Financial Document Analyzer Using AI

Financial reports are typically lengthy, information-heavy, and challenging to interpret without automated assistance. To address this, we created an application that simplifies the review of such documents by processing them automatically. The system accepts PDF files, converts them into smaller text segments, and applies advanced language-model techniques to enable more meaningful search and understanding. These segmented representations are stored in a vector database (ChromaDB) for rapid semantic retrieval, while key extracted values are saved in MongoDB to support structured queries. A Streamlit interface provides an interactive environment where users can converse with the documents, browse stored information, and perform audits assisted by an AI model. The solution reduces the time required to navigate extensive financial files and offers a practical demonstration of how modern AI can enhance real-world document analysis workflows.