Workflow Templates

disclaimer: This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Quick Summary This template automates the creation of YouTube Shorts scripts. Simply send a YouTube video URL to a Telegram bot, and this workflow will use AI (Google Gemini) to generate a script optimized for Shorts and send it back to you. It streamlines your content creation process by eliminating the manual work of transcribing and scriptwriting. Target Audience & Problem Solved This template is ideal for: YouTube Content Creators Social Media Marketers Anyone looking to efficiently repurpose - - video content It solves the following problems: Quickly creating engaging short-form video content from existing long-form videos. Drastically reducing the time spent on video transcription, summarization, and scriptwriting. Enabling content idea generation on the go, even from a smartphone without access to a PC. Workflow Overview This workflow automatically generates a script for YouTube Shorts using AI (Google Gemini) from a YouTube video URL received via Telegram, and then sends the result back to Telegram. The process is as follows: Receive URL: A Telegram bot receives a YouTube video URL from a user. Get Transcript: It uses the community node n8n-nodes-supadata to retrieve the video's transcript via the Supadata service. Generate Script: Based on the retrieved transcript, Google Gemini creates a script (title and body) optimized for a YouTube Shorts video. Send Result: The generated script is sent back to the user who sent the original URL via Telegram. How to Use Prerequisites: Install the n8n-nodes-supadata community node as described below. Register your API keys for Telegram, Supadata, and Google Gemini as credentials in n8n. Set the appropriate credentials in each node within the workflow. For Telegram, create your bot with BotFarther. Execution: Activate the workflow. Send a YouTube video URL to your configured Telegram bot. Confirmation: After a short while, the workflow will run automatically, and you will receive the completed script from the Telegram bot. Customization Guide You can tailor this template to your specific needs: Modify the Prompt: Edit the prompt in the Google Gemini node to change the style of the generated script (e.g., make it more casual, use a specific tone, include emojis). Change the AI Model: You can switch to other AI models like OpenAI. Simply add or replace the corresponding n8n node. Change the Notification Channel: Replace the Telegram node with a Discord or Slack node to send the results to a different platform. Community Node Installation This workflow requires the n8n-nodes-supadata community node. Please install it using the following steps. Installation from the n8n UI (Recommended) Navigate to Settings > Community Nodes in your n8n interface. Click on Install. Enter n8n-nodes-supadata in the input field and click the Install button.

This automated n8n workflow continuously tracks real-time flight fare changes by querying airline APIs (e.g., Amadeus, Skyscanner). It compares new prices with historical fares and sends instant notifications to users when a fare drop is detected. All tracked data is structured and logged for audit and analysis. Key Insights Works post-booking to track price fluctuations for booked routes. Supports multiple fare sources for improved accuracy and comparison. Users are notified instantly via email, SMS, or Slack for high-value drops. Historical pricing data is stored for trend analysis and refund eligibility checks. Can be extended to monitor specific routes or apply airline-specific refund rules. Workflow Process Schedule Trigger Initiates the fare check every 6 hours. Fetch Flight Fare Data Queries APIs (Amadeus, Skyscanner) for current flight fares. Get Tracked Bookings Retrieves tracked routes from the internal database. Compare Fares Detects price drops compared to original booking fares. Update Fare History Table Logs the new fare and timestamp into the fare_tracking table. Classify Drops Determines priority based on absolute and percentage savings. Notify Users Email Alerts: For all medium/high priority drops. SMS Alerts: For savings > \$100 or >15%. Slack Notifications: For internal alerts and rebooking suggestions. Log Activity Stores all sync actions and notifications in fare_alert_logs. Usage Guide Import** the workflow into your n8n instance. Set up** API credentials for Amadeus and Skyscanner. Configure email, SMS (Twilio), and Slack credentials. Update the booking database with valid records (with route, fare, timestamp). Set schedule frequency (e.g., every 6 hours). Review logs regularly to monitor fare alert activity and system