Imagine effortlessly querying complex datasets using natural language, receiving accurate answers in seconds. That's the promise of ERATTA, a new AI system designed to make data analysis more accessible and efficient. Traditionally, querying databases required specialized knowledge of SQL or other query languages. ERATTA changes this by leveraging the power of large language models (LLMs) to translate natural language questions into SQL queries, effectively bridging the gap between human language and database interaction. This innovative approach, termed "extreme RAG" (Retrieval Augmented Generation), involves multiple LLMs working in concert. One LLM authenticates user access, ensuring data security. Another LLM interprets the user's question and identifies the relevant data tables. A third LLM generates the SQL code to retrieve the necessary data. Finally, a fourth LLM synthesizes the retrieved information into a natural language response. This compartmentalized approach not only streamlines the query process but also enhances accuracy and reduces the risk of "hallucinations," where AI systems fabricate information. ERATTA goes beyond simply retrieving data; it's designed to handle complex, multi-table queries and provide structured responses in under 10 seconds. Furthermore, a built-in scoring module detects and flags potential hallucinations, ensuring the reliability of the answers. Tested on diverse datasets, including sustainability, financial, and social media data, ERATTA consistently achieves high confidence scores. The implications of this technology are far-reaching. From simplifying complex financial reporting to accelerating scientific discovery, ERATTA empowers users to unlock valuable insights from data, regardless of their technical expertise. While challenges remain, such as handling nuanced queries and ensuring data privacy, ERATTA represents a significant step towards democratizing data access and analysis. As LLMs continue to evolve, we can expect even more sophisticated and user-friendly data interaction tools to emerge, transforming how we understand and utilize information.