FinKnowledge is an advanced web application designed to streamline the analysis and exploration of financial reports using artificial intelligence. Users can easily upload PDF documents such as annual reports, 10-Ks, or other financial filings. Once uploaded, the system parses and indexes the contents using state-of-the-art language models and vector embeddings, storing them in a high-performance Qdrant vector database. This enables fast, semantic search and retrieval of information from large, complex documents. The application features a user-friendly interface built with Streamlit, allowing users to interact with their indexed reports through a chat-like experience. Users can ask natural language questions about the contents of their financial documents, such as “What were the key financial highlights for 2023?” or “Summarize the risk factors mentioned in the report.” The backend, powered by FastAPI, processes these queries, applies optional filters (such as company name, fiscal year, or report type), and retrieves the most relevant excerpts from the indexed data. To enhance clarity and readability, the system uses Google Gemini AI to rewrite and summarize retrieved information, presenting answers in concise bullet points or easy-to-understand paragraphs. This makes complex financial data accessible to both experts and non-experts. The application supports multiple companies and report types, allowing users to build a searchable knowledge base tailored to their needs. FinKnowledge is ideal for financial analysts, investors, auditors, and anyone who needs to quickly extract insights from financial documents. Its modular architecture, combining FastAPI, Qdrant, and Streamlit, ensures scalability, speed, and a seamless user experience.
19 Nov 2025
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