AI Agents

Extract tweet data and save to Airtable with AI processing

51 nodes 297 158 Automatic trigger
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Workflow Description

An intelligent automation that monitors X, extracts information from tweets using advanced language models, processes and formats the data automatically, then saves it systematically to Airtable tables. This workflow handles data validation and transformation before storage for review and analysis.

How it works

  1. 1.Trigger manually or when new tweets matching criteria are detected on X
  2. 2.Process tweet text using advanced language models to extract relevant data
  3. 3.Validate and transform results to ensure data quality and consistency
  4. 4.Store processed data in specified Airtable records

Use cases

  • Collect customer feedback and insights from social media and organize them in a database
  • Monitor brand conversations and automatically extract important information for tracking
  • Gather community ideas and suggestions, classify them accurately for decision-making

Requirements

  • Active X account with API access and data retrieval permissions
  • Airtable workspace with tables configured to receive and store data
  • API keys for Anthropic and Open Router language model services

Service Value

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

Apps Used

Output Parser Lm Chat Open Router Twitter/X LLM Chain Anthropic Airtable

Details

Trigger Automatic trigger
Nodes 51
Apps 6
Views 297
Downloads 158

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)

/

When clicking ‘Test workflow’

Manual Trigger

#1

Filter

Filter

#2

Structured Output Parser

Output Parser Structured

#3

Perplexity

Lm Chat Open Router

#4

Filter1

Filter

#5

Extract Structured Data

Information Extractor

#6

Research URL

LLM Chain

#7

Extract URL

LLM Chain

#8

Merge Extracted Data

Merge

#9

Split TC Articles

Split Out

#10

TC HTML Parser

HTML Page

#11

Split VB Articles

Split Out

#12

VB HTML Parser

HTML Page

#13

Venturebeat (VB)

HTTP Request

#14

Techcrunch (TC)

HTTP Request

#15

Claude 3.5 Sonnet

Lm Chat Anthropic

#16

Claude 3.5 Haiku

Lm Chat Anthropic

#17

Collect Data

Set

#18

Airtable

Airtable

#19

Sticky Note1

Sticky Note

#20

Sticky Note3

Sticky Note

#21

Sticky Note4

Sticky Note

#22

Sticky Note5

Sticky Note

#23

Sticky Note6

Sticky Note

#24

Sticky Note7

Sticky Note

#25

Sticky Note8

Sticky Note

#26

Sticky Note9

Sticky Note

#27

Sticky Note10

Sticky Note

#28

Sticky Note11

Sticky Note

#29

Sticky Note12

Sticky Note

#30

Sticky Note2

Sticky Note

#31

Auto-fixing Output Parser

Output Parser Autofixing

#32

Extract Structured JSON

Output Parser Structured

#33

Sticky Note13

Sticky Note

#34

Prompts

Set

#35

Deep Research

HTTP Request

#36

Pick data (Perplexity)

Set

#37

Pick data (jina)

Set

#38

Sticky Note

Sticky Note

#39

When Executed by Another Workflow

Execute Workflow Trigger

#40

JINA Deep Search

HTTP Request

#41

Write Results to Airtable

Airtable

#42

Extract Structured Data

LLM Chain

#43

Sticky Note14

Sticky Note

#44

Route to Deep Research

Execute Workflow

#45

Parse TC XML

Xml

#46

Parse VB XML

Xml

#47

Sticky Note15

Sticky Note

#48

Claude 3.5 Sonnet

Lm Chat Anthropic

#49

Get Funding Article HTML for scraping (TC)

HTTP Request

#50

Get Funding Article HTML for scraping (VB)

HTTP Request

#51

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