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I will build a structured rag knowledge base in obsidian from your texts
I build RAG ready knowledge bases from your texts
I transform unstructured texts into structured, RAG-ready knowledge bases in Obsidian. My flagship project: a 4,400+ note TCM vault built from 25 expert sources — textbooks, lectures, web databases, a...
About this Gig
fully optimized for AI retrieval (RAG).
What you get:
Clean folder hierarchy with logical categorization. Cross-linked notes with wiki-style backlinks. YAML frontmatter metadata on every note. Consistent tagging system. Index notes and Maps of Content for easy navigation.
Why this matters:
A well-structured knowledge base lets you find any piece of information in seconds, not hours. With RAG-ready metadata, your content becomes instantly searchable by AI tools like ChatGPT, Claude, or custom LLM pipelines.
My background:
I build and maintain multiple large-scale Obsidian vaults (500+ notes each) covering technical documentation, medical literature, and research materials. I use structured ID systems, cross-referencing, and custom templates daily.
Ideal for researchers, companies building internal knowledge bases, authors organizing reference material, and anyone who wants their documents AI-searchable.
Every delivery includes a walkthrough so you can maintain and extend the vault yourself.
My Portfolio
FAQ
What format will I receive the knowledge base in?
You will receive a complete Obsidian vault as a ZIP file. Just unzip it and open with the free Obsidian app. All notes, folders, tags, and links will work immediately.
What do I need to provide to get started?
Send me your source materials: PDFs, Word docs, text files, or web links. I will handle all the structuring, tagging, and linking from there.
What does RAG-ready mean?
RAG (Retrieval-Augmented Generation) means your knowledge base is structured so AI tools can search and retrieve relevant information efficiently. This includes consistent metadata, clear hierarchy, and semantic tagging.
