Oreta, a Managed Service Provider, delivers a wide range of network reports for monthly reviews, capacity planning, and performance analysis. These reports were traditionally created by manually extracting and consolidating data from various PDFs and sources—a time-consuming and resource-heavy processes. This manual workflow was increasingly unsustainable due to growing data volumes and the need for faster, more accurate insights.
Generating network visibility reports each month and quarter required consolidating fragmented data from multiple PDFs. This process posed numerous challenges: data was scattered and inconsistent, requiring meticulous manual extraction. Creating visualisations and summarising findings added further strain, demanding extra tools and time. Filtering relevant information and handling images introduced further complexity, with resizing, formatting, and annotating tasks prone to inconsistencies. These steps not only delayed reporting but also diverted resources from strategic initiatives, making the process inefficient and unscalable as data demands increased.
To modernise and streamline this process, Oreta implemented an AI-driven, automated reporting solution. Using Azure Document Intelligence, the system extracted structured data from PDFs. A custom module detected key headings and visuals, while Python libraries like Pandas and Seaborn structured the data and created visualisations. Azure OpenAI was used to generate concise summaries, adding contextual insights. All elements—data, visuals, and text—were compiled into a formatted Word document using an automated pipeline. This robust solution leveraged Azure, OpenAI, and Python tools to deliver accurate, polished reports with minimal manual intervention. As a result, Oreta now produces consistent, scalable reports that meet growing demands without compromising quality.
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