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Technologies Involved:
NATURAL LANGUAGE PROCESSING (NLP)
PYTHON
Area Of Work: Generative AI
Project Description

The Financial Data Chatbot redefines how users access financial insights through intuitive, AI-driven conversations. The client partnered with Oodles to build a smart chatbot that understands complex queries and delivers real-time, structured financial data with speed and precision, empowering users with instant, data-backed decisions.
Scope Of Work

The client engaged Oodles to design and develop a conversational Financial Data Chatbot capable of retrieving and presenting financial data through an interactive interface. The scope included creating a chatbot powered by Natural Language Processing (NLP) to understand and classify user queries. Oodles integrated two key data retrieval agents — the Supabase Agent, which fetched structured and historical data from the Supabase database, and the Web Search Agent, which retrieved real-time financial information from APIs such as Alpha Vantage. The engagement also involved implementing structured response generation, error handling, and a feedback system to ensure reliability and accuracy. Additionally, real-time integration with minimal delay was prioritized to provide users with timely, accurate financial insights.
Our Solution

Our comprehensive solution focused on building a scalable, intelligent, and user-centric Financial Data Chatbot to simplify access to financial insights.

 

Our Solution for the Financial Data Chatbot:

  • Frontend and Backend Development: Built the frontend in React/Next.js and backend in FastAPI/Node.js for scalability and smooth performance.
  • Supabase Agent Integration: Configured the Supabase Agent to fetch structured and historical data from predefined financial datasets.
  • Web Search Agent Integration: Integrated the Web Search Agent with APIs like Alpha Vantage to provide real-time market data.
  • NLP-Driven Query Classification: Implemented an NLP engine to interpret queries, classify intent, and route them to the right source.
  • Structured Response Generation: Designed a system that delivers concise, accurate, and readable financial insights.
  • Error Handling and Feedback: Added error handling for missing data and a feedback loop to refine accuracy.
  • Real-Time Data Integration: Optimized latency to ensure users receive the latest financial data instantly via a seamless chatbot experience.

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