by Oneclick AI Squad
This n8n workflow monitors medical equipment usage by reading data daily at 6 AM from a Google Sheet, processes alerts for maintenance or calibration, and sends notifications to technicians and supervisors. Good to Know Runs daily at 6 AM via cron trigger. Requires Google Sheet with equipment data. Sends alerts via email and WhatsApp. Logs all activities in the Google Sheet. Google Sheet Structure Sheet: A: Equipment ID | B: Equipment Name | C: Last Maintenance Date | D: Usage Hours E: Calibration Due | F: Status | G: Technician Email | H: Supervisor Email | I: Last Alert Date Sample Data: E001 | MRI Machine | 2025-07-01 | 150 | 2025-08-15 | Active | tech1@hospital.com | sup1@hospital.com | 2025-08-01 E002 | X-Ray Unit | 2025-06-15 | 200 | 2025-08-10 | Overdue | tech2@hospital.com | sup2@hospital.com | 2025-08-05 How It Works Daily Equipment Check (6 AM)** - Triggers the workflow. Read Equipment Data** - Fetches data from Google Sheet. Process Equipment Alerts** - Identifies maintenance needs. Task Break For 5 Sec** - Adds a delay for processing. Filter Equipment with Alerts** - Filters equipment needing attention. Send Technician Email** - Notifies technicians via email. Send Message (message: send)** - Sends WhatsApp alerts to technicians. Send Critical Alert to Supervisors** - Escalates critical issues via email and WhatsApp. Filter Overdue Equipment** - Identifies overdue maintenance. Update Equipment Status** - Updates sheet with new statuses. Log Maintenance Alerts** - Logs alerts in the sheet. How to Use Import workflow JSON into n8n. Configure nodes with Google Sheet ID, email, and WhatsApp API credentials. Add equipment data to the Google Sheet. Test manually, then activate for daily runs. Requirements Google Sheet with specified structure. Google service account credentials. Email SMTP setup (e.g., Gmail). WhatsApp Business API token. n8n instance. Customizing This Workflow Adjust cron time for different schedules. Modify alert thresholds in the Process Equipment Alerts node. Update notification templates in email and WhatsApp nodes. Extend filters for additional equipment statuses. Want a tailored workflow for your business? Our experts can craft it quickly Contact our team
by Cheng Siong Chin
Extract & Organize Academic Publications with GPT-4 Mini, Google Sheets & Gmail Author: CSChin Example Source: https://www.ncl.ac.uk/singapore/staff/profile/chengchin.html#publications Overview This automated workflow extracts, processes, and organizes academic publications from university staff profile pages using AI-powered extraction. Publications are automatically categorized by type and stored in organized Google Sheets while sending email notifications. Key Features: AI extraction • Auto-categorization • Dual output (Sheets + Email) • Year-based sorting Target Audience Academic Researchers** - Track publications across teams University Administrators** - Manage faculty publication records Research Librarians** - Maintain institutional repositories Department Heads** - Monitor research output PhD Students** - Organize literature reviews Use Cases Automated Publication Tracking - Monitor faculty research output Research Portfolio Management - Maintain publication databases Citation Database Building - Populate citation systems Department Reporting - Generate organized reports by category/year Research Impact Analysis - Track publication trends
by Christian Moises
Gmail AI Email Classifier & Notifier Since Gmail inboxes can quickly become cluttered, this workflow provides an automated AI-based email classification system. It listens for new emails, categorizes them using an AI classifier, applies Gmail labels, and sends you a Telegram notification with a quick summary. If you often miss urgent client messages or struggle with sorting work vs. promotions, this workflow ensures you never overlook important emails. Use case: Especially useful for professionals who receive a high volume of mixed emails (clients, work, promotions). The workflow automatically labels and notifies you of new emails based on their category. How It Works Trigger Input The workflow starts with the Gmail Trigger node, which listens