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Documentation Index

Fetch the complete documentation index at: https://docs.xpander.ai/llms.txt

Use this file to discover all available pages before exploring further.

The canvas is the workspace where you build workflow pipelines. Triggers on the left, processing logic in the middle, outputs on the right. This page covers placing nodes, testing, and the save-and-publish cycle.
Canvas vs. node configuration: This page covers the canvas workspace. For configuring individual node types (writing instructions, selecting tools, setting up classification groups), see Agent Nodes, Action Nodes, and Flow Control.

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Canvas layout

Every workflow flows left to right: a START block on the left, an END block on the right, and a purple connection line between them. Events enter from the left, pass through each node in sequence, and exit as output on the right.
Workflow canvas layout
The START block stacks five trigger types vertically (Webhook, API, Chat, Slack, Schedule). Each row shows a green dot when enabled and a badge below counts active triggers (“3 events”). The END block stacks three output options:
  • A Summarizer for natural language digests
  • A JSON Object for structured data against a schema
  • Notifications for emails or webhooks on success or failure
When a node branches (Classifier, Condition, Guardrail), the canvas expands vertically to show parallel paths, but the left-to-right direction stays the same.

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Add nodes

Click the + button on any connection line to open the node picker. It organizes 15 node types into three categories. Agents use AI to reason about data:
NodeWhat it does
AgentFull AI agent with tool access for multi-step reasoning
ClassifierRoutes inputs to different branches based on meaning
SummarizerCondenses or extracts from content
Actions run deterministic operations without an LLM:
NodeWhat it does
ActionInvokes a connector tool (Salesforce, GitHub, Slack, 2,000+ more)
WorkflowNests a separate workflow as a sub-process
Custom FunctionExecutes a custom function you’ve defined
CodeRuns Python for calculations and transformations
EmailSends an email
OCRExtracts text from images
Upload FileUploads a file to a destination
Flow nodes control branching and execution:
NodeWhat it does
ConditionSplits flow based on values (contains, equals, regex, comparisons)
GuardrailAI judge that validates output as Pass or Fail
WaitPauses for human approval before continuing
Send to EndFinishes the workflow immediately
ParallelRuns child nodes concurrently and combines results
Add node dropdown
Clicking a node type inserts it at that position. A configuration panel opens on the right where you write instructions, select tools, or define conditions. Every connection line between nodes has its own + button, so you can insert steps anywhere in the pipeline without rebuilding the flow. Branching nodes (Classifier, Condition, Guardrail) automatically create output branches. A Classifier with “Billing,” “Technical Support,” and “Other” groups fans out into three branches, each with its own + buttons for adding downstream logic.

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Test workflows

The top toolbar has a green Run button labeled with the active test preset name (e.g., “Hello World”). Click the gear icon next to it to configure your test payload: plain text or JSON, with optional file attachments. Save named presets so you can re-run the same test cases quickly. When a test starts, the Output Console appears at the bottom of the canvas showing real-time execution events: task creation, tool requests, tool results, and the final outcome. Click any entry to expand the full JSON payload.
Test input and output console
If your workflow handles different input shapes, create a preset for each one and cycle through them before publishing. The top toolbar also has Builder and Monitor tabs. Builder is the canvas. Monitor shows execution history, logs, and metrics after the workflow has run.

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Save and publish

Changes are not saved automatically. When you modify anything, a floating toolbar appears at the bottom with Undo, Reset, and Save. It disappears once you save or reset.
Floating save toolbar
Saving stores your changes but does not deploy them. The live version that triggers run against stays unchanged until you publish. This lets you iterate without affecting production traffic. The cycle:
  1. Make changes on the canvas
  2. Save using the floating toolbar
  3. The Publish button in the top toolbar turns purple with a red dot
  4. Click Publish, confirm the dialog, and the new version goes live
Each publish creates a new live version. All triggers (webhooks, schedules, API calls) immediately execute against it. If something goes wrong, you can roll back to a previous version. The platform keeps immutable snapshots of every published version.
Save vs. Publish: Save is a checkpoint. Publish is a release. Save frequently as you work. Publish when the workflow is ready for production traffic. You can save many times between publishes, but only a publish pushes changes to the live version.

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What’s next

Triggers

Configure webhooks, schedules, API calls, and other trigger types in the START block.

Agent Nodes

Add AI-powered reasoning steps that query systems, classify inputs, and summarize results.

Action Nodes

Run deterministic operations: tool invocations, code, email, and OCR.

Flow Control

Branch with conditions, validate with guardrails, and pause for human approval.