Anthropic AI agent: Claude Sonnet 4 and Opus 4 with Think and Web Search tool
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.
By DavideGenerate AI avatar videos from text with HeyGen and upload to YouTube
Create Video with HeyGen and Upload to YouTube Overview This workflow automates the process of creating an AI-generated avatar video using HeyGen and directly uploading it to YouTube. By sending text input via a webhook, the workflow generates a video with a chosen avatar and voice, waits for processing, downloads the completed file, and publishes it to your configured YouTube channel. This template is ideal for automating content creation pipelines, such as daily news updates, explainer videos, or narrated scripts, without manual intervention. --- Use Case Marketing teams: Automate explainer or promotional video creation from text input. Content creators: Generate AI-based avatar videos for YouTube directly from scripts. Organizations: Streamline video generation for announcements, product updates, or tutorials. Instead of recording and editing videos manually, this template allows you to feed text content into a webhook and have a ready-to-publish video on your YouTube channel within minutes. --- How It Works Webhook Trigger: The workflow starts when text content and a title are sent to the webhook endpoint. Code Node: Cleans and formats the input text by removing unnecessary newlines and returns it with the title. Set Node: Prepares HeyGen parameters, including API key, avatar ID, voice ID, title, and content. HeyGen API Call: Sends the request to generate a video with the provided avatar and voice. Wait Node: Pauses briefly to allow HeyGen to process the video. Video Status Check: Polls HeyGen to check whether the video has finished processing. Conditional Check: If the video is still processing, it loops back to wait. Once complete, it moves forward. Download Node: Retrieves the generated video file. YouTube Upload Node: Uploads the video to your YouTube channel with the provided title and default settings. --- Requirements HeyGen API Key: Required to authenticate with HeyGen’s video generation API. HeyGen Avatar & Voice IDs: Unique identifiers for the avatar and voice you want to use. YouTube OAuth2 Credentials: Connected account for video uploads. --- Setup Instructions Import the Workflow: Download and import this template JSON into your n8n instance. Configure the Webhook: Copy the webhook URL from n8n and use it to send requests with title and content. Example payload: json { "title": "Tech News Update", "content": "Today’s top story is about AI advancements in video generation..." } Add HeyGen Credentials: Insert your HeyGen API key in the Set Node under x-api-key. Provide your chosen avatarid and voiceid from HeyGen. To find your HeyGen avatarid and voiceid, first retrieve your API key from the HeyGen dashboard. With this key, you can use HeyGen’s API to look up available options: run a GET request to https://api.heygen.com/v2/avatars to see a list of avatars along with their avatarid, and then run a GET request to https://api.heygen.com/v2/voices to see a list of voices with their voiceid. Once you’ve identified the avatar and voice you want to use, copy their IDs and paste them into the Set HeyGen Parameters node in your n8n workflow. Set Up YouTube Credentials: Connect your YouTube account in n8n using OAuth2. Ensure proper permissions are granted for video uploads. To set up YouTube credentials in n8n, go to the Google Cloud Console, enable YouTube Data API v3, and create an OAuth Client ID (choose Web Application and add the redirect URI: https://<your-n8n-domain>/rest/oauth2-credential/callback). Copy the Client ID and Client Secret, then in n8n create new credentials for YouTube OAuth2 API. Enter the values, authenticate with your Google account to grant upload permissions, and test the connection. Once complete, the YouTube node will be ready to upload videos automatically. Activate the Workflow: Once configured, enable the workflow. Sending a POST request to the webhook with title and content will trigger the full process. --- Notes You can adjust video dimensions (default: 1280x720) in the HeyGen API request. Processing time may vary depending on script length. The workflow uses a wait-and-poll loop until the video is ready. Default YouTube upload category is Education (28) and region is US. These can be customized in the YouTube node. ---
By Nishant RayanBuild a WhatsApp assistant for text, audio & images using GPT-4o & Evolution API
