Handling Large-Scale Financial Data: Processing vast amounts of structured and unstructured financial data required optimizing storage and retrieval mechanisms. We tackled this by integrating Elasticsearch for efficient querying and indexing.
Ensuring Model Accuracy: LLaMA-90B & DeepSeek-R1 with yfinance as the knowledge base for financial predictions posed challenges in terms of accuracy and computational efficiency. We implemented Monte Carlo simulations and confidence scoring to improve reliability.
User-Friendly Experience: Bridging complex AI analysis with an intuitive interface was a hurdle. We focused on interactive dashboards and automated narrative generation to make insights more digestible.