Transforming Raw Data into Polished Reports: An LLM-Powered Solution for Customizing Template-Based PDFs

Author(s)	Sambari Pranathi, Toluva Akshita, Mallak Vaishnavi, Mummadi Ramachandra, Dheeraj Sundaragiri
Country	India
Abstract	Extracting insights from raw data and presenting them in visually appealing reports often requires tedious manual effort. This work introduces a powerful solution leveraging large language models (LLMs) to streamline the process of generating customized, template based PDFs directly from raw data. Our LLM-powered approach automates data analysis, report writing, and template customization, eliminating the need for manual intervention. By integrating seamlessly with existing data sources and reporting templates, this solution empowers users to generate professional reports instantly, saving valuable time and resources. We demonstrate the effectiveness of our approach through real-world examples, showcasing the ability to transform raw data into polished reports with unmatched efficiency and accuracy.
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 6, Issue 3, May-June 2024
Published On	2024-05-04
DOI	https://doi.org/10.36948/ijfmr.2024.v06i03.18590

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International Journal For Multidisciplinary Research