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

# What a Vertical Is

> A Vertical is a curated, domain-specific intelligence layer over MCP — start from the business question, not the signal taxonomy.

A **Vertical** is a curated, domain-specific intelligence layer exposed over MCP. Where your own data tables hold *your* orders, customers, and leads, a Vertical holds the **market around you** — the entities that matter in your industry and everything known about them.

It is not a generic web search and not a raw database query. It is a deliberately modeled surface:

* **Canonical entities** — the brands, models, or players of the domain, each with a stable `entity_id`.
* **Structured signals** — named, typed observations attached to an entity (growth, paid-media, engagement, launches, reviews, …).
* **Time-based observations** — each signal is anchored to a period, so you can see change, not just a snapshot.
* **Cross-entity comparison** — aligned signals across several entities in one call.
* **Market benchmarks** — the "what is normal" aggregates you read a single entity against.
* **Reference lookups** — the controlled vocabulary (countries, tiers, segments, platforms) the surface uses.
* **Editorial know-how** — guides, playbooks, and interpretation rules that explain what the numbers mean.
* **Evidence links** — public source references behind a signal, on request.

## The core principle: start from the business question

The most important habit when using a Vertical: **start from the business question, not the signal taxonomy.**

The AI maps a natural-language intent to the right tool and the right signals. Signal names (`growth_30_60_90`, `omni_channel_score`, `trend_break`, …) are an **agent-facing vocabulary** — an internal index the AI uses to fetch the right evidence. They are not something the user has to know or name.

<Note>
  **Example.** A user asks *"Is this brand growing?"* — the AI internally reaches for the growth signals, retrieves them, and answers in plain language. The user never needs to know a signal called `growth_trajectory_class` exists. The intent drives the tool selection; the taxonomy stays behind the curtain.
</Note>

This is what separates a Vertical from a search box. A search box makes the user speak its language. A Vertical lets the user speak in business terms, and the AI does the translation into signals and tools.

## What a Vertical is not

* **Not a generic web search** — it returns curated, benchmarked signals, not arbitrary pages.
* **Not a raw DB search** — you do not write SQL or guess column names; you ask a question and the AI routes it.
* **Not your first-party data** — it is the market *around* your business, complementary to your own tables.

## Where to go next

<CardGroup cols={2}>
  <Card title="START HERE — What can you ask?" icon="signs-post" href="/for-agents/vertical/start-here">
    The intent library: every kind of question the Vertical can answer, grouped by goal, plus the mandatory first-use bootstrap.
  </Card>

  <Card title="AI Operating Rules" icon="shield-check" href="/for-agents/vertical/operating-rules">
    The ten grounding rules that keep every answer honest and auditable.
  </Card>

  <Card title="Tool Reference" icon="wrench" href="/for-agents/vertical/tools">
    Each canonical `vertical_*` tool: purpose, when to call, key inputs, notes.
  </Card>

  <Card title="Business Question Recipes" icon="list-check" href="/for-agents/vertical/recipes">
    Natural questions mapped to tool-and-signal flows and answer framing.
  </Card>
</CardGroup>

For the complete tool list and parameters see [Vertical (market intelligence)](/for-agents/vertical). For how the Vertical fits the wider session contract see the [Operating Contract](/for-agents/ai/operating-contract).