health. Prerequisites Valid accounts and credentials for: Amadeus API Skyscanner API SendGrid (or SMTP) for email Twilio for SMS Slack workspace & bot token PostgreSQL or MySQL database for fare tracking Tracked booking dataset (with routes, fares, and user contacts) Customization Options Adjust alert thresholds in the comparison logic (e.g., trigger only if fare drops > \$50 or >10%). Add new notification channels (e.g., WhatsApp, Telegram). Extend logic to track multi-leg or roundtrip fares. Integrate airline refund APIs (where supported) to auto-initiate refund or credit requests. Excel Output Columns When exporting or logging fare tracking data to Excel or CSV, use the following structure: | flight\_number | airline | departure | arrival | departure\_time | arrival\_time | current\_fare | route | timestamp | | -------------- | --------------- | ---------------------------- | ------------------------- | ------------------------- | ------------------------- | ------------- | ------- | ------------------------ | | AT5049 | Royal Air Maroc | John F Kennedy International | Los Angeles International | 2025-07-21T06:00:00+00:00 | 2025-07-21T08:59:00+00:00 | 235 | JFK-LAX | 2025-07-21T13:04:14.000Z | | BA1905 | British Airways | John F Kennedy International | Los Angeles International | 2025-07-21T06:00:00+00:00 | 2025-07-21T08:59:00+00:00 | 479 | JFK-LAX | 2025-07-21T13:04:14.000Z |

📱🤖 Create Stunning AI Images Directly from WhatsApp with Gemini This workflow transforms your WhatsApp into a personal AI image generation studio. Simply send a text message with your idea, and this bot will use the advanced prompt engineering capabilities of Gemini 2.5 Pro to craft a detailed, artistic prompt. It then uses Gemini 2.0 Flash to generate a high-quality image from that prompt and sends it right back to your chat. It's a powerful yet simple way to bring your creative ideas to life, all from the convenience of your favorite messaging app\! What this workflow does Listens for WhatsApp Messages: The workflow starts automatically when you send a message to your connected WhatsApp number. Enhances Your Idea with AI: It takes your basic text (e.g., "a knight on a horse") and uses Gemini 2.5 Pro to expand it into a rich, detailed prompt perfect for image generation (e.g., "A cinematic, full-body shot of a stoic knight in gleaming, ornate silver armor, riding a powerful black warhorse through a misty, ancient forest. The scene is lit by ethereal morning sunbeams piercing the canopy, creating dramatic volumetric lighting and long shadows. Photorealistic, 8K, ultra-detailed, award-winning fantasy concept art."). Generates a Unique Image: It sends this enhanced prompt to the Google Gemini 2.0 Flash image generation API. Prepares the Image: The API returns the image in Base64 format, and the workflow instantly converts it into a binary file. Sends it Back to You: The final, high-quality image is sent directly back to you in the same WhatsApp chat. Nodes Used 🟢 WhatsApp Trigger: The entry point that listens for incoming messages. 🧠 LangChain Chain (LLM): Uses Gemini 2.5 Pro for advanced prompt engineering. ➡️ HTTP Request: Calls the Google Gemini 2.0 Flash API to generate the image. 🔄 Convert to File: Converts the Base64 image data into a sendable file format. 💬 WhatsApp: Sends the final image back to the user. Prerequisites To use this workflow, you will need: An n8n instance. A WhatsApp Business Account connected to n8n. You can find instructions on how to set this up in the n8n docs. A Google Gemini API Key. You can get one for free from Google AI Studio. How to use this workflow Get your Google Gemini API Key: Visit the Google AI Studio and create a new API key. Configure the Gemini 2.5 Pro Node: In the n8n workflow, select the Gemini 2.5 Pro node. Under 'Connect your account', click 'Create New' to add a new credential. Paste your Gemini API key from the previous step and save. Configure the Generate Image (HTTP Request) Node: Select the Generate Image node. In the properties panel on the right, find the Query Parameters section. In the 'Value' field for the key parameter, replace "Your API Key" with your actual Google Gemini API Key. Connect WhatsApp: Select the WhatsApp Trigger node. Follow the instructions to connect your WhatsApp Business Account credential. If you haven't created one, the node will guide you through the process. Activate and Test: Save the workflow using the button at the top right. Activate the workflow using the toggle switch. Send a message to your connected WhatsApp number (e.g., "A futuristic city in the style of Van Gogh"). The bot will process your request and send a stunning AI-generated image right back to you\!