Build an intelligent WhatsApp assistant that automatically responds to customer messages using AI. This template uses the Evolution API community node for WhatsApp integration and OpenAI for natural language processing, with built-in conversation memory powered by Redis to maintain context across messages. > ⚠️ Self-hosted requirement: This workflow uses the Evolution API community node, which is only available on self-hosted n8n instances. It will not work on n8n Cloud. What this workflow does Receives incoming WhatsApp messages via Evolution API webhook Filters and processes text, audio, and image messages Transcribes audio messages using OpenAI Whisper Analyzes images using GPT-4 Vision Generates contextual responses with conversation memory Sends replies back through WhatsApp Who is this for? Businesses wanting to automate customer support on WhatsApp Teams needing 24/7 automated responses with AI Developers building multimodal chat assistants Companies looking to reduce response time on WhatsApp Setup instructions Evolution API: Install and configure Evolution API on your server. Create an instance and obtain your API key and instance name. Redis: Set up a Redis instance for conversation memory. You can use a local installation or a cloud service like Redis Cloud. OpenAI: Get your API key from platform.openai.com with access to GPT and Whisper models. Webhook: Configure your Evolution API instance to send webhooks to your n8n webhook URL. Customization options Modify the system prompt in the AI node to change the assistant's personality and responses Adjust the Redis TTL to control how long conversation history is retained Add additional message type handlers for documents, locations, or contacts Integrate with your CRM or database to personalize responses Credentials required Evolution API credentials (self-hosted) OpenAI API key Redis connection
By Antonio GassoFind & verify business emails automatically with OpenRouter, Serper & Prospeo
Who is this template for? Growth teams, SDRs, recruiters, or anyone who routinely hunts for hard‑to‑find business emails and would rather spend time reaching out than guessing formats. What problem does this workflow solve? Manually piecing together email patterns, cross‑checking them in a verifier, and updating a tracking sheet is slow and error‑prone. This template automates the entire loop—research, guess, verify, and log—so you hit Start and watch rows fill up with ready‑to‑send addresses. What this workflow does Pull fresh leads – Grabs only the rows in your Google Sheet where Status = FALSE. Find the company pattern – Queries Serper.dev for snippets and feeds them to Gemini Flash (via OpenRouter) to spot the dominant email format. Build the address – Constructs a likely email for every first/last name. Verify in real time – Pings Prospeo by default (API) or lets you bulk‑clean in Sparkle.io. Write it back – Updates the sheet with pattern, email, confidence, verification status, and flips Status to TRUE. Loop until done – Runs batch‑by‑batch so you never hit API limits. --- 🆓 Work free‑tier magic (up to \~2,500 contacts/month) | Service | Free allowance | How this template uses it | | -------------- | ----------------------------- | ------------------------------------------------------------------------------------ | | Serper.dev | 2,500 searches/mo | Scrapes three public email snippets per domain to learn the pattern | | Sparkle.io | 10,000 bulk verifications/day | Manual upload‑download option—perfect to clean your first 2.5k emails at zero cost | | Prospeo | 75 API calls/mo | Built‑in if you prefer fully automated verification | Quick Sparkle workflow: Let the template generate emails. Export the “Email” column to CSV → upload to Sparkle.io. Download the results and paste the "verification\_status" back into the sheet (or add a small n8n import sub‑flow). --- Setup (5 minutes) Copy the Google Sheet linked in the sticky note and paste its ID into the Get Rows and Update Rows nodes. Add credentials for Google Sheets, Serper (X‑API‑KEY), OpenRouter, and optionally Prospeo. Hit Execute Workflow—that’s it. --- How to customise Prefer Sparkle for volume: Skip the Prospeo node, export emails in one click, bulk‑verify in Sparkle, and re‑import results. Swap the search source: Replace the Get Email Pattern* HTTP node with Bing, Brave, etc. Extend enrichment: Add phone look‑ups or LinkedIn scrapers before the Update Rows* node. Auto‑run: Replace the Manual Trigger with a Cron node so the sheet cleans itself every morning. --- Additional resources | Tool | Purpose | Link | | --------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------- | -------------------------------------------------------- | | Prospeo – API‑ready email verification<br><sub>Special offer: 20 % free credits for the first 3 months on any plan using this link!</sub> | Real‑time, single‑call mailbox validation | prospeo.io | | Sparkle.io – high‑volume bulk verifier (manual upload) | Free daily quota of 10 000 verifications | app.sparkle.io/sign‑up | | OpenRouter – API gateway for Gemini Flash & other LLMs | One key unlocks multiple frontier models | openrouter.ai | | Serper.dev – Google Search API | 2 500 searches/month on the free tier | serper.dev | Add the relevant keys or signup details from these links, drop them into the matching n8n credentials, and you’re all set to enrich your first 2 500 contacts at zero cost. Happy building!
