Amay Bhatnagar

Building an AI diligence agent in Python with the Claude API that scores founder-interview transcripts on 12 weighted criteria, returning scores, explanations, and an overall grade that cites the transcript. The agent has reviewed 60+ deals, and qualified deals now advance about 25% more often. Set rubric weights from analyst benchmarks so the investment committee can review nearly twice as many deals, and connected the scores to the deal pipeline so analysts verify each one. Also manage investor relations for a live Series A raise, drafting updates and meeting materials, with $500K+ committed so far.

Found about $1.2M in overlap in a clinical-trial integration using a Python K-means pipeline on 8,000+ data points, for a deal backed by private equity. Built the client CFO a 12-KPI dashboard in Snowflake, Excel, and Power BI, with Python scripts handling the data cleaning.

Built an M&A diligence dashboard that shows all 40+ targets on one screen, cutting partner review time about 75%. Managed go-live for a 196-workstation IT migration under an M&A deadline and automated migration checklists for the client's operations staff.

Migrated 125 interconnected microservices to a distributed AWS architecture, reducing infrastructure spend about $200K per year for Chase Home Lending. Developed a Python search tool covering 13 mortgage-data categories across 12 systems, adopted by 30+ underwriters.