Startup funding research automation with Claude, Perplexity AI, and Airtable

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Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

Startup Funding Research Automation with Claude, Perplexity AI, and Airtable How it works This intelligent workflow automatically discovers and analyzes recently funded startups by: 1. Monitoring m...

Best for

Market Research automation workflows
AI Summarization automation workflows
advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.manualtrigger, n8n-nodes-base.filter, @n8n/n8n-nodes-langchain.outputparserstructured, @n8n/n8n-nodes-langchain.lmchatopenrouter, @n8n/n8n-nodes-langchain.informationextractor, @n8n/n8n-nodes-langchain.chainllm, n8n-nodes-base.merge, n8n-nodes-base.splitout

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Julian Kaiser.

Original n8n.io source

1.1 Workflow description

Title: Startup funding research automation with Claude, Perplexity AI, and Airtable
Workflow name: Startup funding research automation with Claude, Perplexity AI, and Airtable

Startup Funding Research Automation with Claude, Perplexity AI, and Airtable

How it works

This intelligent workflow automatically discovers and analyzes recently funded startups by:

Monitoring multiple news sources (TechCrunch and VentureBeat) for funding announcements
Using AI to extract key funding details (company name, amount raised, investors)
Conducting automated deep research on each company through perplexity deep research or jina deep search.
Organizing all findings into a structured Airtable database for easy access and analysis

Set up steps (10-15 minutes)

Connect your news feed sources (TechCrunch and VentureBeat). Could be extended. These were easy to scrape and this data can be expensive.
Set up your AI service credentials (Claude and Perplexity or jina which has generous free tier)
Connect your Airtable account and create a base with appropriate fields (can be imported from my base) or see structure below. Airtable Base

Structure Funding Round Base

Field Name	Data Type	Description
website_url	String	URL of the company website
company_name	String	Name of the company
funding_round	String	The funding stage or round (e.g., Series A, Seed, etc.)
funding_amount	Number	The amount of funding received
lead_investor	String	The primary investor leading the funding round
market	String	The market or industry sector the company operates in
participating_investors	String	List of other investors participating in the funding round
press_release_url	String	URL to the press release about the funding
evaluation	Number	The company's valuation

Structure Company Deep Research Base

Field Name	Data Type	Description
website_url	String	URL of the company website
company_name	String	Name of the company
funding_round	String	The funding stage or round (e.g., Series A, Seed, etc.)
funding_amount	Number	The amount of funding received
currency	String	Currency of the funding amount
announcement_date	String	Date when the funding was announced
lead_investor	String	The primary investor leading the funding round
participating_investors	String	List of other investors participating in the funding round
industry	String	The industry sectors the company operates in
company_description	String	Description of the company's business
hq_location	String	Company headquarters location
founding_year	Number	Year the company was founded
founder_names	String	Names of the company founders
ceo_name	String	Name of the company CEO
employee_count	Number	Number of employees at the company
total_funding	Number	Total funding amount received to date
total_funding_currency	String	Currency of total funding
funding_purpose	String	Purpose or use of the funding
business_model	String	Company's business model
valuation	Object	Company valuation information
previous_rounds	Object	Information about previous funding rounds
source_urls	String	Source URLs for the funding information
original_report	String	Original report text about the funding
market	String	The market the company operates in
press_release_url	String	URL to the press release about the funding
evaluation	Number	The company's valuation

Notes

I found that by using perplexity via open router, we lose access to the sources, as they are not stored in the same location as the report itself so I opted to use perplexity API via HTTP node.

For using perplexity and or jina you have to configure header auth as described in Header Auth - n8n Docs

What you can learn

How to scrape data using sitemaps
How to extract strucutred data from unstructured text
How to execute parts of the workflow as subworkflow
How to use deep research in a practical scenario
How to define more complex JSON schemas

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - When clicking ‘Test workflow’

Type / Role: n8n-nodes-base.manualTrigger - manualTrigger
Config choices: Version 1

Block 2 - Filter

Type / Role: n8n-nodes-base.filter - filter
Config choices: Version 2.2

Block 3 - Structured Output Parser

Type / Role: @n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices: Version 1.2

Block 4 - Perplexity

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenRouter - lmChatOpenRouter
Config choices: Version 1