By Naveen ChoudharyAutomated lead generation & qualification with Google Maps, GPT-4 & HubSpot
This n8n workflow automates CVE tracking by retrieving vulnerability details from the NVD API 🛡️, organizing and updating the data in Google Sheets 📊, and optionally alerting teams via Slack or Email 📩💬. --- Who is this for? This workflow is ideal for: Security operations (SecOps) teams 🧑💻 DevSecOps engineers 🛠️ IT compliance officers 🧾 Vulnerability management analysts 🕵️ Sysadmins or cloud engineers in regulated industries 🏢 --- What problem does this workflow solve? Manually checking for the latest CVE information is inefficient and error-prone. This automation: Monitors NVD for CVE entries based on product or keyword filters 🔍 Tracks new vulnerabilities and changes to existing ones ⏱️ Logs all CVE data in a structured Google Sheet for ongoing review and audit 🧾 Can trigger alerts or actions for high-severity CVEs 🚨 --- What this workflow does This workflow builds an automated CVE monitoring system that: Queries the NVD API for vulnerability data matching keywords (e.g. "Apache", "Log4j") 📡 Extracts relevant fields: CVE ID, description, severity (CVSS scores), published/modified dates, and affected products 🗂️ Saves or updates the information in Google Sheets 📑 Optionally filters for critical severity (e.g., CVSS > 8.0) and sends Slack alerts or emails 📬 Supports historical tracking and change detection over time 🕒 Includes a Google Sheets template for tracking: CVE IDs and metadata Severity levels and scores Product/component tags Resolution/patch status tracking --- Setup Prerequisites You'll need: An n8n instance (cloud or self-hosted) ☁️ A Google account + Google Sheets API credentials 📑 (Optional) Slack webhook URL or email setup for notifications 💬 Step 1: Configure API Inputs Open the 🔧 Configuration node and provide: NVD API parameters (keyword filters, date ranges, etc.) Google Sheet ID and tab name for output Slack webhook URL (optional) Step 2: Set Filters & Preferences Define: Target keywords or CPE filters (e.g. “Cisco ASA”, “Windows 10”) 🧩 CVSS threshold for high/critical alerts 🎚️ Update frequency (manual trigger, scheduled cron, webhook, etc.) 🔁 Step 3: Connect to Google Sheets Update Sheet node with your destination Sheet ID Ensure columns like CVE ID, Description, Severity, Last Updated exist Step 4: Enable Alerts (Optional) Set up Slack node with your webhook URL or connect SMTP/Email node Format alert message with key CVE data Step 5: Activate and Run Save and activate the workflow 🔛 Run manually or schedule it to run periodically (e.g., every 6 hours) ⏱️ --- Customization Tips Add deduplication logic to avoid reprocessing the same CVEs ♻️ Use filters to monitor only critical CVEs or specific vendors/vendors 🔍 Extend with GitHub Security Advisories or Exploit DB integration 🧩 Track remediation status and link to patch notes or fixes 🩹 --- Troubleshooting Common Issues Empty results from NVD:* Check if your keywords are too narrow or if NVD API rate limits apply 📉 Google Sheets error:* Ensure the Sheet ID and tab names are correct and accessible 🔑 Alerts not sending:* Check Slack webhook or email configurations 🔧 --- Getting Help Read inline comments in n8n 📝 Visit the n8n Docs 📚 Contact template creator: dimejicole21@gmailcom --- This template was created by David Olusola. 🛡️
By David OlusolaMulti-agent personal assistant orchestration with GPT-4o & WhatsApp
Description 'Elena AI' is a powerful n8n workflow that transforms your automation platform into a full-fledged, multi-agent AI hub. 🤖✨ By combining Redis state management with specialized “tool” sub-workflows, you can build contextual, scalable, and highly personalized conversational automations for WhatsApp, Telegram, email, and more. 🔥 Key Features Unified Ingestion 📥 • Webhook trigger for text, audio, image, or document messages • Automatic extraction of remoteJid, user ID, and payload metadata Stateful Context 🔄 • Redis push/get queue to preserve conversation history • Seamless handling of follow-ups and multi-turn dialogs Dynamic Routing 🔀 • Smart Switch logic directs messages to the right agent workflow • Agents available: 🗓️ Malu: Google Calendar scheduling & reminders 💰 Maria: Expense logging & budget tracking in Baserow 👥 Mafalda: Contact CRUD operations in Baserow 📸 Marcela: Audio transcription & image analysis ✉️ Martina: Gmail send/receive & template replies Bite-Sized Responses ✂️ • Splits long AI replies