Trust

Build a Source-Backed AI Knowledge Base for Agents

Build a source-backed AI knowledge base by connecting trusted sources, atomic knowledge, maintained LLM-wiki pages, citations, review, and refresh state.

Qi-Xuan LuUpdated Aug 20265 min read

Article packet

Concepts

Teams building a local AI knowledge base that agents and people can inspect

5 min read

Trusted sources remain separate from the knowledge derived from them.

Atomic knowledge preserves precise evidence before it becomes a page.

Maintained pages carry citations, review, revisions, and refresh state.

Quick answer

To build a source-backed AI knowledge base, keep trusted sources, atomic knowledge, and maintained LLM-wiki pages separate. Connect them with citations, review, revisions, and refresh state so agents retrieve current answers and people can inspect why those answers are trusted.

Wenlan separates Sources, Memories, and Pages. Source IDs connect maintained pages to supporting knowledge, while revision, stale-reason, review, and refresh flows keep the knowledge base inspectable instead of silently rewriting it.

When this problem appears

Raw document dumps and one-off summaries both decay. A dump makes agents search too much context; a detached summary can become stale without showing which source supported it or what should refresh it.

Build the smallest maintainable loop

Prove one topic end to end before importing a large archive.

Register or scope the trusted source that should support the topic.
Capture one atomic fact with its source and why it matters.
Distill only after a topic repeats or needs a reusable answer.
Open the page and inspect the source IDs behind its claims.
Run lint to find thin, stale, conflicting, or unsupported knowledge.
Curate revisions and refresh the page when its evidence changes.

Wenlan knowledge-base loop

/brief <topic>
/capture <fact + source + why>
/distill <topic>
/pages <topic>
/lint
/curate

What to check next

A maintained page is still a claim, not ground truth. Verify important conclusions against the cited source, and mark the page stale when the source or operating context changes.

Try the local memory loop

Install Wenlan, connect your AI client, and verify that capture, recall, and handoff work on your machine.

Get started View on GitHub

FAQ

Is an AI knowledge base the same as RAG?+

No. RAG retrieves source fragments at question time. A maintained knowledge base also keeps reusable answers, citations, review, and refresh state; it may use retrieval underneath.

Should I import every note before starting?+

No. Start with one repeated, high-value topic and prove its source, capture, distill, inspection, lint, and review loop before expanding.