I’m an AI leader, author, and builder focused on practical GenAI systems — especially Retrieval Augmented Generation, agentic AI, enterprise knowledge systems, and AI-native workflows.
Over the last two decades, I’ve worked across analytics, machine learning, data science, and AI. I’ve led enterprise data science and GenAI consulting teams, co-founded and built AI products, and helped organizations turn AI ideas into working systems.
I’m the author of A Simple Guide to Retrieval Augmented Generation. Much of my current work focuses on moving GenAI from prototypes to dependable systems — with the right architecture, evaluation, governance, and human-in-the-loop design.
I also come from a background in theatre and writing, which continues to shape how I think about AI, creativity, communication, and human judgment.
Book
A practical guide to designing and building Retrieval Augmented Generation systems, published by Manning.
The book covers the core ideas, architectures, and implementation patterns behind RAG — from retrieval and chunking to evaluation, operations, and production workflows.
How AI systems retrieve, rank, reason, and respond over enterprise knowledge.
How models plan, use tools, evaluate outputs, and collaborate with humans in real workflows.
How GenAI moves from experiments to governed, observable, production-grade systems.
How AI changes software, teams, decision-making, and organizational design.
How AI reshapes writing, storytelling, art, learning, and creative practice.
I write about GenAI, RAG, agentic AI, enterprise AI systems, and what it means to work and create with AI.
A structured map of 200+ terms across RAG components, pipelines, operations, technologies, and emerging patterns.
A deep dive into advanced indexing, pre-retrieval, retrieval, and post-retrieval techniques for building more reliable RAG systems.
A practical guide to RAG evaluation, retrieval metrics, and measurement-driven improvement.
A guide to the architecture, operational layers, and best practices for building and scaling RAG systems.
An evolving taxonomy of GenAI concepts, language, and building blocks.
I teach and speak about GenAI systems, Retrieval Augmented Generation, agentic workflows, and practical AI adoption.
ACM TechTalk
Software Engineering Radio
Oxford Lifelong Learning
Speaker at HackerRank’s Bangalore AI Circle meetup
AI/ML Systems 2023 tutorial
I have also delivered invited sessions for universities, professional programs, and enterprise teams, including Great Learning, PES University, SCMHRD, Pondicherry University, and Shell India.
I use GitHub to share code, notebooks, tutorials, and experiments around RAG, LLMs, and applied AI systems.
Code examples and illustrations from my Manning book on Retrieval Augmented Generation.
A tutorial repository covering RAG, LLM inference, FAISS, LangChain, and model fine-tuning.
An experimental document and web Q&A application built with OpenAI models and Streamlit.