into line-by-line messages • Loop node controls rate & order for best UX Flexible Output 📤 • HTTP Request node to deliver text, media, or files • Customize headers, payloads, and endpoints 🎯 Use Cases AI-powered customer support bots Automated lead qualification & follow-up Intelligent scheduling & reminders Expense approval workflows Multimedia content analysis & response 📋 Requirements n8n ≥ 1.0 with Webhook, Redis, SplitInBatches, HTTP Request & Workflow nodes Redis server (connection credentials in n8n) Service accounts / API keys for: Google Calendar (OAuth2) Baserow (API token) Gmail (OAuth2) Messaging API endpoint (HTTP) Environment variables set in n8n: REDISHOST, REDISPORT, REDIS_PASSWORD GOOGLECLIENTID, GOOGLECLIENTSECRET BASEROWAPITOKEN GMAILCLIENTID, GMAILCLIENTSECRET MSGAPIURL, MSGAPIKEY 🚀 Quick Start Import the ElenaAI.json into n8n. Configure credentials and environment variables under Settings → Credentials. Link sub-workflows (Malu, Maria, Mafalda, Marcela, Martina) by updating their Workflow IDs in the main node. Test via Execute node or send a sample webhook payload. Deploy by exposing the Webhook endpoint to your messaging platform. Unlock seamless, AI-driven conversations across any channel—get MavenBot 2.0 running in minutes! 🚀
By Amanda BenksConvert Google Tasks to Google Calendar events via webhook integration
Who’s it for Operators and makers who capture tasks from custom forms, bots, or automations and want them to appear as time-boxed events in Google Calendar with minimal setup. How it works A Webhook receives a payload containing the task title and a due date (as Unix seconds). The workflow formats the date, checks the most recently updated events in your calendar to avoid duplicates, and creates a new 30-minute event (configurable). After creation, it optionally deletes the original task, keeping your Task list clean and your Calendar up to date. How to set up Select your Google Tasks and Google Calendar credentials. Open the Configuration node and set tasklistId, calendarId (use primary or a specific calendar), defaultMinutes, and eventColor. Send a sample POST to the Webhook with { TaskName, DueDateTimeSeconds }. Run once in manual mode and, if all looks good, activate. Requirements Google accounts for Tasks and Calendar. Appropriate scopes/permissions in the selected credentials. How to customize the workflow Change the event duration/color in Configuration. Adjust duplicate detection by modifying the Calendar search window and query. Map additional fields (e.g., description, attendees) on the Calendar node’s optional fields. Tags Google Calendar, Google Tasks, Webhook, Automation, Productivity Categories Productivity, Google, Calendar
By R4wd0GAuto-categorize Gmail emails with AI and send prioritized Slack alerts
Who is this for? Teams using Gmail and Slack who want to streamline email handling. Customer support, sales, and operations teams that want emails sorted by topic and priority automatically. Anyone tired of manually triaging customer emails. What does it solve? Stops important messages from slipping through the cracks. Automatically identifies the nature and urgency of incoming emails. Routes emails to the right Slack channel with a clear, AI-generated summary. How it works The workflow watches for unread emails in your Gmail inbox. It fetches the full email content and passes it to OpenAI for classification. The AI returns structured JSON with the email’s category, priority, summary, and sender. Based on the AI result, it assigns a label and Slack channel. A message is sent to the right Slack channel with the details. How to setup? Connect credentials: Gmail (OAuth2) Slack (OAuth2) OpenAI (API Key) Adjust email polling: Open the Gmail Trigger node and set how frequently it should check for new emails. Verify routing settings: In the “Routing Map” node, update Slack channel IDs for each category if needed. Customize AI behavior (optional): Tweak the AI Agent prompt to better match your internal categorization rules. How to customize this workflow to your needs Add more categories: Update the AI prompt and the schema in the “Structured Output Parser.” Change Slack formatting: Modify the message text in the Slack node to include links, emojis, or mentions. Use different routing logic: Expand the Routing Map to assign based on keywords, domains, or even sentiment. Add escalation workflows: Trigger follow-up actions for high-priority or complaint emails.
