> ## Documentation Index
> Fetch the complete documentation index at: https://docs.useboom.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# The Agent

> One agent per organization, briefed by a knowledge base, that improves from the corrections your team gives it.

Boom runs **one agent per organization**, not a separate bot per use case. The
agent that runs a win-back campaign is the same agent that staffs a support
line, runs a research round, handles onboarding, qualifies a lead, or collects
a document from a customer. Whatever the mission, it carries your
organization's voice and what it knows about your business into the
conversation.

Treat it like a teammate you brief, not a workflow you have to feed a prompt
to on every step. You set your refund policy, your tone, and the facts about
your business once, and the agent applies them in every conversation it runs,
regardless of which mission that conversation belongs to.

## How you brief it

The **knowledge base** is how you brief the agent. Each organization has its
own, organized into areas:

* **Brand voice**: how the agent should sound.
* **Policies**: what it can promise, refund, or has to escalate.
* **Data schemas**: the people, objects, and events it can reason about.
* **Company information**: the facts about your business it can draw on.

The agent reads from this knowledge base to answer in your voice and stay
inside your rules, no matter which initiative the conversation is part of.

You don't edit the knowledge base through this API. You prepare its content and
hand it to Boom, and the [`build-knowledge-base` skill](/skills) runs that as a
guided interview: it asks what it needs, researches your own site, and hands you
a structured bundle to pass along.

On top of the knowledge base, each initiative carries its own **per-initiative
context and guiding questions**, the specifics of that one mission. The
knowledge base is the constant across every conversation; the per-initiative
layer is what changes from mission to mission.

## How it improves from feedback

When someone on your team gives a thumbs-down to an agent message and says
what was wrong, an internal agent reviews the reasoning behind that message,
patches the knowledge base, and writes a new evaluation case that reproduces
the failed conversation.

<Note>
  The new version of the agent only ships if it passes that new evaluation
  case, alongside every evaluation case written before it. A correction that
  regresses a past fix never reaches your organization.
</Note>

Each correction your team makes is locked in as a permanent test, not a
one-time patch. The agent you have after a month of use is meaningfully
better than the one you started with, because every mistake anyone corrected
along the way is now a case it has to keep passing.

## When it hands off to a person

The agent handles a conversation end to end when it can, and escalates the
ones it shouldn't handle. Escalated conversations land in a shared inbox
where a person can take one over: reply, leave internal notes, and send or
receive files. The customer's attributes sit alongside the conversation, so
whoever picks it up has context without asking the customer to repeat
themselves.

## Guardrails while it talks

Before the agent responds, the conversation is checked for prompt injection.
Before a response goes out, it's reviewed to stop it from sharing personal
data it shouldn't.

<Warning>
  If a customer asks to stop, that's respected: the contact is not messaged
  again, even if someone re-enrolls them into a later initiative. Do Not
  Contact is enforced by the platform, not by whoever built a given flow.
</Warning>

## Reliability

Messages are queued and retried with spacing rather than sent in a burst. If
the primary model provider goes down, Boom falls back to another one so
conversations don't stall.

## Related

<CardGroup cols={2}>
  <Card title="Journeys" icon="route" href="/journeys">
    The workflow behind an initiative, and how you author and publish one.
  </Card>

  <Card title="Extraction" icon="list-checks" href="/extraction">
    The typed fields the agent pulls out of a conversation, and how you read
    them back.
  </Card>

  <Card title="Customer Data Platform" icon="layers" href="/cdp/overview">
    The people, objects, and events behind the data schemas in the
    knowledge base.
  </Card>

  <Card title="Use MCP" icon="plug" href="/use-mcp">
    Connect an AI tool to the same organization and capabilities.
  </Card>
</CardGroup>
