AI Agents

Automated Airtable data processing and enrichment with AI

51 nodes 310 151 Webhook
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Workflow Description

Workflow that receives data via webhook, processes it using OpenAI's language models to extract and analyze information, then automatically updates Airtable records while efficiently handling large batches of data with conditional logic.

How it works

  1. 1.Receive webhook trigger and initiate workflow execution
  2. 2.Process incoming data in batches using Split In Batches node
  3. 3.Send data to OpenAI for intelligent analysis and content generation
  4. 4.Apply conditional filters and logical rules to results
  5. 5.Update matching Airtable records with processed data automatically

Use cases

  • Process thousands of Airtable records automatically and enrich them with AI-generated insights
  • Extract and classify document content, then save results directly to Airtable tables
  • Analyze customer feedback and generate smart summaries stored in your database

Requirements

  • Active Airtable account with configured database and table structure
  • Valid OpenAI API key with sufficient usage quota and model access
  • Properly formatted data in Airtable to ensure accurate processing and results

Service Value

Ideal as a smart automation service combining integrations and AI to produce ready-to-use results.

Apps Used

Split In Batches LLM Chain OpenAI Airtable

Details

Trigger Webhook
Nodes 51
Apps 4
Views 310
Downloads 151

How to Use

  1. 1.Click "Download Template"
  2. 2.Open your n8n dashboard
  3. 3.Go to Workflows > Import from File
  4. 4.Select downloaded file and configure credentials

Nodes Used (51)

/

Event Type

Switch

#1

Get Prompt Fields

Code

#2

Get File Data

HTTP Request

#3

Extract from File

Extract From File

#4

Get Result

Set

#5

Loop Over Items

Split In Batches

#6

Row Reference

No Op

#7

Generate Field Value

LLM Chain

#8

Fields to Update

Code

#9

Loop Over Items1

Split In Batches

#10

Row Ref

No Op

#11

Get File Data1

HTTP Request

#12

Extract from File1

Extract From File

#13

Get Result1

Set

#14

Generate Field Value1

LLM Chain

#15

Filter Valid Rows

Filter

#16

Filter Valid Fields

Filter

#17

Event Ref

No Op

#18

Event Ref1

No Op

#19

Sticky Note

Sticky Note

#20

Sticky Note1

Sticky Note

#21

Sticky Note2

Sticky Note

#22

Sticky Note3

Sticky Note

#23

Sticky Note4

Sticky Note

#24

Sticky Note5

Sticky Note

#25

Sticky Note7

Sticky Note

#26

Sticky Note8

Sticky Note

#27

Sticky Note9

Sticky Note

#28

Sticky Note10

Sticky Note

#29

Sticky Note11

Sticky Note

#30

OpenAI Chat Model

OpenAI

#31

Sticky Note12

Sticky Note

#32

OpenAI Chat Model1

OpenAI

#33

Sticky Note13

Sticky Note

#34

Sticky Note6

Sticky Note

#35

Get Webhook Payload

HTTP Request

#36

Parse Event

Code

#37

Get Table Schema

Airtable

#38

Fetch Records

Airtable

#39

Update Row

Airtable

#40

Get Row

Airtable

#41

Add Row ID to Payload

Set

#42

Update Record

Airtable

#43

Airtable Webhook

Webhook

#44

When clicking ‘Test workflow’

Manual Trigger

#45

Set Airtable Vars

Set

#46

Get Table Schema1

Airtable

#47

Get "Input" Field

Set

#48

RecordsChanged Webhook

HTTP Request

#49

FieldsChanged Webhook

HTTP Request

#50

Sticky Note14

Sticky Note

#51

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