Try It Out! This n8n template helps you create SEO-optimized Blog Posts for your businesses website or for personal use. Whether you're managing a business or helping local restaurants improve their digital presence, this workflow helps you build SEO-Optimized Blog Posts in seconds using Google Autocomplete and People Also Ask (SerpAPI). Who Is It For? This is helpful for people looking to SEO Optimize either another person's website or their own. How It Works? You start with a list of blog inspirations in Google Sheets (e.g., “Best Photo Session Spots”). The workflow only processes rows where the “Status” column is not marked as “done”, though you can remove this condition if you’d like to process all rows each time. The workflow pulls Google Autocomplete suggestions and PAA questions using: A custom-built SEO API I deployed via Render (for Google Autocomplete + PAA), SerpAPI (for additional PAA data). These search insights are merged. For example, if your blog idea is “Photo Session Spots,” the workflow gathers related Google search phrases and questions users are asking. Then, GPT-4 is used to draft a full blog post based on this data. The finished post is saved back into your Google Sheet. How To Use Fill out the “Blog Inspiration” column in your Google Sheet with the topics you want to write about. Update the OpenAI prompt in the ChatGPT node to match your tone or writing style. (Tip: Add a system prompt with context about your business or audience.) You can trigger this manually, or replace it with a cron schedule, webhook, or other event. Requirements A SerpAPI account to get PAA An OpenAI account for ChatGPT Access to Google Sheets and n8n How To Set-Up? Your Google Sheet should have three columns: "Blog Inspiration", "Status" → set this to “done” when a post has been generated, "Blog Draft" → this is automatically filled by the workflow. To use the SerpAPI HTTP Request node: 1. Drag in an HTTP Request node, 2. Set the Method and URL depending on how you're using SerpAPI: Use POST to run the actor live on each request. Use GET to fetch from a static dataset (cheaper if reusing the same data). 3. Add query parameters for your SerpAPI key and input values. 4. Test the node. Refer to this n8n documentation for more help! https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.toolserpapi/. The “Autocomplete” node connects to a custom web service I built and deployed using Render. I wrote a Python script (hosted on GitHub) that pulls live Google Autocomplete suggestions and PAA questions based on any topic you send. This script was turned into an API and deployed as a public web service via Render. Anyone can use it by sending a POST request to: https://seo-api2.onrender.com/get-seo-data (the URL is already in the node). Since this is hosted on Render’s free tier, if the service hasn’t been used in the past ~15 minutes, it may “go to sleep.” When that happens, the first request can take 10–30 seconds to respond while it wakes up. Happy Automating!

Workflow Overview: Extract text from image using AI is worth because you need no code. It incorporates Google Gemini 2.0 Flash model for important text extraction from image. If you code without AI, you have to use multiple condition and may cause a lot of bug but with Google Gemini, you don't need any coding and if the Pay Slip is different, Gemini will extract it automatically. Workflow description: User uses Line Messaging API to send Pay Slip image or message to the chatbot, create Line Business ID from here: Line Business Classify the message which is image or text If the message is Pay Slip image, it will process using Gemini 2.0 Flash EXP and extract important information and response in JSON format without coding by using the following prompt: Analyze image and then return in JSON Response that has the only following value: Status, From, To, Date, Amount To get Google AI Studio API Key, you can find from the following link: Google AI Studio API Key Create Google Sheets which include the fileds (Status, From, To, Date, Amount) that we have created related to the AI prompt Google Sheets as the following example: If the message is text, it will process using Gemini 2.0 Flash EXP model as the AI Assistant else if the message is image, it will extract the important fields then reply to the User and insert into Google Sheets Key Features: Extract text from image with No Code** Without N8N, we have to write code to extract text from image, but with N8N and Google Gemini 2.0 Flash EXP together, we don't need to code and it will process all slip vendors or other document vendors. Multipurpose Chatbot** this chatbot accept both text and image so we don't have to create many chatbot accounts Reduce human error** this workflow let any officer to verify document status when the job ends Note: You can change the information by changing your prompt and also Google Sheets Column names relatively.

