Smart RSS news alert system with DeepSeek AI and Slack notifications

Name: Smart RSS news alert system with DeepSeek AI and Slack notifications
Availability: InStock
Rating: 4.5 (59 reviews)
Author: Țugui Dragoș

$20/month : Unlimited workflows

2500 executions/month

Try free

THE #1 IN WEB SCRAPING

Scrape any website without limits

Try free

HOSTINGER 🎉 Early Black Friday Deal
DISCOUNT 20%

Self-hosted n8n

Unlimited workflows - from $4.99/mo

Try free

#1 hub for scraping, AI & automation

6000+ actors - $5 credits/mo

Try free

How it works

This workflow fetches articles from any RSS feed, processes them with an AI model (DeepSeek), and sends only the most relevant alerts directly to Slack.

Normalizes and deduplicates RSS items
Extracts article text and cleans HTML
Summarizes and classifies with AI (sentiment + flags)
Filters out irrelevant news
Sends real-time alerts to your Slack channel

Setup steps

Add your Slack Bot Token (via Slack API)
Add your DeepSeek API Key
Import this workflow into n8n
Deploy and start receiving smart news alerts in Slack

Use case

Perfect for tracking AI, startups, finance, and tech industry news without the noise.

Slack Preview

Țugui Dragoș

0 workflows

Nodes

set gmail telegram agent google-gemini

Complexity

intermediate

Published 02 Sept 2025

Likes 0

View on n8n.io Download Workflow

✨

Share Your Workflow

Have a great workflow to share? Join the n8n Creator Hub and help the community!

Submit Your Template How to Submit

Related Workflows

Draft and manage academic research papers with GPT-4 and Pinecone

## How It Works This workflow automates academic research processing by routing queries through specialized AI models while maintaining contextual memory. Designed for researchers, faculty, and graduate students, it solves the challenge of managing multiple AI models for different research tasks while preserving conversation context across sessions. The system accepts research queries via webhook, stores them in vector databases for semantic search, and intelligently routes requests to appropriate AI models (OpenAI, Anthropic Claude, or NVIDIA NIM). Results are consolidated, formatted, and delivered via email with full citation tracking. The workflow maintains conversation history using Pinecone vector storage, enabling follow-up queries that reference previous interactions. This eliminates manual model switching, context loss, and repetitive credential management—streamlining research workflows from literature review to hypothesis generation. ## Setup Steps 1. Configure Pinecone credentials 2. Add OpenAI API key for GPT-4 access and embeddings 3. Set up Anthropic Claude API credentials for advanced reasoning 4. Configure NVIDIA NIM API key for specialized academic models 5. Connect Google Sheets for query logging and result tracking 6. Set Gmail OAuth credentials for automated result delivery 7. Configure webhook URL for query submission endpoint ## Prerequisites Active accounts and API keys for Pinecone, OpenAI ## Use Cases Literature review automation with semantic paper discovery. ## Customization Modify AI model selection logic for domain-specific optimization. ## Benefits Reduces research processing time by 60% through automated routing.

