FinWise: Streamlining financial data retrieval for smarter, faster insights.
FinWise is an advanced AI-driven financial consultant designed to streamline and transform how financial data is retrieved, organized, and analyzed. At its core, FinWise tackles the inefficiencies financial professionals face when extracting and managing information from complex documents like annual reports. By utilizing a cutting-edge Knowledge-Graph Retrieval-Augmented Generation (KG-RAG) system, FinWise dynamically builds and updates a knowledge graph, enabling intelligent query-based retrieval across multiple documents. This empowers users to ask natural language questions and receive precise, context-aware financial insights.
FinWise integrates several key components:
The system supports a rich feature set:
FinWise is designed with scalability and ease of use in mind, targeting financial professionals and large corporations that need efficient, reliable solutions for managing complex data. By offering the ability to manage and visualize financial information seamlessly, FinWise reduces manual efforts in data extraction, formatting, and conversion, significantly enhancing productivity. Additionally, it handles global data format variations, such as international and Indian numbering conventions, allowing for smoother global financial analysis.
The system doesn’t just answer queries; it helps users present data in a meaningful way, whether by providing tailored insights, generating dynamic graphs, or adapting to diverse formats. FinWise aims to transform the way financial consultants and corporations manage their data, making the process faster, smarter, and more intuitive.
I discovered GaiaNet from HackArCode, but actually understood it from CodeCubicle 3.0's GaiaNet session, both of which I participated in. GaiaNet gave me wings in terms of AI-powered development, Especially with the public nodes hosted on GaiaNet, they were a life saver. The rest of the tech stach is Streamlit for the UI of the bot and Python as the backend.
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