Block 5 - Filter1

Type / Role: n8n-nodes-base.filter - filter
Config choices: Version 2.2

Block 6 - Extract Structured Data

Type / Role: @n8n/n8n-nodes-langchain.informationExtractor - informationExtractor
Config choices: Version 1

Block 7 - Research URL

Type / Role: @n8n/n8n-nodes-langchain.chainLlm - chainLlm
Config choices: Version 1.5

Block 8 - Extract URL

Type / Role: @n8n/n8n-nodes-langchain.chainLlm - chainLlm
Config choices: Version 1.5

Block 9 - Merge Extracted Data

Type / Role: n8n-nodes-base.merge - merge
Config choices: Version 3

Block 10 - Split TC Articles

Type / Role: n8n-nodes-base.splitOut - splitOut
Config choices: Version 1

Block 11 - TC HTML Parser

Type / Role: n8n-nodes-base.html - html
Config choices: Version 1.2

Block 12 - Split VB Articles

Type / Role: n8n-nodes-base.splitOut - splitOut
Config choices: Version 1

Block 13 - VB HTML Parser

Type / Role: n8n-nodes-base.html - html
Config choices: Version 1.2

Block 14 - Venturebeat (VB)

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.2

Block 15 - Techcrunch (TC)

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.2

Block 16 - Claude 3.5 Sonnet

Type / Role: @n8n/n8n-nodes-langchain.lmChatAnthropic - lmChatAnthropic
Config choices: Version 1.2

Block 17 - Claude 3.5 Haiku

Type / Role: @n8n/n8n-nodes-langchain.lmChatAnthropic - lmChatAnthropic
Config choices: Version 1.2

Block 18 - Collect Data

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 19 - Airtable

Type / Role: n8n-nodes-base.airtable - airtable
Config choices: Version 2.1

Block 20 - Sticky Note1

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 21 - Sticky Note3

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 22 - Sticky Note4

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 23 - Sticky Note5

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 24 - Sticky Note6

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Showing the first 24 of 51 workflow blocks. Download the JSON for the full node graph.

3. Summary Table

Workflow	Startup funding research automation with Claude, Perplexity AI, and Airtable
Complexity	advanced
Nodes	51
Categories	Market Research, AI Summarization
Author	Julian Kaiser
Published	08 Mar 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/3107/3107.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source Market Research workflows AI Summarization workflows

Frequently asked questions

What does Startup funding research automation with Claude, Perplexity AI, and Airtable do?

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Market Research, AI Summarization use case.

Julian Kaiser

11 workflows

Nodes

n8n-nodes-base.manualtrigger n8n-nodes-base.filter @n8n/n8n-nodes-langchain.outputparserstructured @n8n/n8n-nodes-langchain.lmchatopenrouter @n8n/n8n-nodes-langchain.informationextractor @n8n/n8n-nodes-langchain.chainllm n8n-nodes-base.merge n8n-nodes-base.splitout

Complexity

advanced

Published 08 Mar 2025

Likes 0

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Install path: /data/workflows/3107/3107.json

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Startup funding research automation with Claude, Perplexity AI, and Airtable

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

Startup Funding Research Automation with Claude, Perplexity AI, and Airtable

How it works

Set up steps (10-15 minutes)

Structure Funding Round Base

Structure Company Deep Research Base

Notes

What you can learn

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - When clicking ‘Test workflow’

Block 2 - Filter

Block 3 - Structured Output Parser

Block 4 - Perplexity

Block 5 - Filter1

Block 6 - Extract Structured Data

Block 7 - Research URL

Block 8 - Extract URL

Block 9 - Merge Extracted Data

Block 10 - Split TC Articles

Block 11 - TC HTML Parser

Block 12 - Split VB Articles

Block 13 - VB HTML Parser

Block 14 - Venturebeat (VB)

Block 15 - Techcrunch (TC)

Block 16 - Claude 3.5 Sonnet

Block 17 - Claude 3.5 Haiku

Block 18 - Collect Data

Block 19 - Airtable

Block 20 - Sticky Note1

Block 21 - Sticky Note3

Block 22 - Sticky Note4

Block 23 - Sticky Note5

Block 24 - Sticky Note6

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions