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

# Workflows & Agents

> How conversation flows are defined in Ambivert AI

In Ambivert AI, what you see as an **agent** in the dashboard is called a **workflow** in the API. They are the same thing — a workflow is the underlying definition, agent is the product name for it.

<Note>
  Anywhere the API says `workflow`, think "agent". Anywhere the API says `workflow_definition`, think "the conversation logic inside your agent".
</Note>

## The graph model

A workflow is a **directed graph** — a set of nodes connected by edges.

```mermaid theme={null}
graph LR
    A[Start Call] -->|Caller greets| B[Qualify Intent]
    B -->|Wants support| C[Support Agent]
    B -->|Wants sales| D[Sales Agent]
    C -->|Issue resolved| E[End Call]
    D -->|Demo booked| E
```

**Nodes** are the steps in the conversation. Each node has a prompt that tells the LLM what to say and do at that point.

**Edges** are the transitions between nodes. Each edge has a condition — a natural language description of when to move on. The LLM evaluates whether the condition has been met based on the conversation so far.

## Node types

| Type         | What it does                                                                                     |
| ------------ | ------------------------------------------------------------------------------------------------ |
| `startCall`  | Entry point for telephony calls. The first thing the agent says when a call connects             |
| `agentNode`  | An LLM-powered conversation step. The core building block                                        |
| `globalNode` | Defines instructions that apply across all agent nodes (e.g. tone, language, fallback behaviour) |
| `endCall`    | Terminates the call                                                                              |
| `trigger`    | Entry point for API-triggered runs (non-telephony)                                               |
| `webhook`    | Fires an HTTP request when reached — use for CRM updates, notifications, etc.                    |
| `qa`         | Runs automated quality analysis on the completed call                                            |

## Edges and transitions

An edge connects two nodes and fires when its condition is satisfied:

<img src="https://mintlify.s3.us-west-1.amazonaws.com/ambivertai/images/edge.png" alt="Edge configuration" style={{border: "1px solid #d1d5db", borderRadius: "8px", maxWidth: "100%"}} />

`transition_speech` is optional — if set, the agent speaks it before moving to the next node.

## Versioning

Every time you update a workflow's `workflow_definition`, Ambivert AI saves a new version while keeping the history. The current version is always what runs. Old versions are retained for auditing.

## Creating workflows

There are two ways to create a workflow via the API:

* **From a definition** — provide the full node/edge graph yourself. Best for programmatic generation.
* **From a template** — describe the use case in natural language and Ambivert AI generates the initial graph using an LLM. Best for getting started quickly.

See the [Workflow Definition Schema](/developer/workflow-schema) for the full field reference.