Anywhere the API says
workflow, think “agent”. Anywhere the API says workflow_definition, think “the conversation logic inside your agent”.The graph model
A workflow is a directed graph — a set of nodes connected by edges. 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:
transition_speech is optional — if set, the agent speaks it before moving to the next node.
Versioning
Every time you update a workflow’sworkflow_definition, Dograh 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 Dograh generates the initial graph using an LLM. Best for getting started quickly.