Himanshu Goel
AI Research Engineer & Data Scientist | GenAI, LLMs, RAG
Delhi, India
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Himanshu Goel is an AI Research Engineer and Data Scientist with nearly six years of experience building and deploying production-grade AI, machine learning, and Generative AI systems across finance and healthcare. He specializes in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and document intelligence systems, with a strong focus on reliability, scalability, and real-world constraints.
His work spans the full AI lifecycle, including data analysis, feature engineering, statistical modeling, and the design of end-to-end ML and GenAI pipelines using Python, TensorFlow, LangChain, and cloud platforms such as AWS and Azure. Himanshu has led and contributed to enterprise solutions involving semantic search, regulatory document analysis, predictive modeling, and AI-powered decision support systems, delivering measurable improvements in accuracy, efficiency, and cost.
Through his talks, Himanshu focuses on sharing practical lessons from building AI systems in production covering architecture decisions, trade-offs, failure modes, and best practices for deploying trustworthy AI solutions in cloud environments.
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Building Internal AI Platforms: From RAG Pipelines to Platform Capabilities
This talk explores how organizations can evolve AI pipelines into internal platforms. It covers turning RAG systems into reusable platform capabilities that improve developer experience, governance, and scalability across teams.
Himanshu Goel
AI Research Engineer & Data Scientist | GenAI, LLMs, RAG
Delhi, India
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