> ## Documentation Index
> Fetch the complete documentation index at: https://docs.a2v2.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Knowledge Base Overview
> The knowledge base is the content your agent answers from. Here's how it works and how to fill it.
The **Knowledge Base** is where you give your agent its expertise. Everything the
agent knows about *your* business comes from the sources you add here. The more
relevant and well-organized your sources, the better your agent answers.
Open it from the agent sidebar under **Expertise → Knowledge Base**. Its subtitle
sums up the goal: "Create organized content collections that help your AI provide
consistent, detailed responses."
To add content, select **New Knowledge Item** — this opens a tabbed screen with
five source types.
## Source types
You can train an agent on five kinds of sources. Mix and match as many as you need.
Paste plain text directly — notes, snippets, policies, anything you can type.
Upload documents like PDF, DOCX, and TXT — manuals, policies, guides, reports.
Pull the transcript from a YouTube video and train on what's said.
Write a question and its exact answer — best for FAQs and canned responses.
Add website links and index their content automatically.
## Usage
The Knowledge Base header shows how much of your plan's capacity you've used:
| Meter | What it tracks |
| ------------------- | --------------------------------------------------------------------- |
| **Characters Used** | Total characters indexed across all sources (for example, 0 / 15.0M). |
| **Documents Used** | Number of sources added (for example, 0 / 100). |
These limits depend on your plan — the values above are an example from a
free/trial plan. Check the meters on your own Knowledge Base for your current
allowance.
You can filter the source list by **Search by name**, **KB items**, **Status**,
**Sort by**, and **Date Range** to find a specific source quickly.
## How processing works
Adding a source kicks off background processing that turns your content into
something the agent can search:
The file or URL is read and the raw text is extracted (including from PDFs and
Word documents).
The text is split into small, overlapping passages so the agent retrieves only
the relevant part of a long document.
Each passage is converted into an embedding and stored in your agent's private
vector index, ready to be searched on every question.
You don't have to wait on this screen — processing runs in the background, even
for large files. See [Manage sources](/knowledge-base/manage-sources) to track
status and retrain.
### Source statuses
| Status | Meaning |
| ------------------------- | ---------------------------------------------------------------------------------------------------------------- |
| **Unprocessed / Pending** | Queued, waiting to start. |
| **Processing** | Being read, chunked, and indexed. |
| **Completed** | Indexed and live — the agent can now use it. |
| **Failed** | Something went wrong. [Reprocess it](/knowledge-base/manage-sources#reprocess-a-source) or remove and re-add it. |
Only **Completed** sources are used in answers. If your agent ignores content you
just added, check that the source finished processing.
## What makes a good knowledge base
* **Prefer clean text.** Searchable PDFs and well-structured docs beat scanned
images and screenshots.
* **One topic per source** where you can — it keeps retrieval sharp.
* **Add Q\&A pairs for the questions you already know** customers ask. They give
precise, predictable answers.
* **Remove stale content.** Outdated sources produce outdated answers.
## Searching your knowledge base
You can search across an agent's indexed content directly from the Knowledge Base
screen to confirm a topic is covered before you rely on it in a live agent.
## Related