Implemented a semantic search engine integrating tools such as Confluence, GitHub, and other workplace tools to streamline project management processes. Developed algorithms to process natural language queries and retrieve relevant information from project data stored in various information hubs. Utilized embedding models including OpenAI's text-embedding-ada-002-v2 (ada-v2) and Google's gcp-textembedding-gecko-001 (gcp-gecko) to convert extracted data into embeddings. Designed and implemented a chat interface for the semantic search engine, enabling users to interactively access project data. Collaborated with AI agents to optimize search algorithms and improve decision-making in query processing. During this research enriched my understanding with GenerativeAI, NLP, embedding models, vector databases. Presented the above work in DemoJam challenge in SAP Dcom-2024