This workflow dynamically chooses between two new powerful Anthropic models — Claude Opus 4 and Claude Sonnet 4 — to handle user queries, based on their complexity and nature, maintaining scalability and context awareness with Anthropic web search function and Think tool. Key Advantages 🔁 Dynamic Model Selection Automatically routes each user query to either Claude Sonnet 4 (for routine tasks) or Claude Opus 4 (for complex reasoning), ensuring optimal performance and cost-efficiency. 🧠 AI Agent with Tool Use The AI agent can utilize a web search tool to retrieve up-to-date information and a Think tool for complex reasoning processes — improving response quality. 📎 Memory Integration Uses session-based memory to maintain conversational context, making interactions more coherent and human-like. 🧮 Built-in Calculation Tool Handles numeric queries using an integrated calculator tool, reducing the need for external processing. 📤 Structured Output Parser Ensures outputs are always well-structured and formatted in JSON, which improves consistency and downstream integrations. 🌐 Web Search Capability Supports real-time information retrieval for current events, statistics, or details not available in the AI’s base knowledge. Components Overview Trigger**: Listens for new chat messages. Routing Agent**: Analyzes the message and returns the best model to use. AI Agent**: Handles the conversation, decides when to use tools. Tools**: web_search for internet queries Think for reasoning Calculator for math tasks Models Used**: claude-sonnet-4-20250514: Optimized for general and business logic tasks. claude-opus-4-20250514: Best for deep, strategic, and analytical queries. How It Works Dynamic Model Selection The workflow begins when a chat message is received. The Anthropic Routing Agent analyzes the user's query to determine the most suitable model (either Claude Sonnet 4 or Claude Opus 4) based on the query's complexity and requirements. The routing agent uses predefined criteria to decide: Claude Sonnet 4: Best for standard tasks like real-time workflow routing, data validation, and routine business logic. Claude Opus 4: Reserved for complex scenarios requiring deep reasoning, advanced analysis, or high-impact decisions. Query Processing and Response Generation The selected model processes the query, leveraging tools like web_search for real-time information retrieval, Think for internal reasoning, and Calculator for numerical tasks. The AI Agent coordinates these tools, ensuring the response is accurate and context-aware. A Simple Memory node retains session context for coherent multi-turn conversations. The final response is formatted and returned to the user without intermediate steps or metadata. Set Up Steps Node Configuration Trigger: Configure the "When chat message received" node to handle incoming user queries. Routing Agent: Set up the "Anthropic Routing Agent" with the system message defining model selection logic. Ensure it outputs a JSON object with prompt and model fields. AI Model Nodes: Link the "Sonnet 4 or Opus 4" node to dynamically use the selected model. The "Sonnet 3.7" node powers the routing agent itself. Tool Integration Attach the "web_search" HTTP tool to enable internet searches, ensuring the API endpoint and headers (e.g., anthropic-version) are correctly configured. Connect auxiliary tools (Think, Calculator) to the "AI Agent" for extended functionality. Add the "Simple Memory" node to maintain conversation history. Credentials Provide an Anthropic API key to all nodes requiring authentication (e.g., model nodes, web search). Testing Activate the workflow and test with sample queries to verify: Correct model selection (e.g., Sonnet for simple queries, Opus for complex ones). Proper tool usage (e.g., web searches trigger when needed). Memory retention across chat turns. Deployment Once validated, set the workflow to active for live interactions. Need help customizing? Contact me for consulting and support or add me on Linkedin.

