I bridge the gap between advanced financial theory and AI implementation. By combining a formal background in finance with specialized prompt engineering, I build the "logical reasoning layers" required for high-accuracy financial automation and data synthesis.

Educational Foundation
MBA in Finance (Analytics & Research)
Academic training focused on corporate finance, market research, and data-driven decision-making. My background ensures that every AI workflow is built on sound financial principles and professional rigor.

Regulatory & Compliance Knowledge
Deep understanding of financial frameworks, including SEBI and RBI guidelines. This allows me to design AI prompts that respect statutory boundaries and maintain professional standards.

Statistical Expertise
Trained in Regression Analysis and statistical modeling, which I apply to prompt design to ensure AI-generated insights are grounded in data patterns rather than just text generation.

Service Offerings
Financial Prompt Engineering
Designing complex, multi-step prompt chains (Chain-of-Thought) that guide AI models through deep financial analysis, preventing "hallucinations" and ensuring logical consistency.

Automated Financial Reporting
Architecting non-coding workflows to extract, summarize, and synthesize insights from P&L statements, balance sheets, and market research reports.

Workflow Optimization
Streamlining manual finance tasks into AI-assisted processes, using tools like NotebookLM and ChatGPT/Claude to handle large-scale document analysis efficiently.

Strategic Data Logic
Building "low-code" frameworks that use AI to identify market trends, perform variance analysis, and generate executive-level financial summaries.