for new incoming emails. By default, it polls every minute, but you can adjust the polling frequency. Email metadata (from, subject, body) is passed downstream. Example JSON input: { "from": "client@example.com", "subject": "Urgent project deadline", "text": "Please review the attached contract ASAP" } Classify Email (AI) The Classification Agent (powered by OpenAI via LangChain) receives the email data. It sorts the email into one of four categories: High Priority – urgent, time-sensitive Work Related – general work emails Promotions – newsletters, offers, sales Other – uncategorized emails The classifier uses a system prompt to ensure output is returned in JSON format for downstream processing. Apply Gmail Labels Based on classification, the workflow applies the corresponding Gmail label: High Priority → “Important + Starred” Work Related → “Work” (custom Gmail label) Promotions → “Promotions” (custom Gmail label) Each label must already exist in Gmail for the operation to work. Generate Notification The AI Agent (notification assistant) takes the classified email and rewrites it into a short, casual notification. Example notification: [High Priority] New email from client@example.com Subject: Urgent project deadline "Please review the attached contract ASAP" Send to Telegram The Telegram node sends the generated notification to your personal chat ID. Requires a Telegram bot created with @BotFather and your chat ID configured. How to Use Import this workflow into n8n. Set up Gmail OAuth2 credentials and connect your Gmail account. Create Gmail labels: High Priority, Work Related, Promotions. Set up a Telegram bot in @BotFather and copy your chatId into the node. Run the workflow — every new email will now be classified, labeled, and notified. Requirements n8n Gmail Trigger** with Gmail OAuth2 credentials OpenAI API key** configured for LangChain nodes Telegram bot** created via @BotFather with your chat ID Existing Gmail labels (Work, Promotions, etc.) Customizing This Workflow You can extend it by: Adding more categories** – e.g., “Finance,” “Personal,” or “Spam.” Changing the notification channel** – send to Slack, Discord, or SMS instead of Telegram. Adjusting classification rules** – edit the system prompt for finer-grained AI sorting. Changing polling frequency** – set Gmail Trigger to every 5 minutes instead of every minute. Expanding extracted fields** – include attachments, links, or CC addresses in the notification.
by Manu
Complete AI-powered sales system Automates lead capture, qualification, and follow-up from multiple channels. AI INTELLIGENCE: Automatic GPT-4 analysis Detects: sentiment, urgency, intent, budget signals Identifies pain points and interests Generates personalized responses LEAD SCORING ENGINE: Score 0-100 based on 10+ variables: Channel (Referral +30, LinkedIn +25, WhatsApp +20, Web Form +15, Email +10) Positive sentiment (+15) High urgency (+25) Purchase intent (+30) High budget (+20) Decision maker (+20) Engagement (+5 per interaction, max 25) MULTI-CHANNEL INPUT: Gmail (incoming emails) Webhook for web forms Webhook for WhatsApp/Telegram All normalized to unified format SMART ROUTER - 5 FLOWS: Schedule Demo: Hot lead with Calendly CTA Send Info: Informative response Create Task: Slack notification for call Nurturing: Cold lead, value-driven email Disqualify: Invalid lead AUTO CRM: Detects new vs existing leads Stores last 10 interactions history Updates score and stage automatically Complete interaction log HOT LEAD ALERTS (Score 70+): Instant Slack notification with lead data, company, score, stage, intent, urgency, pain points, and AI summary. AUTO-NURTURING (Daily 10AM): Filters leads with score 20-60 No contact in 3+ days AI personalized follow-up emails Max 10 per day WEEKLY REPORT (Monday 9AM): Total and new leads Active hot leads count Average score Distribution by stage and channel SETUP: Google Sheets with 3 tabs: Leads, Interactions, Tasks OpenAI API Key Gmail connected Slack channels: #sales, #errors IDEAL FOR: B2B Startups Digital agencies Consulting firms SaaS companies Any business with multi-channel leads Replaces HubSpot, Pipedrive, Close.io - 100% customizable, no monthly fees.
