Knowledge Base
The Knowledge Base is your account's pool of answer articles. It's what Agent Assist surfaces to agents mid-call and what the AI voice bot searches to answer callers — one pool, sliced by tags so each queue sees the right topics.
Knowledge managers and supervisors curate it: write articles by hand, upload documents, or approve suggestions mined from your own call transcripts.
In the app: Analytics → Knowledge Base.
Browse and search articles
The Articles tab lists every article in the pool. Each row shows its tags, its source, how many search chunks it was split into, and when it was last updated.
- Search titles… filters by title as you type.
- All sources narrows by where an article came from — Manual (typed in), Document (uploaded file), or From call (mined from a transcript).
- The tag chips under the toolbar filter to one or more topics.
A From call article links to the call summary it came from; open it to see the original conversation.
Anyone with Knowledge Base → view can browse and search. Creating, editing, uploading and tagging need Knowledge Base → manage; approving mined candidates needs Knowledge Base → review.
Create an article
- Click New Article (top right of the Articles tab).
- Give it a Title and write the Content — the answer an agent should see: steps, policy, or a resolution.
- Optionally attach one or more tags.
- Click Save.
The article goes live immediately — Orbit splits it into search chunks and embeds it into the pool, so Agent Assist and the voice bot can find it on the next call.
Delete an article
To remove an article, click the trash icon at the end of its row and confirm. Orbit deletes the article and its embedded chunks, so it stops appearing in Agent Assist and voice-bot answers right away.
There's no undo and no trash — a deleted article is gone. If you only want to stop an article showing for one queue, remove its tag instead (see Organize with tags) rather than deleting it.
Organize with tags
Tags are how you slice one pool into per-queue topics (e.g. sales, support,
billing), so a support agent isn't shown sales articles.
Open Manage Tags to create, rename or delete tags. Pick a colour, type a name, and Add. Rename by clicking a tag's name; the number on the right is how many articles carry that tag.
To tag many articles at once, tick their checkboxes in the list and use the Add tag / Remove tag bar that appears.
Once your topics exist, point each queue at the tags it needs in the flow's Agent Assist step — that's what keeps suggestions relevant per queue.
If a tag is referenced by a call flow, deleting it is blocked and Orbit names the flows — detach it there first.
Upload a document
- Click Upload.
- Choose a PDF, Word (.docx), Markdown or plain-text file (up to 20 MB).
- Optionally attach tags, then Upload.
Orbit extracts the text, splits it into chunks and embeds them into the pool. The document then appears in the list with a Document source and its filename; a toast confirms how many chunks were ingested.
Long content is split into smaller passages so search returns the exact relevant part, not a whole document. The Chunks column shows how many an article produced — it's normal for an uploaded file to have several.
Review candidates mined from calls
When a call runs through a flow with Auto-source knowledge enabled, Orbit turns its AI summary into a candidate article and drops it in the Review tab (the badge shows how many are pending). This is how the pool grows itself from real conversations — you stay in control by approving only the useful ones.
For each candidate you can Edit the suggested title/content, adjust its tags, then:
- Approve — it becomes a live article in the pool.
- Reject — it's discarded.
- Show source call — open the call it was mined from.
If a candidate closely matches an article you already have, Orbit flags it with a match percentage and suggests rejecting it. Approving near-duplicates bloats the pool and splits search relevance across two entries.
Reindex after an embedding-model change
You'll rarely see this. Search works by comparing embeddings (numeric vectors) of your content. If the account's embedding model or tier changes, the stored vectors no longer match the new model, and an amber banner appears at the top of the Articles tab with a Reindex now button. Your articles' text is kept — reindexing just re-embeds everything with the new model.
It can take several minutes. Search keeps serving the old vectors until the new set is ready, then swaps over — no downtime, but new content may lag until it finishes.