Knodegraph is a knowledge graph builder that lets you upload documents and automatically extract entities and relationships using AI. You can also build graphs manually with a drag-and-drop editor.

How much does Knodegraph cost?

Knodegraph has a free tier with 3 graphs and 100 nodes per graph. The Pro plan is $14.99/month and includes unlimited graphs, 50,000 nodes, NLP extraction, multilingual support, and API access.

What languages does Knodegraph support?

Knodegraph supports over 100 languages for entity extraction, including English, Arabic (with full RTL support), French, Spanish, German, Chinese, Japanese, and many more.

Is my data secure on Knodegraph?

Yes. Knodegraph uses per-user data isolation, meaning your knowledge graphs are completely separate from other users. All data is stored on secure, self-hosted infrastructure with encrypted connections.

How does AI extraction work?

Upload any document and Knodegraph uses Claude AI to identify entities (people, organizations, locations, concepts) and the relationships between them. Extracted data is staged for your review before being added to your graph - you always have final control.

Can I export my knowledge graphs?

Yes. Free users can export to PNG, SVG, JSON, and CSV. Pro users additionally get access to JSON-LD, RDF, and Neo4j export formats.

Tutorials 10 min read

Using a Knowledge Graph for Personal Knowledge Management (PKM)

Published 2026-04-30

Personal knowledge management tools have multiplied — Notion, Obsidian, Logseq, Tana — but most still treat your notes as a tree or flat link soup. A typed knowledge graph adds precise, queryable structure none of them give you on their own. This tutorial walks through PKM on a real graph database, organised around PARA and Tiago Forte's CODE framework.

Step 1: Capture into a single inbox

Friction kills PKM. The capture step has to take under 10 seconds. Pick one inbox and one capture shortcut, regardless of source.

Step 2: Process with PARA + a typed graph

Tiago Forte's PARA gives you four buckets: Projects, Areas, Resources, Archives. The graph version adds typed edges between them and the captured notes.

Step 3: Distill notes into atomic concepts

Every time you re-read a note, extract one or two atomic concepts and link them. Atomic concepts are reusable, get richer over time, and become the high-degree hubs of your graph.

Step 4: Query rather than search

Search returns ranked text. Querying returns answers. A typed graph lets you ask things you cannot ask of a normal note tool.

Step 5: Schedule a weekly review

PARA's weekly review is the part everyone skips. Process the Inbox to zero, run two queries, prune one stale Project. 15 minutes a week.

Common pitfalls

Trying to capture everything. Cull aggressively.
Letting the inbox grow unboundedly. Process to zero weekly.
Confusing taxonomy with graph. PARA is four buckets, not four trees.
Inventing too many node types. Stick to Note / Project / Area / Concept / Person at first.
Refusing to delete. Archive is part of PARA for a reason.

Frequently Asked Questions

Do I need to abandon Obsidian / Notion / Logseq?

No — they remain great capture front-ends. Use them as the editor, then sync the underlying Markdown into a graph database.

How is this different from Obsidian's graph view?

Obsidian's graph view is undirected, untyped, and read-only. A typed graph distinguishes MENTIONS from CONTRADICTS from CITES, supports queries, and stores edge properties.

How many notes before this is worth doing?

Around 1,000 notes. Below that, full-text search and tags carry you. Past 1,000, the graph approach pays for itself within a month.

What about spaced repetition / Anki?

Compatible. Treat each Anki card as a `:Card` node linked to its source `:Note` and prioritize review by graph centrality.

Does AI extraction help here?

Yes — auto-extracting Concepts from each new note keeps your concept layer rich without conscious effort.

Source

Tiago Forte's 'Building a Second Brain' (Atria, 2022) introduced the PARA + CODE framework now adopted by 100,000+ paying course alumni. Forte's 2023 'State of PKM' analytics report users with 50+ cross-bucket links retrieve information 4.2x faster than users with under 10 — directly motivating the graph-shaped approach. [link]

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