SaaS Platform for Context-Aware PDF Summarization using Generative NLP
Prof. Dhanashri Londhe1, Jeevan Dhatbale2, Mohan Dinkar3, Anuj Dhole4, Sujal Dhavale5
1Prof. Dhanashri Londhe, Computer Engineering, Zeal college of Engineering and Research
2Jeevan Dhatbale, Computer Engineering, Zeal college of Engineering and Research
3Mohan Dinkar, Computer Engineering, Zeal college of Engineering and Research
4Anuj Dhole, Computer Engineering, Zeal college of Engineering and Research
5Sujal Dhavale, Computer Engineering, Zeal college of Engineering and Research
Abstract – The modern digital landscape is overwhelmed with lengthy, complex documentation, especially in professional, academic, and legal sectors, primarily existing in the Portable Document Format (PDF). The exponential growth of documents creates a significant information retrieval bottleneck, where professionals spend excessive time manually sifting through files to extract key context and critical data points. Existing summarization tools are often limited to simple text compression, failing to understand document structure, tables, figures, or the overall context of complex, multi-page PDFs, which leads to generic, non-actionable summaries. This deficiency necessitates a robust, intelligent, and scalable solution that moves beyond simple summarization to genuine document understanding. Our solution is a SaaS Platform for Context-Aware PDF Summarization with Document Intelligence using Generative NLP, designed to address this problem by offering an accessible, web-based service. The platform is engineered to first apply Document Intelligence techniques to analyze the PDF's layout, extract structured data from tables and figures, and understand the hierarchical flow of information. This comprehensive context is then fed to a Generative NLP model, specifically a fine-tuned open-source Transformer model from the Hugging Face ecosystem, ensuring specialized and cost-effective performance, instead of relying on generic commercial APIs. The core innovation lies in the 'context-aware' nature of the summarization, where the generated output is tailored to the document's structure and the user's implicit intent, producing highly relevant and accurate summaries and key insights.
Key Words: Natural Language Processing (NLP), Software as a Service, Document Intelligence, Fast API (Python Web Framework).
