Sreeraj Sreesadan

Mechanical Engineer with 26+ years of professional experience in Material Master Data Management, MRO spare parts cataloguing, Supply Chain Analytics, and Data Quality Improvement. Currently self-employed, partnering a data consultancy ('Source Corporate') since Jan 2020, and I’m an AI enthusiast focused on training, evaluating, and improving AI/LLM outputs.

I designed, authored, and engineered accurate AI prompts for engineering spare part specifications across Manufacturing, Power, Oil & Gas, Iron & Steel, Mining, and more. I built my own data quality improvement code s purely through AI prompts (GPT 4, Claude Opus/Sonnet 4.6, Google Gemini 3.1 Pro, Local LLMs), and I’ve strengthened ERP-driven data validation, normalization, and classification through monthly extraction and data strategy.

In leadership roles, I managed analysts to deliver supply chain performance visibility, initiated spend analytics and eSourcing events, and established SOPs and quality benchmarks. Notably, I conceptualized and implemented a 'Data Quality Improvement Strategy Roadmap' that increased spend data classification quality from 56% to ~90%, bridging functional and IT teams to deliver reliable global supply data systems.