FoundationaLLM can analyze flat files that reside within a data store that you define. In this example, we defined an intelligent agent that accesses a collection of CSV files containing employee survey data. The agent infers the file schema and generates Python code to query the data and compute the aggregate calculations in order to answer questions about the information and provide recommendations based on analyzing the data. FLLM works with your data to unlock insights that go beyond simple search capabilities.