthly).

    AI-powered analysis: We incorporated natural language processing (NLP) models that automatically write the executive summaries and conclusions of each report, detecting anomalies, trends, and deviations from previous periods.

    Reporting portal: We built a web portal where each user can view, download, and share their reports, with role- and department-based access control.

  • Results:

    85% reduction in preparation time: From 1,200 hours per month to fewer than 180, freeing up teams for strategic analysis tasks.

    Elimination of human errors: Automating the data process eliminated the transcription and calculation errors that had affected 12% of previous reports.

    Full standardization: All departments now produce reports with the same format, metrics, and level of detail, making comparison and executive-level decision-making easier.

    Real-time reporting: Management went from receiving reports 5-7 days late to having up-to-the-minute data on demand.

  • TECHNOLOGIES

    NLP / Generative AI


    Centralized Data Lake


    SAP / SCADA Connectors


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