Quick Overview This workflow runs every Monday and reads pending rows from a Microsoft Excel workbook, generates certificate and contract PDFs in bulk with Carbone using templates stored in SharePoint, uploads the files to OneDrive, posts a summary card to Microsoft Teams, and marks the Excel rows as completed via Microsoft Graph. How it works Runs every Monday at 08:00 on a schedule. Fetches the Excel header row via Microsoft Graph and reads the pending rows from the configured Microsoft Excel worksheet. Splits the rows into certificate and contract batches and prepares the data arrays Carbone uses to render documents. If certificate rows exist, downloads the certificate template from Microsoft SharePoint, generates a zipped batch of PDFs with Carbone, extracts the files, and uploads them to Microsoft OneDrive. If contract rows exist, downloads the contract template from Microsoft SharePoint, generates a zipped batch of PDFs with Carbone, extracts the files, and uploads them to Microsoft OneDrive. Posts an Adaptive Card summary (batch ID and document counts) to the configured Microsoft Teams channel. Uses Microsoft Graph $batch requests to update each processed Excel row with Status = Completed and sets ProcessedAt to the current timestamp. Setup Add Microsoft 365 credentials for Microsoft Excel (OAuth2), Microsoft SharePoint, Microsoft OneDrive, and Microsoft Teams, plus a Carbone API credential. In the Config step, replace all placeholder IDs for the Excel workbook/worksheet, SharePoint template file IDs, OneDrive folder IDs, and the target Teams team and channel. Ensure your Excel sheet includes header columns named Status and ProcessedAt (and the fields used in the workflow such as Name, Email, Company, Role, DocumentType, CourseTitle, CompletionDate, and Score). Update the organization/signatory values (issuedBy and issuerName) and make sure your Carbone templates reference the workflow’s certificate and contract fields.

This workflow connects Telegram bots with LangChain nodes in n8n. The main AI Agent Node is configured as a Conversation Agent. It has a custom System Prompt which explains the reply formatting and provides some additional instructions. The AI Agent has several connections: OpenAI GPT-4 model is called to generate the replies Window Buffer Memory stores the history of conversation with each user separately There is an additional Custom n8n Workflow tool (Dall-E 3 Tool). AI Agent uses this tool when the user requests an image generation. In the lower part of the workflow, there is a series of nodes that call Dall-E 3 model with the user Telegram ID and a prompt for a new image. Once image is ready, it is sent back to the user. Finally, there is an extra Telegram node that masks HTML syntax for improved stability in case the AI Agent replies using the unsupported format.

This guide details the setup and functionality of an automated workflow designed to monitor the health, uptime, and SLA compliance of travel supplier APIs, specifically the Amadeus Flight API and Booking.com Hotel API. The workflow runs every 10 minutes, processes health and SLA data, and sends alerts or logs based on the status. What It Monitors API Health**: UP/DOWN status with health indicators. Uptime Tracking**: Real-time availability percentage. SLA Compliance**: Automatic breach detection and alerts. Performance Rating**: Classified as EXCELLENT, GOOD, AVERAGE, or POOR. Features Runs every 10 minutes automatically. Monitors the Amadeus Flight API with a 99.5% SLA target. Monitors the Booking.com Hotel API with a 99.0% SLA target. Smart Alerts that notify via WhatsApp only on SLA breaches. Logging of results for both breaches and normal status. Workflow Steps Monitor Schedule**: Triggers the workflow every 10 minutes automatically. Amadeus Flight API**: Tests the Amadeus Flight API (GET: https://api.amadeus.com) simultaneously. Booking Hotel API**: Tests the Booking.com Hotel API (GET: https://distribution-xml.booking.com) simultaneously. Calculate Health & SLA**: Processes health, uptime, and SLA data. Alert Check**: Routes to appropriate responses based on breach status. SLA Breach Alert**: Sends an alert with throwError if an SLA breach occurs. Normal Status Log**: Records results with throwError for healthy