by Samuel Heredia
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Workflow*: **Daily News Aggregator & MongoDB Storage This workflow is designed to run seamlessly in the background, automating the full cycle of news aggregation, storage, and reporting with precision and reliability. Daily Trigger (Cron Node) The process kicks off every morning at 8:00 AM UTC. This scheduling ensures that fresh global news is captured consistently at the start of each day. Perplexity Node At the heart of the workflow, a Perplexity node queries the latest global news. The prompt specifies both the type of news and the JSON structure required, guaranteeing the output is ready for structured storage. The result is a clean feed of headlines, timestamps, sources, and URLs. Data Formatting (Code Node) Since Perplexity’s response is a string, the workflow includes a custom JavaScript function to clean and parse it into a valid JSON array. Each news item is then transformed into its own object, ready for iteration. MongoDB Insertion (Loop Node) Each news article is inserted into the daily_news collection in MongoDB. The workflow ensures that fields such as headline, timestamp, source, URL, and category are stored neatly, with additional metadata available for future filtering and analysis. Aggregation & Notification Prep (Code Node) Once all items are stored, the workflow aggregates the day’s results. This step prepares a digest of what was successfully processed, ensuring visibility into the pipeline’s performance. Email Notification (Gmail Node) Finally, a summary email is sent via Gmail. This message confirms the operation’s success and provides a quick snapshot of the news collected and stored that day. Workflow Flow Cron Trigger → Perplexity API → Format Data → MongoDB Insert → Aggregate Results → Send Email Notification This setup transforms what could be a manual, repetitive task into a streamlined daily routine. It not only guarantees timely and structured storage of news but also provides immediate confirmation, making it an elegant solution for automated information management.
by Oneclick AI Squad
The workflow is triggered manually with user input, searches LinkedIn profiles, processes the results using AI, generates connection recommendations, and delivers them via email. It leverages AI to enhance networking opportunities based on insights from profiles. Good to Know Each email is personalized with the user’s name and recommended connections. Recommendations are based on LinkedIn search results and AI analysis. The system ensures data privacy by processing inputs securely. Email notifications include a curated list of potential connections. How it Works Profile Analysis Workflow Get User Data from Email**: Manually inputs user email and profile information to initiate the workflow. Your Profile Information**: Provides initial user data for LinkedIn search. Search LinkedIn Profiles**: Queries LinkedIn via an API (e.g., SerpAPI) to gather profile data. Process LinkedIn Search Results**: Extracts relevant details from search results. AI Recommendation Workflow AI Profile Analysis**: Uses an AI model (e.g., Ollama Model) to analyze profile data and suggest connections. Create Recommendations**: Generates a curated list of potential connections. Create Final Recommendations**: Refines and formats the recommendation list. Create Email**: Prepares a personalized email with the connection list. Send Email**: Delivers the email to the user. Excel Sheet Structure No persistent Excel sheet is required**; data is processed in-memory and emailed directly. However, optional logging can be set up: Optional Log Sheet (Recommendations): Timestamp: Date and time of recommendation generation. User Email: User’s email address. Profile Name: User’s LinkedIn profile name. Industry: User’s industry. Recommended Connections: List of suggested connections. Sent Status: Whether the email was sent successfully. How to Use Import the Workflow into your n8n instance and configure email integration. Provide User Data: Manually enter the user’s email and profile information in the "Get User Data from Email" node. Configure API Credentials: Set up SerpAPI for LinkedIn searches and email service (e.g., SMTP). Run the Workflow: Execute manually to test the process. Monitor Emails: Check the user’s inbox for the curated connection list. Optional Logging: Set up a Google Sheet to log recommendations if desired. Requirements SerpAPI**: For LinkedIn profile searches. Email Service Integration**: Gmail, SMTP, or similar for email delivery. Ollama Model**: For AI-based profile analysis. n8n Instance**: With SerpAPI, email, and function nodes. Customizing this Workflow Expand Data Sources**: Integrate additional platforms (e.g., Xing) for broader searches. Enhance AI**: Train the Ollama Model for more specific connection criteria (e.g., job role, location). Add Notifications**: Include Slack or SMS alerts for admin tracking. Customize Email**: Adjust the email template for branding or additional details. Automate Trigger**: Replace manual input with a scheduled trigger or webhook.
