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I am a Data Science Manager specializing in agentic AI, data strategy, and production-grade intelligent systems. I lead high-performance solutions that connect real-time data with LLM reasoning—without losing reliability, traceability, or business context.
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| Project | What it does | Focus |
|---|---|---|
| Navexa | Tree-first PDF indexing and vectorless RAG for grounded, traceable answers across long and structured documents. | Python RAG Document AI |
| Navexa Docs | Keyboard-first developer documentation platform with strong information architecture and API discoverability. | Docs DX Web |
| Agentic Data Hub | Multi-agent ecosystem powered by custom MCP servers and clients with synchronized reasoning and actions. | MCP Agents Orchestration |
| InsightGenix | Metadata-aware Text-to-SQL assistant using schema context and retrieval to reduce query drift. | Text-to-SQL Retrieval Analytics |
| Python Course | Notebook-first learning path designed for kids and first-time Python learners. | Python Education Notebooks |
| Scrape-AI | LLM-powered browser automation and intelligent extraction for analysis-ready web datasets. | LLMs Automation Data |
I build practical AI systems that turn complex data, domain knowledge, and LLM reasoning into reliable products.
- Architected agentic workflows, custom MCP integrations, and RAG systems for grounded, traceable answers.
- Delivered end-to-end AI products spanning discovery, data pipelines, modeling, evaluation, and deployment.
- Built cloud-ready analytics and decision-support tools with Python, Azure, AWS, Docker, and Kubernetes.
- Led cross-functional delivery of ML, NLP, and GenAI solutions for high-impact enterprise use cases.
