I will build a structured rag knowledge base in obsidian from your texts

Vietnam

I speak English

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.

Database type:

Centralized database

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Graph database

Platform:

Airtable

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Elasticsearch

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MongoDB

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Neo4J

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Notion

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PostgreSQL

Expertise:

Big data

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Data structure

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Design

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Normalization

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NoSQL

My Portfolio