By Matt Chong | n8n Creator📊 Token Estim8r UI – visualize token usage analytics dashboard in n8n
📊 Visualize all your AI Token Usage analytics Dashboard using a single n8n Workflow --- Artwork Generated with ✨ ideoGener8r n8n workflow template --- Token Estim8r UI is the premium version of our token tracking solution for n8n users who want real-time insight into AI model usage and exact cost per execution — all in a beautifully designed analytics dashboard. We've done the work with over 4000 lines of code for you to simply add a pre-configured HTTP Request node to the end of any workflow you want to track, and Token Estim8r UI will handle the rest: collecting data, analyzing token usage, calculating model costs, and feeding everything into a clean UI with charts, graphs, and summaries. --- 🖼️ What the Dashboard Looks Like --- 🙋♂️ Who is this for? This workflow is perfect for: AI engineers Automation specialists Business analysts Teams using OpenAI, Anthropic, Claude, or any token-based LLM If you’re managing API budgets or optimizing prompt performance, this tool provides immediate visibility into where tokens (and money) are going. --- 😌 What problem does this solve? n8n makes it easy to build powerful workflows — but it doesn’t natively track OpenAI token usage or cost. Without that visibility, it’s impossible to: Know what each automation is costing Spot inefficiencies in prompt construction Track cost trends over time Token Estim8r UI solves that with zero manual logging. --- ⚙️ What this workflow does Fetches detailed execution logs from n8n Extracts prompt/completion token usage per model/tool Optionally retrieves live pricing or use preset pricing as of 4/2025 Calculates total cost per run Sends data to a backend for aggregation Displays a full-featured analytics dashboard with: Total tokens, cost, and usage trends Most used models/tools Workflow-model correlations Cost breakdowns and comparisons Workflow usage over time Auto-complete workflow search with filtering by ID or name Filter by date or workflow (single or all workflows) Built in image server Sortable & searchable data table of filtered results with: Prompt & completion token breakdown Cost calculations Workflow name + direct link to the workflow Link to exact execution in n8n --- 🛠️ How Setup Works Import the Token Estim8r UI workflow into your n8n instance Deploy the included dashboard (React/Next.js app, hosted or self-hosted) Configure Google Sheets or your preferred backend (e.g., Supabase, Airtable) Copy the prebuilt HTTP Request node into the end of any n8n workflow Run your workflow — data is captured, aggregated and stored automatically in Google Sheets 🎉 --- 🔄 What Makes This Better than the simple version? The simple version logs to Google Sheets only. This premium UI version adds: Full analytics dashboard Cost aggregation across all workflows Graphs, filters, and model/tool comparisons --- 🔧 Customization Ideas Switch backend to Supabase or Firebase Add alerts via Slack when costs exceed thresholds Build weekly token cost summaries Track model performance across teams Add filters by user/session/timeframe --- 🧠 Why Users Love It "Token Estim8r UI is exactly what I needed to take control of my AI costs inside n8n. It’s plug and play — and the dashboard makes optimization easy." – Beta user, AI Ops Lead 😐 If you're serious about building with AI in n8n, Token Estim8r UI gives you the visibility to scale confidently. 🚀
By RealSimple SolutionsTransform hotel guest feedback with GPT-4 sentiment analysis & service recovery
Transform guest complaints into loyalty opportunities - achieving 60% reduction in negative reviews, 85% faster service recovery, and turning dissatisfied guests into brand advocates through AI-powered sentiment analysis and automated response workflows. What This Workflow Does Revolutionizes hotel guest experience management with AI-driven sentiment analysis and proactive service recovery: 📝 Real-Time Feedback Capture - Jotform collects guest feedback during their stay, not after checkout 🤖 AI Sentiment Analysis - GPT-4 analyzes feedback across sentiment, urgency, and reputation impact 🚨 Instant Escalation - Critical issues immediately alert managers via email and Slack 💝 Personalized Recovery Offers - AI generates custom compensation (upgrades, discounts, credits) 📧 Automated Guest Communication - Sends recovery offers to unhappy guests, thank-you notes to satisfied ones 🎫 PMS Integration - Creates tickets in your Property Management System with full context ⭐ Review Generation - Encourages happy guests to share experiences on Google, TripAdvisor, Booking.com 📊 Complete Analytics - Tracks all feedback with sentiment scores for trend analysis 🎯 Proactive Prevention - Resolves issues before guests post negative online reviews 💰 ROI Tracking - Measures service recovery effectiveness and guest satisfaction improvements Key Features AI Guest Experience Analyst: GPT-4 analyzes feedback across 10+ dimensions including sentiment scoring, urgency classification, and reputation impact assessment Intelligent Routing: Automatically escalates critical/high-urgency issues to hotel management within minutes Personalized Service Recovery: AI generates tailored compensation offers based on issue severity, guest emotional state, and long-term value potential Multi-Channel