Autom8 AI Docs
  • Introduction to A8I
  • Quick Start
    • Your First Workflow
  • Workflows Explained
    • Create and Run a Workflow
    • Workflow Components
    • Executions
    • Manual, Partial, and Production Executions
    • Workflow Executions
    • All Executions
    • Custom Execution Data
    • Debug and Re-run Past Executions
    • Tags
    • Export and Import Workflows
    • Workflow Templates
    • Workflow Sharing
    • Workflow Settings
  • Flow Logic
  • Data
    • Data Structure
    • Data Flow Within Nodes
    • Transforming Data
    • Processing Data with Code
    • Data Mapping
  • AI Assistant
  • Glossary
  • Integrations
  • Build an AI Chat Agent in Autom8 AI
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Data

Data is the core of every workflow in Autom8 AI—it's what flows through nodes, triggers actions, and drives logic.

For simple workflows, you don’t need deep knowledge of how data is structured. But if you're building advanced flows, writing code, or creating custom nodes, understanding how data is handled becomes essential.


Why Data Matters

A solid understanding of data helps when you:

  • Build custom or advanced nodes

  • Write dynamic expressions or conditional logic

  • Use coding nodes like Function or Function Item

  • Manipulate or transform inputs before sending them to other systems


What This Section Covers

  • Data structure: How Autom8 AI organizes data in items and fields

  • Data flow: How data moves between nodes

  • Transforming data: Using built-in nodes to modify or reshape data

  • Using code: Writing JavaScript or Python to process data

  • Pinning/editing data: Freezing and editing node outputs during workflow development

  • Item linking: How data items stay related across branches or merged paths


Data Transformation Nodes

Autom8 AI offers built-in tools to help reshape and manage data:

  • Aggregate: Combine multiple items into one

  • Limit: Restrict output to a set number of items

  • Remove Duplicates: Clean up repeated data entries

  • Sort: Order or randomly shuffle items

  • Split Out: Break list-type data into separate items

  • Summarize: Group data for summary insights, similar to pivot tables

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Last updated 5 days ago