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Automated daily AI news digest: scrape, categorize & save to Google Sheets

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Automated daily AI news digest: scrape, categorize & save to Google Sheets preview
Open on n8n.io

Important notice

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

1. Workflow Overview

This workflow is designed to automatically process AI news emails, extract and summarize articles, categorize them, and store the results in a structured Google Sheet for daily tracking and insight...

Best for

  • Document Extraction automation workflows
  • AI Summarization automation workflows
  • advanced n8n builders looking for reusable templates

Tools used

@n8n/n8n-nodes-langchain.lmchatgooglegemini, n8n-nodes-scrapegraphai.scrapegraphaitool, n8n-nodes-base.splitinbatches, @n8n/n8n-nodes-langchain.lmchatopenai, n8n-nodes-base.gmail, n8n-nodes-base.markdown, @n8n/n8n-nodes-langchain.agent, n8n-nodes-base.code

Source and attribution

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

Original n8n.io source

1.1 Workflow description

Title
Automated daily AI news digest: scrape, categorize & save to Google Sheets
Workflow name
Automated daily AI news digest: scrape, categorize & save to Google Sheets

This workflow is designed to automatically process AI news emails, extract and summarize articles, categorize them, and store the results in a structured Google Sheet for daily tracking and insights.

This automated workflow processes a daily AI newsletter from AlphaSignal, extracting individual articles, summarizing them, categorizing them, and saving the results to a Google Sheet.


Key Features

1. ✅ Fully Automated Daily News Pipeline

No manual work is required — the workflow runs autonomously every time a new email arrives. This eliminates repetitive human tasks such as opening, reading, and summarizing newsletters.

2. ✅ Cross-AI Model Integration

It combines multiple AI systems:

  • Google Gemini and OpenAI GPT-5 Mini for natural language processing and categorization.
  • Scrapegraph AI for external web scraping and summarization.

This multi-model approach enhances accuracy and flexibility.

3. ✅ Accurate Content Structuring

The workflow transforms unstructured email text into clean, structured JSON data, ensuring reliability and easy export or reuse.

4. ✅ Multi-Language Support

The summaries are generated in Italian, which is ideal for local or internal reporting, while the metadata and logic remain in English — enabling global adaptability.

5. ✅ Scalable and Extensible

New newsletters, categories, or destinations (like Notion, Slack, or a database) can be added easily without changing the core logic.

6. ✅ Centralized Knowledge Repository

By appending to Google Sheets, the team can:

  • Track daily AI developments at a glance.
  • Filter or visualize trends across categories.
  • Use the dataset for further analysis or content creation.
7. ✅ Error-Resilient and Maintainable

The JSON validation and loop-based design ensure that if a single article fails, the rest continue to process smoothly.


How it Works

  1. Email Trigger & Processing: The workflow is automatically triggered when a new email arrives from [email protected]. It retrieves the full email content and converts its HTML body into clean Markdown format for easier parsing.

  2. Article Extraction & Scraping: A LangChain Agent, powered by Google Gemini, analyzes the newsletter's Markdown text. Its task is to identify and split the content into individual articles. For each article it finds, it outputs a JSON object containing the title, URL, and an initial summary. Crucially, the agent uses the "Scrape" tool to visit each article's URL and generate a more accurate summary in Italian based on the full page content.

  3. Data Preparation & Categorization: The JSON output from the previous step is validated and split into individual data items (one per article). Each article is then processed in a loop:

    • Categorization: An OpenAI model analyzes the article's title and summary, assigning it to the most relevant pre-defined category (e.g., "LLM & Foundation Models," "AI Automation & WF").
    • URL Shortening: The article's link is sent to the CleanURI API to generate a shortened URL.
  4. Data Storage: Finally, for each article, a new row is appended to a specified Google Sheet. The row includes the current date, the article's title, the shortened link, the Italian summary, and its assigned category.


Set up Steps

To implement this workflow, you need to configure the following credentials and nodes in n8n:

  1. Email Credentials: Set up a Gmail OAuth2 credential (named "Gmail account" in the workflow) to allow n8n to access and read emails from the specified inbox.

  2. AI Model APIs:

    • Google Gemini: Configure the "Google Gemini(PaLM)" credential with a valid API key to power the initial article extraction and scraping agent.
    • OpenAI: Configure the "OpenAi account (Eure)" credential with a valid API key to power the article categorization step.
  3. Scraping Tool: Set up the ScrapegraphAI account credential with its required API key to enable the agent to access and scrape content from the article URLs.

  4. Google Sheets Destination: Configure the "Google Sheets account" credential via OAuth2. You must also specify the exact Google Sheet ID and sheet name (tab) where the processed article data will be stored.

  5. Activation: Once all credentials are tested and correctly configured, the workflow can be activated. It will then run automatically upon receiving a new newsletter from the specified sender.


Need help customizing?

Contact me for consulting and support or add me on Linkedin.

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 - Google Gemini Chat Model

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

Block 2 - Scrape

Type / Role
n8n-nodes-scrapegraphai.scrapegraphAiTool - scrapegraphAiTool
Config choices
Version 1

Block 3 - Loop Over Items

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

Block 4 - OpenAI Chat Model

Type / Role
@n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices
Version 1.3

Block 5 - Get email

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

Block 6 - Convert HTML to MD

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

Block 7 - Scrape Agent

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 3

Block 8 - Validate Json

Type / Role
n8n-nodes-base.code - code
Config choices
Version 2

Block 9 - Categorization Chain

Type / Role
@n8n/n8n-nodes-langchain.chainLlm - chainLlm
Config choices
Version 1.7

Block 10 - Short url

Type / Role
n8n-nodes-base.httpRequest - httpRequest
Config choices
Version 4.3

Block 11 - Add article to sheet

Type / Role
n8n-nodes-base.googleSheets - googleSheets
Config choices
Version 4.7

Block 12 - Sticky Note

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

Block 13 - Sticky Note3

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

Block 14 - Sticky Note4

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

Block 15 - Sticky Note6

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

3. Summary Table

Workflow Automated daily AI news digest: scrape, categorize & save to Google Sheets
Complexity advanced
Nodes 15
Categories Document Extraction, AI Summarization
Author Davide
Published 18 Nov 2025

4. Reproducing the Workflow from Scratch

  1. 1. Download the workflow JSON

    Use the JSON export at /data/workflows/10952/10952.json as the source template for this automation.

  2. 2. Import the template into n8n

    Open n8n, import the downloaded JSON, and review each node before activating the workflow.

  3. 3. Configure credentials and variables

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

  4. 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. 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.

Frequently asked questions

What does Automated daily AI news digest: scrape, categorize & save to Google Sheets do?

This workflow is designed to automatically process AI news emails, extract and summarize articles, categorize them, and store the results in a structured Google Sheet for daily tracking and insight...

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 Document Extraction, AI Summarization use case.