HexaCorp partnered with a leading energy company to revolutionize how stakeholders interact with structured data. The core challenge was the dependency on data analysts to write SQL queries, causing significant delays in decision-making. To overcome this, HexaCorp implemented a Generative AI-based solution leveraging LLaMA LLM, LangChain, and Python to convert natural language queries into executable SQL. A user-friendly interface was built using Streamlit, enabling real-time data access and summarization for non-technical users. This scalable, secure solution significantly reduced turnaround time and operational costs while enhancing stakeholder autonomy and decision-making agility.

• Stakeholders relied heavily on analysts to write SQL queries, causing delays in decision-making.
• Writing SQL queries for non-technical users was a significant challenge.
• Executing queries, analyzing results, and summarizing insights required considerable time and effort.
• Scaling the process to meet growing data needs and user expectations was difficult.

• Generative AI Integration: Implemented LLaMA LLM and LangChain to interpret natural language inputs and convert them into SQL queries.
• Automated Query Execution: Utilized Python and PostgreSQL agents to execute generated queries and fetch results in real time.
• Insight Summarization: Developed an AI-driven summarization engine to provide concise insights from query results.
• User-Friendly Interface: Built an intuitive front-end using Streamlit, allowing stakeholders to interact with data effortlessly.
• Scalability and Efficiency: Ensured seamless integration with the existing PostgreSQL database and optimized query execution for faster response times.
• Robust Security Measures: Incorporated role-based access and audit logs to ensure data security and compliance.