Abstract: A technique for generative artificial intelligence-based information retrieval is disclosed. The system receives a natural language query for information to be retrieved from a knowledge base, that includes a structured data source and an unstructured data source. Further, contextual information for the natural language query is extracted from the knowledge base by domain-based chunking and tagging of relevant documents in the unstructured data source, and/or executing an automatically generated Structured Query Language (SQL) query, on the structured data source. Following, the system inputs the contextual information along with the natural language query to at least a Large Language Model (LLM). The system provides an output of the LLM as a response to the natural language query.