View

Scrape Trustpilot reviews 📊 with ScrapegraphAI and OpenAI Reputation analysis

This workflow automates the **collection, analysis, and reporting of Trustpilot reviews** for a specific company, transforming unstructured customer feedback into **structured insights and actionable intelligence**. --- ### Key Advantages #### 1. ✅ End-to-End Automation The entire process—from scraping reviews to delivering a polished management report—is fully automated, eliminating manual data collection and analysis . #### 2. ✅ Structured Insights from Unstructured Data The workflow transforms raw, unstructured review text into structured fields and standardized sentiment categories, making analysis reliable and repeatable. #### 3. ✅ Company-Level Reputation Intelligence Instead of focusing on individual products, the analysis evaluates the **overall brand, service quality, customer experience, and operational performance**, which is critical for leadership and strategic teams. #### 4. ✅ Action-Oriented Outputs The AI-generated report goes beyond summaries by: * Identifying reputational risks * Highlighting improvement opportunities * Proposing concrete actions with priorities, effort estimates, and KPIs #### 5. ✅ Visual & Executive-Friendly Reporting Automatic sentiment charts and structured executive summaries make insights immediately understandable for non-technical stakeholders. #### 6. ✅ Scalable and Configurable * Easily adaptable to different companies or review volumes * Page limits and batching protect against rate limits and excessive API usage #### 7. ✅ Cross-Team Value The output is tailored for multiple internal teams: * Management * Marketing * Customer Support * Operations * Product & UX --- ### Ideal Use Cases * Brand reputation monitoring * Voice-of-the-customer programs * Executive reporting * Customer experience optimization * Competitive benchmarking (by reusing the workflow across brands) --- ### **How It Works** This workflow automates the complete process of scraping Trustpilot reviews, extracting structured data, analyzing sentiment, and generating comprehensive reports. The workflow follows this sequence: 1. **Trigger & Configuration**: The workflow starts with a manual trigger, allowing users to set the target company URL and the number of review pages to scrape. 2. **Review Scraping**: An HTTP request node fetches review pages from Trustpilot with pagination support, extracting review links from the HTML content. 3. **Review Processing**: The workflow processes individual review pages in batches (limited to 5 reviews per execution for efficiency). Each review page is converted to clean markdown using ScrapegraphAI. 4. **Data Extraction**: An information extractor using OpenAI's GPT-4.1-mini model parses the markdown to extract structured review data including author, rating, date, title, text, review count, and country. 5. **Sentiment Analysis**: Another OpenAI model performs sentiment classification on each review text, categorizing it as Positive, Neutral, or Negative. 6. **Data Aggregation**: Processed reviews are collected and compiled into a structured dataset. 7. **Analytics & Visualization**: - A pie chart is generated showing sentiment distribution - A comprehensive reputation analysis report is created using an AI agent that evaluates company-level insights, recurring themes, and provides actionable recommendations 8. **Reporting & Delivery**: The analysis is converted to HTML format and sent via email, providing stakeholders with immediate insights into customer feedback and company reputation. ## **Set Up Steps** To configure and run this workflow: 1. **Credential Setup**: - Configure OpenAI API credentials for the chat models and information extraction - Set up ScrapegraphAI credentials for webpage-to-markdown conversion - Configure Gmail OAuth2 credentials for email notifications 2. **Company Configuration**: - In the "Set Parameters" node, update `company_id` to the target Trustpilot company URL - Adjust `max_page` to control how many review pages to scrape 3. **Review Processing Limits**: - The "Limit" node restricts processing to 5 reviews per execution to manage API costs and processing time - Adjust this value based on your needs and OpenAI usage limits 4. **Email Configuration**: - Update the "Send a message" node with the recipient email address - Customize the email subject and content as needed 5. **Analysis Customization**: - Modify the prompt in the "Company Reputation Analyst" node to tailor the report format - Adjust sentiment analysis categories if different classification is needed 6. **Execution**: - Click "Test workflow" to execute the manual trigger - Monitor execution in the n8n editor to ensure all API calls succeed - Check the configured email inbox for the generated report **Note**: Be mindful of API rate limits and costs associated with OpenAI and ScrapegraphAI services when processing large numbers of reviews. The workflow includes a 5-second delay between paginated requests to comply with Trustpilot's terms of service. --- 👉 [Subscribe to my new **YouTube channel**](https://youtube.com/@n3witalia). Here I’ll share videos and Shorts with practical tutorials and **FREE templates for n8n**. [![image](https://n3wstorage.b-cdn.net/n3witalia/youtube-n8n-cover.jpg)](https://youtube.com/@n3witalia) --- ### **Need help customizing?** [Contact me](mailto:[email protected]) for consulting and support or add me on [Linkedin](https://www.linkedin.com/in/davideboizza/).

View

Monitor multi-city weather with OpenWeatherMap, GPT-4o-mini, and Discord

## Weather Monitoring Across Multiple Cities with OpenWeatherMap, GPT-4o-mini, and Discord This workflow provides an automated, intelligent solution for global weather monitoring. It goes beyond simple data fetching by calculating a custom "Comfort Index" and using AI to provide human-like briefings and activity recommendations. Whether you are managing remote teams or planning travel, this template centralizes complex environmental data into actionable insights. ## Who’s it for - **Remote Team Leads:** Keep an eye on environmental conditions for team members across different time zones. - **Frequent Travelers & Event Planners:** Monitor weather risks and comfort levels for multiple destinations simultaneously. - **Smart Home/Life Enthusiasts:** Receive daily morning briefings on air quality and weather alerts directly in Discord. ## How it works 1. **Schedule Trigger:** The workflow runs every 6 hours (customizable) to ensure data is up to date. 2. **Data Collection:** It loops through a list of cities, fetching current weather, 5-day forecasts, and Air Quality Index (AQI) data via the **OpenWeatherMap node** and **HTTP Request node**. 3. **Smart Processing:** A **Code node** calculates a "Comfort Index" (based on temperature and humidity) and flags specific alerts (e.g., extreme heat, high winds, or poor AQI). 4. **AI Analysis:** The **OpenAI node** (using GPT-4o-mini) analyzes the aggregated data to compare cities and recommend the best location for outdoor activities. 5. **Conditional Routing:** An **If node** checks for active weather alerts. Urgent alerts are routed to a specific Discord notification, while routine briefings are sent normally. 6. **Archiving:** All processed data is appended to **Google Sheets** for historical tracking and future analysis. ## How to set up 1. **Credentials:** Connect your OpenWeatherMap, OpenAI, Discord (Webhook), and Google Sheets accounts. 2. **Locations:** Open the **'Set Monitoring Locations'** node and edit the JSON array with the cities, latitudes, and longitudes you wish to track. 3. **Google Sheets:** Configure the **'Log to Google Sheets'** node with your specific Spreadsheet ID and Sheet Name. 4. **Discord:** Ensure your Webhook URL is correctly pasted into the **Discord nodes**. ## Requirements - **OpenWeatherMap API Key** (Free tier is sufficient). - **OpenAI API Key** (Configured for GPT-4o-mini). - **Discord Webhook URL**. - **Google Sheet** with headers ready for logging. ## How to customize - **Adjust Alert Thresholds:** Modify the logic in the 'Process and Analyze Data' Code node to change what triggers a "High Wind" or "Extreme Heat" alert. - **Refine AI Persona:** Edit the System Prompt in the 'AI Weather Analysis' node to change the tone or focus of the weather briefing. - **Change Frequency:** Adjust the Schedule Trigger to run once a day or every hour depending on your needs.

View

👨‍💻

Need Custom Automation?

N8N Automation Expert

Specialized in N8N automation, I design custom workflows that connect your tools and automate your processes.