Data Science
Prizm AI
RAG-Powered Market Analysis Tool
Built comprehensive financial analysis system synthesizing multi-decade datasets (2000-2025) with Revenue, EPS, and Operating Cash Flow metrics. Engineered hybrid data pipeline using Python and Pandas achieving 98% normalization accuracy. Implemented context-aware retrieval with LangChain and deployed interactive Streamlit dashboards reducing manual analysis time by 70%.
6 months
Project Duration
98% normalization accuracy
Key Achievement
6+
Technologies Used
The Challenge
Prizm AI needed a comprehensive market analysis tool that could synthesize and analyze multi-decade financial datasets to provide actionable business insights.
The Solution
Built a RAG-powered system using LangChain for document processing, integrated with financial APIs, and developed custom normalization algorithms for handling diverse data formats from 2000-2025.
Results & Impact
- Achieved 98% data normalization accuracy
- Reduced manual analysis time by 70%
- Processed 25+ years of financial data
- Generated automated market insights and reports
Project Metrics
98% normalization accuracy
70% manual analysis time reduction
Technologies Used
RAGLangChainPythonPandasStreamlitFinancial APIs
Project Details
Company
Prizm AI
Duration
6 months
Team Size
Solo project with business analyst support
Category
Data Science