This proof of concept integrates Large Language Models (LLMs) with Oracle PeopleSoft Campus Solutions to enable natural language querying of class and course data, democratizing access to data. PeopleSoft manages essential student records and supports critical academic processes. This prototype, built with Python, LangChain, the ChatGPT API, Streamlit, prompt engineering, and schema transformation, offers a chatbot-style interface for users who may not be SQL experts to access data. User testing confirmed that LLM-generated SQL queries were syntactically correct and accurately reflected user intent, improving accessibility for non-technical users. Challenges included controlling query output and handling complex SQL operations like aggregation and pagination. Security and privacy considerations were also addressed. These findings lay the groundwork for future AI-driven natural language interfaces in Oracle PeopleSoft and other enterprise systems