Alerts: Instant notifications via Gmail and Slack ensure no critical feedback is missed Sentiment Scoring: 0-100 numerical sentiment scores enable data-driven trend analysis Category Detection: AI identifies issue categories (cleanliness, staff, amenities, noise, etc.) Reputation Impact Assessment: Predicts likelihood of negative online review (low/medium/high) Recovery Action Suggestions: AI recommends specific steps to resolve each guest concern Positive Feedback Amplification: Automatically requests online reviews from satisfied guests with incentivized return offers Property Management Integration: Creates structured tickets with all AI insights for staff follow-up Complete Audit Trail: Google Sheets logging enables performance tracking and staff training insights Cost Optimization: AI balances recovery offer value against long-term guest lifetime value Perfect For Boutique Hotels: 20-100 rooms requiring personalized guest experience management Hotel Chains: Multi-property operations standardizing service recovery protocols Resorts: Large properties with multiple service areas (spa, dining, housekeeping, etc.) Business Hotels: Corporate-focused properties prioritizing fast issue resolution Vacation Rentals: Airbnb management companies handling guest communications at scale Hostels: Budget accommodations building reputation through responsive service Extended Stay Properties: Long-term guest relationships requiring proactive care Conference Centers: Event venues managing large groups and critical feedback What You'll Need Required Integrations Jotform - Guest feedback form (free tier works) Create your form for free on Jotform using this link OpenAI API - GPT-4 for AI sentiment analysis (~$0.10-0.30 per feedback) Gmail - Automated notifications to managers and guests Google Sheets - Feedback database and analytics dashboard Optional Integrations Slack - Real-time alerts to management team Property Management System - Automated ticket creation (via API) Quick Start Import Template - Copy JSON and import into n8n Add OpenAI Credentials - Set up OpenAI API key (GPT-4 recommended for best results) Create Jotform Guest Feedback Form: Guest Name (q3_guestName) Guest Email (q4_guestEmail) Room Number (q5_roomNumber) Stay Dates (q6_stayDates) Overall Rating 1-5 (q7_overallRating) Feedback Comments (q8_feedbackComments) Service Area (q9_serviceArea) Create your form for free on Jotform using this link Configure Gmail - Add Gmail OAuth2 credentials (same credential for all 3 Gmail nodes) Setup Google Sheets: Create spreadsheet with "Guest Feedback Analytics" sheet Replace YOURGOOGLESHEET_ID in workflow Columns: timestamp, submissionId, guestName, roomNumber, stayDates, overallRating, serviceArea, sentiment, sentimentScore, urgencyLevel, keyIssues, categories, reputationImpact, recoveryOfferSent, feedbackText Configure PMS Integration (Optional): Add your PMS API endpoint URL Set up HTTP authentication credentials Setup Slack Webhook (Optional): Create Slack incoming webhook Replace YOUR/SLACK/WEBHOOK in workflow Customize Email Addresses: Update hotel.manager@yourhotel.com Update guestrelations@yourhotel.com Update review site URLs in positive feedback email Test Workflow - Submit test feedback through Jotform Go Live - Share feedback form link with guests (QR codes in rooms, checkout emails, etc.) Customization Options Service Recovery Tiers: Adjust compensation levels based on issue severity and guest value Auto-Approval Thresholds: Set limits for automatic vs manager-approved recovery offers AI Prompt Tuning: Customize sentiment analysis criteria for your brand standards Multi-Language Support: Add translation nodes for international guests Guest Segmentation: VIP guests receive premium recovery offers Timing Rules: Different workflows for during-stay vs post-checkout feedback Review Platform Integration: Direct API connections to TripAdvisor, Google Reviews Staff Training Alerts: Route feedback to specific department managers Competitive Analysis: Track sentiment vs competitor properties Seasonal Adjustments: Higher compensation during peak season to retain bookings Loyalty Program Integration: Award points as part of service recovery Follow-Up Sequences: Automated check-ins after issue resolution Expected Results 60% reduction in negative online reviews - Proactive resolution before guests post publicly 85% faster service recovery - Automated workflows vs manual monitoring 40% increase in repeat bookings - Effective recovery turns complainers into loyalists 95% manager response rate - Instant alerts ensure nothing falls through cracks 3x increase in positive review requests - Automated outreach to satisfied guests 75% cost reduction in review management - Less time fighting bad reviews 90% guest satisfaction with recovery - Personalized, immediate responses 100% feedback tracking - Complete audit trail for quality improvement 50% improvement in staff training - Data-driven insights on recurring issues 30% reduction in compensation costs - AI optimizes offer value vs actual resolution Use Cases Luxury Resort (200 Rooms) Scenario: Guest in oceanview suite complains about noisy pool area disrupting afternoon nap. Rating: 2/5. Feedback submitted at 2:47 PM during stay. AI Analysis: Sentiment = negative (35/100), Urgency = high, Impact = high reputation