@giulia_buonafina197

KNAI transforms data analysis by addressing a critical challenge: making complex data accessible and actionable for all team members, regardless of technical expertise. Our platform leverages advanced natural language processing to create a seamless bridge between business users and their structured data repositories. Our solution is built on a sophisticated architecture powered by WatsonX and the Granite-3.1-8b-instruct model. This foundation enables KNAI to automatically understand database schemas, transforming natural language questions into precise, optimized SQL queries. The system implements intelligent filtering and maintains contextual awareness, ensuring each interaction builds upon previous queries for more meaningful insights. KNAI stands out through its comprehensive approach to data democratization. Beyond translating questions into queries, it incorporates advanced features like automatic query validation, prompt engineering optimization, and persistent conversation history. This ensures accurate results while maintaining complete transparency of the query generation process. Organizations implementing KNAI have seen substantial improvements in their data analysis capabilities, with projected metrics showing a 75% reduction in analysis time, 90% decrease in query errors, and 60% increase in decision-making speed. This efficiency translates to improved business outcomes and a projected 3x ROI in the first year. For technical teams, KNAI offers robust integration through its API, hosted on IBM Code Engine, with PostgreSQL for structured storage and Redis for conversation management. For business users, it provides an intuitive interface that makes complex data analysis as simple as having a conversation. By eliminating traditional barriers between business users and their data, KNAI enables organizations to make more informed decisions faster, unlock hidden insights, and drive innovation across all levels.

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