status. Send Message**: Sends a WhatsApp message for breach alerts. How to Use Copy the JSON configuration of the workflow. Import it into your n8n workspace. Activate the workflow. Monitor results in the execution logs and WhatsApp notifications. The workflow will automatically start tracking your travel suppliers and alert you via WhatsApp only when SLA thresholds are breached. Please double-check responses to ensure accuracy. Requirements n8n account and instance setup. API credentials for Amadeus Flight API (e.g., https://api.amadeus.com). API credentials for Booking.com Hotel API (e.g., https://distribution-xml.booking.com). WhatsApp integration for sending alerts. Customizing this Workflow Adjust the Monitor Schedule interval to change the frequency (e.g., every 5 or 15 minutes). Modify SLA targets in the Calculate Health & SLA node to align with your service agreements (e.g., 99.9% for Amadeus). Update API endpoints or credentials in the Amadeus Flight API and Booking Hotel API nodes for different suppliers. Customize the Send Message node to integrate with other messaging platforms (e.g., Slack, email). Enhance the Normal Status Log to include additional metrics or export logs to a database.

This workflow automates pre-dispatch customs document validation for international shipments. It ingests shipping document packages, extracts content from each file, uses Claude AI to cross-validate all documents for consistency, regulatory compliance, and HS code accuracy, then flags errors before goods are dispatched — preventing costly delays, fines, and rejected shipments at the border. How it works Trigger — Webhook submission or watched Drive/S3 folder when new shipment docs are uploaded Register Shipment — Assigns shipment case ID, normalises metadata from payload Fetch Document Files — Downloads each document from Google Drive or URL Extract Text Content — Parses PDF/DOCX text from all documents Classify Document Types — Identifies invoice, packing list, bill of lading, COO, etc. Cross-Document Consistency Check — Detects mismatches across documents (values, weights, quantities) AI Compliance Validation — Claude AI validates each doc against destination country rules Aggregate Findings — Merges per-document results into a shipment-level report Route by Risk Level — Branches on CLEAR / HOLD / REJECT Notify Logistics Team — Slack alert with error summary and action items Email Exporter Report — Detailed validation report with fix instructions Update Shipment Tracker — Writes status back to Airtable / Google Sheets Create Compliance Ticket — Opens Jira issue for HOLD or REJECT shipments Return API Response — Structured JSON result to caller or TMS integration Setup Steps Import workflow into n8n Configure credentials: Anthropic API — Claude AI for compliance validation Google Drive OAuth — Document intake and storage Google Sheets OAuth — Shipment compliance audit log Airtable — Shipment tracker CRM Slack OAuth — Logistics team alerts SendGrid / SMTP — Exporter notification emails Jira API — Compliance issue tracking Set your Google Drive intake folder ID Configure destination country rules in the AI prompt node Set your Airtable base and shipment table IDs Activate the workflow Sample Webhook Payload { "shipmentId": "SHP-2025-00392", "exporterEmail": "logistics@exportco.com", "originCountry": "CN", "destinationCountry": "AU", "incoterms": "FOB", "declaredValue": 48500, "currency": "USD", "goodsDescription": "Electronic Components", "documents": [ { "name": "Commercial Invoice", "type": "commercial_invoice", "driveFileId": "1aBcD" }, { "name": "Packing List", "type": "packing_list", "driveFileId": "2eFgH" }, { "name": "Bill of Lading", "type": "bill_of_lading", "driveFileId": "3iJkL" }, { "name": "Certificate of Origin", "type": "certificate_of_origin", "driveFileId": "4mNoP" } ] } Documents Supported Commercial Invoice Packing List Bill of Lading (B/L) / Airway Bill (AWB) Certificate of Origin (COO / Form D / EUR.1) Customs Entry / Import Declaration Dangerous Goods Declaration (DGD) Phytosanitary / Health Certificate Insurance Certificate Letter of Credit (L/C) Export Licence / Permit Material Safety Data Sheet (MSDS) Fumigation Certificate AI Validation Checks Field Completeness** — All mandatory