by Billy Christi
Who is this for? This workflow is perfect for: Agile development teams and project managers who need to quickly set up Jira projects Product managers who want to convert feature ideas into structured user stories and tasks Software development agencies that need to rapidly create detailed project structures for clients Scrum masters seeking to automate the initial project setup and backlog creation process What problem is this workflow solving? Creating comprehensive Jira projects with detailed user stories and sub-tasks is time-consuming and often inconsistent. This workflow solves those issues by: Automating project creation** from basic feature descriptions to fully structured Jira projects Generating professional user stories** following Agile best practices with proper "As a [user], I want to [goal], so that [benefit]" formatting Creating detailed sub-tasks** covering design, development, testing, and documentation phases What this workflow does This workflow transforms raw project ideas into fully structured Jira projects with comprehensive user stories and sub-tasks using AI-powered analysis and automated Jira integration. Step by step: Form Trigger collects project name and feature descriptions through a web form Project Naming uses GPT-4.1 mini to clean and professionalize the project name while generating a unique project key Create Project establishes a new Jira project with proper software development template and configuration Get Status ID retrieves project details and available issue types for story creation Jira Story Generator analyzes project features using AI to create structured user stories with sub-tasks Create Story generates individual Jira stories with proper titles and descriptions Execute Sub-task Workflow automatically creates all associated sub-tasks for each story Gmail Notification sends completion confirmation with project details and direct links How to set up Connect your Jira account by adding your Jira Software Cloud API credentials to all Jira-related nodes Update Jira URL in the "Set Jira URL" node to match your Jira instance (e.g., https://yourcompany.atlassian.net) Add OpenAI API key to the OpenAI Chat Model node for AI-powered story generation Configure Gmail credentials for the notification node and update the recipient email address Update project lead in the Create Project node by replacing the leadAccountId with your user ID Test the workflow using the manual trigger with sample project data Customize story templates in the Structured Output Parser if you need different story formats Set up the sub-workflow by ensuring the Execute Workflow node points to the correct workflow ID How to customize this workflow to your needs Adjust story generation prompts**: modify the AI prompts in the "Jira Story Generator" to match your team's specific story writing style or include additional fields Include estimation**: add story point estimation logic or time tracking fields to generated stories Switch AI models**: replace the OpenAI Chat Model node with other AI providers like Google Gemini, Claude, or local models by using the appropriate n8n AI nodes for different cost and performance requirements Need help customizing? Contact me for consulting and support: 📧 billychartanto@gmail.com
by WeblineIndia
Auto FAQ Generator for Clients using NewsAPI, OpenAI GPT-4.1 and Google Sheets This workflow automatically generates weekly client-ready investment FAQs by combining market news (NewsAPI) and portfolio data (Google Sheets) using OpenAI GPT-4.1. The final FAQs are structured and saved back into Google Sheets. Quick Implementation Steps Import the workflow into n8n Add your NewsAPI API key in the HTTP Request node Connect your Google Sheets account Ensure your sheet has required columns: Client Name Asset Investment Amount Current Value Last Week Value Risk Level Sector Add your OpenAI API key Create a destination sheet with columns: Q1–A5 Activate the workflow That’s it! Your FAQs will be generated every Monday at 8 AM. What It Does This workflow automates the process of generating weekly investment FAQs for clients by combining real-time market insights with portfolio performance data. It ensures that financial advisors or teams can deliver consistent, relevant and easy-to-understand updates without manual effort. It pulls the latest tech-focused market