Knowledge
Knowledge is the org's shared library — documents, small facts, crawled websites, and typed records — that agents ground their replies in. This overview names the tabs and points at the per-area pages.
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Knowledge is the area where the org's data lives so agents can read and cite it. Editors curate it once; agents retrieve over it at reply time, which is why an agent in Tale can answer with your reality instead of the model's training data. The area opens on six tabs: Documents, Knowledge entries, Websites, Products, Customers, and Vendors.
The two shapes
Everything in the area is one of two shapes. Indexed content — the files in Documents, the facts in Knowledge entries, the pages a website crawl brings in — runs through the indexing pipeline (extract, chunk, embed, store) so agents retrieve relevant passages and cite them. Typed records — Products, Customers, Vendors — are rows with named fields that agents read as data, not prose: exact values, no retrieval guesswork.
The shape you pick decides how an agent can use the content, which is why Structured data is a decision page, not just a reference.
How agents reach in
An agent does not see the whole library by default. The agent's Knowledge tab controls its retrieval scope — which parts of the library it searches at reply time — and team-scoped items stay invisible to agents and members outside the team. Retrieval is driven by the agent's RAG-tagged tools, and every retrieved passage carries its source, so citations point back at the file, entry, or page it came from. The agent-side mechanics live in Agent knowledge.
Pages in this section
Documents
Uploading files, the indexing pipeline, supported formats, and the per-document lifecycle.
Knowledge entries
Small, topic-keyed facts — captured from chat with approval or added by hand.
Crawling
Turning a public website into knowledge — domain, scan interval, and the indexed-pages view.
Structured data
Customers, Products, Vendors, Websites — when a typed record beats a document.
Where this fits
Knowledge is the data layer every grounded reply stands on; without it, agents only know what the model already knows. Bring content in through the tab that matches its shape, then wire agents to it — the natural next read is Documents for files, Structured data for records, and Agent knowledge for the retrieval side.