Mayur Agrawal is a forward-thinking Knowledge Strategy Leader with 18+ years of experience architecting enterprise content systems. He is currently spearheading the "Genesis 2.0" initiative, operationalizing Generative AI for technical documentation by shifting workflows from manual drafting to AI-assisted content architecture. Mayur specializes in optimizing unstructured data for Vector Databases and RAG systems. His recent work involves a massive data governance overhaul, archiving over 1,000 legacy product sets to reduce "hallucination noise" in internal AI search tools. He holds a master’s degree in Computer Science from La Trobe University, where his thesis on "Retrieval Logic" foreshadowed modern LLM architecture.