news using NewsAPI and combines it with structured portfolio data stored in Google Sheets. The workflow then analyzes portfolio trends such as high-risk assets and declining investments to enrich the context. Using OpenAI, the workflow generates 5 practical and client-friendly FAQs, each with a short, one-line answer. These FAQs are then structured and saved into a Google Sheet, making them easy to reuse, share or distribute. Who’s It For Financial advisors and wealth managers Investment firms and portfolio managers Fintech startups Client relationship teams Anyone managing client portfolios and communications Requirements To use this workflow, you will need: n8n account (self-hosted or cloud) NewsAPI account** (https://newsapi.org/) OpenAI API key** Google Sheets account** Required Google Sheets Structure 📥 Input Sheet (Portfolio Data) Must include these exact column headers: Client Name Asset Investment Amount Current Value Last Week Value Risk Level Sector 📤 Output Sheet (FAQs) Create a sheet with the following columns: Q1, A1 ,Q2, A2,Q3, A3, Q4, A4, Q5, A5 How It Works & Set Up 1. Schedule Trigger Node: Weekly Portfolio & News Trigger Runs every Monday at 8:00 AM You can modify timing as needed 2. Fetch Market News Node: Fetch Market News (HTTP Request) Endpoint: https://newsapi.org/v2/top-headlines Query Parameters: sources=techcrunch apiKey=YOUR_API_KEY Action Required: Add your NewsAPI key manually 3. Check News Availability Node: IF Node Checks whether news articles exist If yes → formats top 5 articles If no → uses fallback message 4. Format News Node: Format Top News Extracts top 5 headlines and descriptions Node: Fallback News Message Used when no news is available: "No major market news this week. Focus on portfolio performance" 5. Fetch Portfolio Data Node: Fetch Portfolio Data (Google Sheets) Connect your Google account Select your portfolio sheet 6. Format Portfolio Summary Node: Set Node Combines all rows into readable format: Client Name | Asset | Investment Amount | Current Value | Last Week Value | Risk Level | Sector 7. Analyze Portfolio Node: Code Node Calculates: Number of high-risk assets Number of assets losing value 8. Merge Data Node: Merge Node Combines: News data Portfolio summary & analysis 9. Generate FAQs using AI Node: OpenAI Model: gpt-4.1-nano Action Required: Add your OpenAI API credentials AI generates: Exactly 5 FAQs Focus on trends, risks, opportunities Simple one-line answers 10. Extract Structured Output Node: Set Node Uses regex to extract: Q1–Q5 A1–A5 11. Save FAQs to Google Sheets Node: Google Sheets (Append) Writes structured FAQs into output sheet Ensure your sheet has columns: Q1–A5 How To Customize Nodes Change News Source** Modify sources=techcrunch to another provider Adjust AI Output Style** Edit prompt in OpenAI node Example: longer answers, different tone Change Schedule** Update trigger node (daily, weekly, etc.) Modify Portfolio Analysis** Update Code node logic for deeper insights Add-ons Send FAQs via Email (Gmail/SMTP node) Push data to dashboards (Notion, Airtable) Send alerts via Slack or Microsoft Teams WhatsApp or SMS notifications Add historical comparison (week-over-week trends) Use Case Examples Weekly investor update emails Portfolio performance summaries for clients Internal advisory team insights Automated client reporting systems Fintech app content generation There can be many more use cases depending on how you extend the workflow. Troubleshooting Guide | Issue | Possible Cause | Solution | |------|--------------|----------| | No news data fetched | Missing or invalid NewsAPI key | Add valid API key in HTTP node | | Empty FAQs | OpenAI credentials missing | Configure OpenAI API key | | FAQs not structured properly | AI output format changed | Ensure prompt format is unchanged | | Google Sheets not updating | Incorrect sheet or permissions | Reconnect credentials and verify sheet | | Portfolio data not showing | Incorrect column names | Ensure exact headers are used | | Workflow not triggering | Schedule inactive | Activate workflow | Need Help? If you need assistance with: Setting up this workflow Customizing AI prompts Adding advanced automation features Integrating with your business tools We’re here to help! Contact WeblineIndia for expert support in building and scaling automation workflows tailored to your business needs.
