> For the complete documentation index, see [llms.txt](https://help.brieftech.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.brieftech.ai/concepts/how-ai-analysis-works.md). # How AI analysis works: agents and playbooks BriefTech's AI doesn't run as one undifferentiated black box. It is organised into agents that you switch on for a matter, each driven by a playbook that defines what to look for. Understanding that split explains what the AI can and can't do, where its results turn up, and why you stay in control of it. *** ## Agents and playbooks: the two-layer model There are two ideas at work. An agent is the thing you activate for a matter; it watches your documents and acts on them. A playbook is the instruction set behind an agent — the list of things to extract and how to extract them. Separating the two means the same underlying engine can do very different jobs depending on the playbook it follows. It also means analysis is predictable: an agent extracts what its playbook describes, rather than guessing at the task each time. *** ## The Organise agent and automatic analysis of new uploads The agent you'll meet first is Organise. It reads each document once it is ready and works out what kind of document it is, its key dates, and a short summary. It runs automatically as documents arrive, so a batch you upload and leave alone still comes back classified and described. This is why Review usually has something to correct rather than a blank slate: Organise has already proposed the metadata, and your job is to confirm or adjust it. The **Date** and **Description** fields you see in the Review tab tab are the direct output of this agent — you do not need to trigger extraction manually. Open the Review tab tab after upload to see them filling in as each document finishes processing. The agent also assigns each document a **Document Class**; this is read-only and isn't a Review column, but you can filter by it using the **Classes** group in the left-hand panel. You don't normally trigger analysis by hand — the Organise agent runs on each document as it finishes uploading. You can re-run it on particular documents (for example after correcting a few); re-running replaces only the AI's own suggestions, so any values you've corrected by hand are kept. For the steps, see [Bulk-edit metadata across many documents](/how-to-guides/review/bulk-edit-metadata.md). *** ## What gets extracted — and why the output is structured AI analysis produces structured information — a document class, dates, summaries — rather than loose prose. Structure is the point: because the results land in defined fields, the dates and descriptions flow straight into the Review tab table for checking, and into your Document Index as descriptions and dates. Free text would be harder to trust and impossible to slot into a column. Structured output is what lets the AI's work become part of your finished index rather than a note off to the side. *** ## Why agents are activated per matter Analysis is opt-in at the matter level. You choose which agents apply to a given matter, and activating an agent is what allows it to process that matter's documents. Some agents are switched on for you when a matter is created; others you turn on when you need them. Keeping activation per matter means analysis is deliberate. You decide what kind of work the AI does on each case, rather than every capability running everywhere by default. *** ## How analysis feeds Review and the Document Index The results of analysis are not a separate report — they are woven into the pipeline. Extracted dates and descriptions appear in the Review stage, where you correct them, and the values you settle on become the content of your Document Index. Analysis, review, and indexing are three views of the same underlying document details. > For the agents available and what each one produces, see [AI agents](/reference/ai-agents.md). *** ## Related
AI agentsThe AI agents available in BriefTech and what each one produces./pages/inI4FwnWTojBa1nKPMTF
Bulk-edit metadata across many documentsChange labels, collections, dates, descriptions and index categories on many documents at once./pages/dEDlGCOBIN4gmoc8RlSY
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