Build a Custom AI Research Assistant with RAG & LangChain – A Step-by-Step Tutorial

1. Why Build a RAG-Based Research Assistant?

• Understand the core problem: LLMs have knowledge cutoffs and hallucinate on private or recent documents — RAG (Retrieval-Augmented Generation) solves both by grounding responses in your own data.
• Real-world use cases: summarizing academic papers, answering questions from internal wikis, or building a personal knowledge base chatbot.
• What you’ll build by the end: a working research assistant that ingests PDFs, indexes

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  Written byTheo Grant

  Theo Grant explores real-world AI applications, automation workflows, and hands-on tutorials at AI In Action Hub. Theo breaks down complex AI concepts into practical guides that help professionals and creators leverage AI in their daily work.