by Billy Christi
What this workflow does This workflow creates an automated web scraper that accepts form submissions, extracts specific data from any website using AI, and emails the results back to you. Step by step: Web Scraper Form Submission provides a web form interface where users submit a URL and specify what data to extract Get HTML from Source URL fetches the complete HTML content from the provided website HTML Extractor processes the raw HTML and extracts the body content for analysis Data Extractor LLM Chain uses Google Gemini AI to intelligently analyze the content and extract only the specific data requested by the user Structured Output Parser formats the AI response into clean JSON structure with standardized format Gmail Send Result delivers the extraction results via email including the source URL, extraction request details, and clean extracted results How to set up Connect your Google Gemini API to the Google Gemini Chat Model node for AI-powered data extraction Connect your Gmail account to the Gmail node for sending result emails Update the recipient email in the Gmail node Customize the extraction prompt in the Data Extractor LLM Chain node based on your specific requirements How to customize this workflow to your needs Switch AI models**: Replace Google Gemini with OpenAI, Claude, or other LLM providers in the Chat Model node based on your accuracy requirements and budget preferences Change result delivery**: Replace Gmail with Google Sheets for data storage, Outlook for corporate email, Slack for team notifications, or webhook integrations for custom applications Customize extraction prompts**: Modify the LLM prompt in the Data Extractor Chain to handle specific data types, extraction formats, or industry-specific terminology for your use case Need help customizing? Contact me for consulting and support: 📧 billychartanto@gmail.com
by Sana Fatima
From Leads to Smiles – Automated Patient Engagement______Turn every lead into a booked appointment with AI 💡 Why this workflow? Dental clinics lose 50%+ of leads due to slow response. This template ensures instant engagement with AI-powered personalization. Works for dentists, beauty clinics, physiotherapists, or any appointment-based business. Description: When a new patient submits a form (e.g., teeth whitening, Invisalign, implants), the workflow: Captures and stores the lead in Google Sheets. 2.Uses an AI Agent to generate a friendly, personalized welcome message. Instantly sends tailored notifications to both the patient and the dentist. No more generic thank-you emails → engage leads before they go cold! 🚀 Category: Marketing & Sales Customer Engagement Healthcare Automation 📖 Step-by-Step Guide (for beginners) Trigger (Google Sheets): Every time a new patient submits a Google Form, the lead is automatically captured in Google Sheets. AI Agent (OpenAI Chat Model): Generates a personalized welcome message Patient Notification (Email): Sends a warm, engaging welcome message with appointment details instantly. Dentist Notification (Email): Alerts the dentist with lead details so they can follow up quickly. Execution: Just hit Execute Workflow → watch as your clinic never loses another lead. 👉 Perfect for beginners in AI + n8n automation. You can duplicate this template, connect your Google Sheet + Gmail + OpenAI API key, and start converting leads today. Tags: lead generation dentist crm google sheets ai agent chatgpt email automation
by Siddhant
Hourly Email Summary: This agent scans your inbox every 4 hour and summarizes new emails into a clean, actionable Slack message. Powered by GPT-4, it classifies emails by Urgency (High, Medium, Low) and Intent (Awaiting Reply, To Respond, Comment, Notification, Marketing). No more inbox FOMO — just what you need to act fast. Main Use Cases: • Stay on top of important threads without refreshing your inbox constantly • Prioritize tasks and replies based on urgency and context • Catch missed follow-ups by surfacing emails that need a response • Filter out noise like marketing emails or low-priority notifications • Enable async decision-making by keeping the team updated on critical emails via Slack • Reduce cognitive load by letting AI handle sorting and triaging ⸻ ✅ Steps to Use Connect Your Accounts: Add your Gmail, Slack, Google Sheets, and OpenAI credentials inside n8n. Create Gmail Labels (Required): Go to your Gmail settings and create labels matching the following format: AI Agent/To Respond, AI Agent/Awaiting Reply, AI Agent/Notification, AI Agent/Marketing, etc. These are used by the workflow to auto-tag emails based on intent. Create a Google Sheet with 2 Tabs • Name the sheet something like “N8N - Emails”. • Add two sheets/tabs inside: • Sheet1 → stores all processed emails • Sheet2 → stores only the latest batch for digest view • In both sheets, add these columns (first row): From | Summary | Intent | Category | TimeStamp | Urgency Import the Workflow: Upload or paste the .json file into your n8n instance. Make sure each node is linked to your active credentials. Configure Slack Channel: In the Slack node, select the channel where you want urgent alerts and digest summaries to be posted. Adjust Schedule (Optional): Default: runs every hour. You can tweak this to suit your preference (e.g., every 30 min or 2 hours). Run a Test: Execute manually once to check: • Emails are getting processed • Labels are added correctly in Gmail • Slack notifications are triggered • Data is logged in Google Sheets Turn It On • Once everything looks good, activate the workflow. • Your inbox will now be triaged in real-time — sorted, labeled, summarized. Step-by-Step Breakdown: ⏰ Schedule Trigger: Runs every hour to kick off the workflow automatically. 