risk. Key issue: noise disturbance. Category: amenities/environment. Automated Response: 2:48 PM: Hotel manager receives urgent email and Slack alert 2:49 PM: AI generates recovery offer: complimentary room upgrade to quiet wing + $100 spa credit + late checkout 2:52 PM: Manager reviews AI recommendation, approves via phone 3:00 PM: Guest receives personalized apology email with upgrade offer 3:15 PM: Guest accepts, moves to premium suite 3:45 PM: Manager personally visits guest with welcome amenity Next Day: Guest updates internal feedback to 5/5 Result: $200 recovery cost prevents $5,000+ in future lost bookings from negative review. Guest becomes repeat customer, books 3 more stays over next year. Business Hotel (80 Rooms) Scenario: Corporate traveler rates stay 5/5, praises front desk staff professionalism and fast WiFi. Checkout feedback at 7:23 AM. AI Analysis: Sentiment = positive (92/100), Urgency = low, Categories: staff excellence, amenities. Automated Response: 7:24 AM: Thank you email sent with review request links (Google, TripAdvisor) Email includes 15% discount code for next stay (WELCOME-BACK-2025) Review links customized with pre-filled star ratings 11:30 AM: Guest posts 5-star Google review mentioning staff by name Result: Positive review attracts 12 new corporate bookings over next quarter. Guest becomes regular weekly visitor. Zero manual effort required. Budget Hotel Chain (150 Locations) Scenario: Guest complains about unclean bathroom, slow check-in, and uncomfortable bed. Rating: 1/5. Multiple critical issues. AI Analysis: Sentiment = negative (15/100), Urgency = CRITICAL, Impact = very high reputation risk. Categories: cleanliness, operations, room quality. Automated Response: Instant email to hotel manager + regional director Slack alert to operations-critical channel AI recommends: full refund + 2 free night voucher + immediate room change PMS ticket created for housekeeping inspection Guest receives apology within 10 minutes Manager calls guest personally within 20 minutes Room changed immediately, housekeeping staff retrained Result: Guest accepts recovery offer, doesn't post negative review. Systemic cleaning issue identified and corrected across all 150 locations, preventing 1,000+ potential complaints. Boutique B&B (12 Rooms) Scenario: Couple celebrating anniversary rates stay 4/5, mentions minor issue with breakfast timing but overall lovely experience. AI Analysis: Sentiment = positive (78/100), Urgency = low, Issue noted: breakfast service timing, Categories: dining, overall satisfaction. Automated Response: Thank you email with review requests AI suggests small gesture: complimentary breakfast on next visit Owner receives gentle notification about breakfast timing feedback (not urgent) Follow-up email includes personalized anniversary wishes Result: Couple posts glowing TripAdvisor review, becomes annual anniversary tradition. Breakfast timing adjusted based on feedback trend analysis. Personal touch strengthens brand loyalty. Resort During Peak Season Scenario: Family of 4 complains about overbooked pool area, long wait times at restaurant, stressed staff. Rating: 3/5. Peak season capacity issues. AI Analysis: Sentiment = neutral-negative (45/100), Urgency = medium, Categories: capacity management, staffing, amenities access. AI notes this is systemic, not individual service failure. Automated Response: Manager receives analysis highlighting capacity issues vs service quality AI recommends: restaurant priority reservations rest of stay + late checkout + $150 resort credit Recovery offer emphasizes "peak season challenges we're addressing" Guest receives empathetic communication acknowledging valid concerns Operations team receives alert about capacity strain for staffing adjustments Result: Family accepts offer, enjoys remaining days. Operations team adds staff for following weekend. Feedback trends identify need for reservation system improvements, implemented before next season. Pro Tips QR Code Distribution: Place QR codes linking to feedback form in every room, at checkout desk, and in common areas Timing Optimization: Send feedback requests on Day 2 of stay (not checkout) to enable real-time recovery Manager Training: Educate managers on interpreting AI sentiment scores and urgency classifications Recovery Budgets: Set department budgets for service recovery offers ($50-500 per incident) Review Monitoring: Cross-reference internal feedback with online reviews to measure prevention effectiveness Staff Recognition: Share positive feedback with staff members mentioned by name Trend Analysis: Weekly reviews of Google Sheets data to identify recurring issues Seasonal Patterns: Track sentiment scores across different seasons and events Competitor Benchmarking: Compare your sentiment scores to industry averages Follow-Up Surveys: Send 30-day post-stay surveys to guests who received service recovery Loyalty Integration: Higher-tier loyalty members receive premium recovery offers Language Customization: For international properties, adjust AI prompts for cultural norms Response Time Tracking: Monitor average time from feedback to resolution Cost-Benefit Analysis: Track recovery offer costs vs prevented negative review impact Success Metrics Dashboard: Create Google Data Studio dashboard from Sheets data Learning