fields present and populated Cross-Document Consistency** — Values, weights, quantities, HS codes match across docs HS Code Validation** — Correct classification for declared goods and destination Incoterms Compliance** — Terms correctly applied across invoice and B/L Valuation Rules** — Customs value method correct, currency declared Country of Origin** — COO criteria met, preferential rates applicable Restricted / Prohibited Goods** — Flags potential dual-use, CITES, or embargoed items Sanction Screening** — Party names checked against common red flags Date & Validity** — Document dates consistent, certificates not expired Features Multi-document cross-validation in a single run AI-powered HS code verification and suggestion Destination-country–specific compliance rules Automatic HOLD/REJECT routing for high-risk findings Detailed error report with fix instructions per field Full audit trail in Google Sheets Jira ticket creation for escalated compliance issues Explore More Automation: Contact us to design AI-powered lead nurturing, content engagement, and multi-platform reply workflows tailored to your growth strategy.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This workflow automatically tracks brand mentions across various online platforms by scraping blog posts and articles for specific brand references. It saves you time by eliminating the need to manually search for brand mentions and provides sentiment analysis on how your brand is being discussed online. Overview This workflow automatically scrapes Medium blog posts and other online content to find mentions of specific brands (like OpenAI) and performs sentiment analysis on the content. It uses Bright Data to access content without restrictions and AI to intelligently extract brand-related information, analyze sentiment, and summarize key points about brand coverage. Tools Used n8n**: The automation platform that orchestrates the workflow Bright Data**: For scraping blog posts and articles without being blocked OpenAI**: AI agent for intelligent content analysis and sentiment extraction Google Sheets**: For storing brand mention data and sentiment analysis results How to Install Import the Workflow: Download the .json file and import it into your n8n instance Configure Bright Data: Add your Bright Data credentials to the MCP Client node Set Up OpenAI: Configure your OpenAI API credentials Configure Google Sheets: Connect your Google Sheets account and set up your brand monitoring spreadsheet Customize: Define target URLs and brand keywords to monitor Use Cases Brand Monitoring**: Track how your brand is mentioned and discussed online Public Relations**: Monitor media coverage and public sentiment about your brand Competitive Intelligence**: Track mentions of competitor brands and market perception Crisis Management**: Quickly identify negative brand mentions for rapid response Connect with Me Website**: https://www.nofluff.online YouTube**: https://www.youtube.com/@YaronBeen/videos LinkedIn**: https://www.linkedin.com/in/yaronbeen/ Get Bright Data**: https://get.brightdata.com/1tndi4600b25 (Using this link supports my free workflows with a small commission) #n8n #automation #brandmonitoring #sentimentanalysis #brightdata #webscraping #brandmentions #n8nworkflow #workflow #nocode #mediamonitoring #brandtracking #publicrelations #brandanalytics #onlinemonitoring #contentanalysis #brandsentiment #digitalmonitoring #brandresearch #mediaanalysis #brandinsights #reputationmanagement #brandwatch #socialmediamonitoring #contentmonitoring #brandpresence #digitalpr #brandlistening #mediatracking #onlinereputation

The workflow is well-designed for CRM analysis with a robust quality control mechanism. The dual-AI approach ensures reliable results, while the webhook integration makes it production-ready for real-time CRM data processing. Dual-AI Architecture: Uses DeepSeek Reasoner for analysis and DeepSeek Chat for verification. Flexible Input: Supports both manual testing and production webhook integration. Quality Assurance: Built-in verification system to ensure report accuracy. Comprehensive Analysis: Covers lead conversion, upsell metrics, agent ranking, and more. Professional Output: Generates structured markdown reports with actionable insights