Financial NL-to-SQL RAG

1. 1Build a local environment using LangGraph, Ollama, and PGVector
2. 2Configure the Financial NL-to-SQL RAG model to connect to your banking database
3. 3Test the model by asking plain English questions about your database
4. 4Apply the results to inform business decisions or identify trends
5. 5Compare the performance of the RAG model to traditional SQL querying methods

Data scientists and software engineers can benefit from this technology to simplify database querying and improve data analysis

💡 Financial NL-to-SQL RAG enables users to query databases using natural language, simplifying data analysis and improving decision-making

Query your banking database in plain English with Financial NL-to-SQL RAG!