Resources This workflow demonstrates advanced automation: AI Agents with Multi-Dimensional Analysis: Sentiment scoring, urgency classification, impact assessment, and recovery recommendations Conditional Logic Routing: Different workflows for positive, negative, and critical feedback Real-Time Alerting: Multi-channel notifications (email + Slack) for urgent issues Dynamic Content Generation: AI creates personalized emails based on sentiment analysis API Integration Patterns: Property Management System ticket creation via HTTP requests Data Aggregation: Complete feedback logging for business intelligence and reporting Natural Language Processing: AI extracts key issues, categories, and emotional tone from free-text feedback Decision Support Systems: Provides managers with AI recommendations and key considerations Approval Workflows: Optional manager approval step for high-value recovery offers Guest Communication Templates: Professional, empathetic email templates for all scenarios Business Impact Metrics Review Management ROI: Compare cost of service recovery vs reputation management services (typically $500-2000/month) Guest Lifetime Value: Track repeat booking rates for guests who received service recovery vs those who didn't Online Reputation Score: Monitor aggregate rating improvements on Google, TripAdvisor, Booking.com Staff Efficiency: Calculate hours saved vs manual feedback monitoring and response Revenue Protection: Estimate revenue preserved by preventing negative reviews (avg negative review costs hotel $2,000-5,000 in lost bookings) Recovery Success Rate: Percentage of negative feedback resolved without resulting in online reviews Response Time: Average minutes from feedback submission to initial response First-Contact Resolution: Percentage of issues resolved without multiple interactions Training ROI: Reduction in recurring issues after staff training based on feedback trends Competitive Positioning: Sentiment score comparison vs competitor properties --- Ready to Transform Your Guest Experience? Import this template and turn guest feedback into your competitive advantage with AI-powered insights and automation! 🏨✨ Questions or customization? The workflow includes detailed sticky notes explaining each AI analysis component and decision logic. Template Compatibility ✅ n8n version 1.0+ ✅ Works with n8n Cloud and Self-Hosted ✅ No coding required for basic setup ✅ Fully customizable for advanced users
By Jitesh Dugar🛠️ Emelia tool MCP server 💪 all 9 operations
Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator? Join the community Complete MCP server exposing all Emelia Tool operations to AI agents. Zero configuration needed - all 9 operations pre-built. ⚡ Quick Setup Import this workflow into your n8n instance Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works • MCP Trigger: Serves as your server endpoint for AI agent requests • Tool Nodes: Pre-configured for every Emelia Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n Emelia Tool tool with full error handling 📋 Available Operations (9 total) Every possible Emelia Tool operation is included: 📢 Campaign (7 operations) • Add a contact to a campaign • Create a campaign • Duplicate a campaign • Get a campaign • Get many campaigns • Pause a campaign • Start a campaign 🔧 Contactlist (2 operations) • Add a contact list • Get many contact lists 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Resource IDs and identifiers • Search queries and filters • Content and data payloads • Configuration options Response Format: Native Emelia Tool API responses with full data structure Error Handling: Built-in n8n error management and retry logic 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • Other n8n Workflows: Call MCP tools from any workflow • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Complete Coverage: Every Emelia Tool operation available • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n error handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.
By David AshbyCYBERPULSE AI GRC: automate PCI DSS control evaluation and compliance tracking
Description Automatically evaluates PCI DSS control responses using logic or AI. Designed to speed up compliance workflows, reduce audit fatigue, and flag non-compliance early. Who’s It For: Internal compliance teams PCI DSS auditors Security officers preparing for certification How It Works: Reads PCI controls and responses from Google Sheet Applies logic to classify each control as Compliant, Partial, or Non-Compliant Tags evaluation results Sends output to Sheet, Email, or Drive Requirements: Google Sheet with PCI controls n8n (open-source automation tool) Optional: Gmail or Drive node for delivery Google Sheet Requirements: Columns: ControlID, ControlDescription, Response, Evaluation_Result, Notes Headers must be in row 1 File Templates: PCIControlEvaluation_Template.xlsx Customization Tips: Adjust logic for more strict evaluation Highlight non-compliant results for rapid review Compliance Alignment: • PCI DSS v4.0 • ISO 27001 – Annex A crosswalk • Internal audit programs Setup Instructions: Fill in the Google Sheet template Connect to n8n with Google Sheet node Run the workflow or schedule via Cron node Review and export results 🌐 https://cyberpulsesolutions.com 📧 info@cyberpulsesolutions.com
By Adnan Tariq