📩 Fetch Emails & Labels • Pulls all Gmail messages received in the last 4 hours. • Also fetches Gmail labels to use for tagging messages based on intent. 🤖 Analyze with GPT-4 • Each email is analyzed using GPT-4. • Output includes: • Summary • Urgency: High, Medium, Low • Intent: To Respond, Awaiting Reply, Marketing, Notification, etc. • Category: Customer, Investor, Spam, etc. Classify and Label • Emails are tagged with the right intent label inside Gmail. 5.🚨 Slack Alerts for High Urgency • If an email is marked High Urgency, it sends an alert to a designated Slack channel with all key details. 📊 Google Sheets Logging • All emails are logged to two Google Sheets: • Sheet1: All messages, for long-term record. • Sheet2: Temporary sheet to collect latest batch for digest. ⏳ Wait + Digest Preparation • After logging, the workflow waits 30 seconds. • It then fetches recent entries from Sheet2, filters out older messages, and groups them by Medium and Low urgency. 📬 Slack Digest Summary • A clean digest is posted on Slack showing only the Medium and Low urgency messages from the past hour — helping you catch up without inbox overload. Uses a System Prompt to define its role as an AI Chief of Staff. Uses a User Prompt that instructs GPT-4 to analyze each email and return a structured JSON with the following: • summary – One-line summary of the email • urgency – High / Medium / Low • category – Investor, Customer, Support, Spam, Other • Intent – One of: • To Respond: Needs your reply • Awaiting Reply: You’re waiting for a response • Notification: Auto-updates from tools or services • Meeting Update: Calendar or schedule changes • Marketing: Promotional or cold emails • FYI: Informational emails that don’t need action The output is clean JSON with built-in guardrails to avoid hallucinations or irrelevant content. Only real message data is used for summaries and classification. Sections with no relevant data are omitted to keep it concise. 🧩 What’s Next This agent already cuts through inbox noise and gives you clarity — but there’s more you can build on top: 💡 Suggestions to Improve: • Train on your past threads to make prioritization even smarter • Allow custom rules per sender or domain (e.g. always mark investor emails as High) • Add emoji tags or reactions in Slack to quickly mark emails as done or follow-up • Support voice summary via Slack audio snippet or Loom integration 🚀 Next Features You Could Add: • Reply-from-Slack: One-click smart reply suggestions that can be sent right from Slack • Cross-inbox support: Add Outlook or multiple Gmail accounts • Weekend Digest: A weekly email or Slack drop with trends (top senders, most flagged categories) • Daily Timeline View: Generate a Notion page that logs the day’s most critical communication
by Aziz B
Overview This workflow is an AI-powered Booking Assistant that automates restaurant and event reservations through Telegram. It interacts with the user in natural conversation, collects booking details (guest count, preferences, date/time, and special requests), finalizes the draft, and confirms the reservation by storing it in Google Calendar and sending an email confirmation — fully automated end-to-end. How It Works 1. User Interaction The workflow starts with a Telegram welcome message. The AI agent asks step-by-step questions: Number of guests Seating preference (indoor/outdoor/private room) Special occasion requests (birthday, date, etc.) Preferred date & time Once details are gathered, it generates a draft booking summary. 2. Confirmation & Personal Details The user reviews the draft and confirms. The assistant then asks for personal details (name, email, phone number). 3. Booking & Notifications After confirmation, the details are sent to Google Calendar to create an event. A confirmation email is sent to the user with all booking information. A final Telegram message confirms that the reservation is successfully completed. How to Use Triggered directly from Telegram Bot. Simply start chatting with the bot to begin the reservation process. The assistant will guide the user step by step until the booking is finalized. Once completed, the user receives both an email confirmation and a Telegram confirmation message. Requirements To use this workflow, you’ll need: n8n account (self-hosted or cloud) Telegram Bot Token (for chat interaction) OpenAI or OpenRouter API Key (for AI-driven conversation) Google Calendar API access (to create bookings) Gmail / SMTP credentials (to send confirmation emails)