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In wiki and card-based knowledge bases, content is written by hand: someone summarises a topic, turns it into a card, and verifies it periodically. The model works, but rests on an assumption — that an owner exists to keep the cards current. In practice that ownership weakens over time; verification dates lapse, cards drift from the source document, and two truths emerge: what the card says and what the procedure says.

The drift becomes most visible when legislation or a procedure changes. The procedure file is updated but the card summarising it is not; the team reads the card and acts on the old rule. The card-based system is not itself flawed, but it requires continuous human maintenance.

KobiGPT takes a different approach: it produces no intermediate summary layer, indexing the source document and answering from it directly. When the procedure file is updated it is re-indexed and answers automatically reflect the new content; there is no separate card left to update.

The cost of this is that answer quality binds directly to document quality. A well-written procedure produces good answers; a vague or contradictory document produces vague answers. In a card system a human resolves that ambiguity while writing; in a document-based system it must be resolved in the document itself.

Your existing cards are not lost; you can export and upload them as documents. But the practical recommendation differs: rather than moving the cards, attaching the source documents the cards summarise usually produces better results. A card is already an interpretation of a source, and indexing the interpretation creates a double layer.

During migration the cards make a good audit tool: where a card and the assistant's source-grounded answer disagree, either the document or the card is out of date. That comparison makes the real debt in your knowledge base visible. The 100-document capacity on the Ücretsiz plan plan is enough to run that audit.