Year: 2025
Type: article
Abstract: Fin-RAG (Financial Retrieval-Augmented Generation) is an AI-powered chatbot system designed to simplify and accelerate financial data retrieval. Built on Retrieval-Augmented Generation (RAG), it enables natural language querying of financial documents, delivering accurate and context-aware responses in real time. The system supports both text-based and image-based documents, utilizing advanced NLP and image recognition capabilities. Users can extract key insights from balance sheets, profit and loss statements, and scanned invoices effortlessly. Fin-RAG leverages domain-specific embeddings via Hugging Face’s Inference API for precise and relevant search results. Key features include real-time insights, automated reporting, semantic search, and multimodal document analysis. Scalable and compliant, Fin-RAG improves financial decision-making efficiency. It is ideal for auditing, corporate finance, and strategic analysis.
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4409969381