Workflow Templates

Summarize Google Alerts with Gemini Turn your noisy Google Alerts folder into a concise, AI-curated executive briefing. This workflow replaces dozens of individual notification emails with a single, structured daily digest. How it works Ingest:** Fetches unread Google Alerts emails from your Gmail inbox. Clean:** Extracts article links, scrapes the website content, and strips away ads and clutter to ensure high-quality AI processing. Analyze:** Uses Google Gemini to summarize each article into a concise 2-4 sentence overview. Deliver:** Compiles a professional HTML email report sorted by topic, sends it to you, and automatically marks the original alerts as read. Set up steps Connect Gmail:** Authenticate your Gmail account to allow reading alerts and sending the digest. Connect Gemini:** Add your Google Gemini API key. Configure Recipient:* Update the *Send Email Digest** node with your desired destination email address. Schedule:* (Optional) Replace the Manual Trigger with a *Schedule Trigger** (e.g., every morning at 7 AM) to fully automate the process.

How It Works Automates daily learner engagement monitoring, progress analysis, and personalized feedback delivery for training programs. Target audience: learning and development teams, corporate training managers, and online education platforms scaling instructor workload. Problem solved: manual progress tracking consumes instructor time; AI analysis identifies struggling learners early for intervention. Workflow runs daily checks on learner activity, retrieves course data and progress, analyzes engagement with OpenAI models, evaluates quiz scores, generates performance summaries, sends progress reports to learners, emails instructors on at-risk cases, generates learning paths, and triggers manager notifications. Setup Steps Configure daily schedule trigger. Connect learning management system APIs (LMS). Set OpenAI keys for progress analysis. Enable Gmail for multi-recipient notifications. Map learner risk thresholds and escalation rules. Prerequisites LMS platform credentials, OpenAI API key, learner database, email service for notifications, manager contact lists. Use Cases Corporate onboarding programs tracking employee progress, online learning platforms identifying struggling students Customization Adjust AI analysis criteria for your curriculum. Integrate Slack for instructor alerts. Benefits Reduces instructor workload by 70%, identifies at-risk learners 2 weeks early

How It Works This workflow automates regulatory compliance monitoring and policy violation detection for enterprises managing complex governance requirements. Designed for compliance officers, legal teams, and risk management departments, it addresses the challenge of continuous policy adherence across organizational activities while reducing manual audit overhead.The system initiates on schedule, triggering compliance checks across operational data. Solar compliance data generation simulates policy document collection from various business units. Claude AI performs comprehensive policy validation against regulatory frameworks, while parallel NVIDIA governance models analyze specific compliance dimensions through structured outputs. The workflow routes findings by compliance status: violations trigger immediate escalation emails to compliance teams with detailed Slack notifications, warnings generate supervisor alerts with tracking mechanisms, and compliant activities proceed to standard documentation. All execution paths merge for consolidated audit trail creation, logging enforcement actions and generating governance reports for regulatory submissions. Setup Steps Configure Schedule Compliance Check node with monitoring frequency Add Claude AI credentials in Workflow Configuration and Policy Validation nodes Set up NVIDIA API keys for governance output parser and agent modules in respective nodes Connect Gmail authentication for compliance team alerts and configure recipient distribution lists Integrate Slack workspace credentials and specify compliance channel webhooks Prerequisites Claude API access, NVIDIA API credentials, Gmail/Google Workspace account Use Cases Financial services regulatory compliance (SOX, GDPR), healthcare HIPAA monitoring Customization Add industry-specific regulatory frameworks, integrate document management systems Benefits Reduces compliance audit time by 70%, ensures consistent policy application across departments

Description This workflow turns scattered user feedback into a structured product backlog pipeline. It collects feedback from three channels (Telegram bot, Google Form/Sheets, and Gmail), normalizes it, and sends it to an AI model that: Classifies the feedback (bug, feature request, question, etc.) Extracts sentiment and pain level Estimates business impact and implementation effort Generates a short summary Then a custom RICE-style priority score is computed, a Jira ticket is created automatically, a Notion page is generated for documentation, and a monthly product report is sent by email to stakeholders. It helps product & support teams move from “random feedback in multiple tools” to a repeatable, data-driven product intake process with zero manual triage. Context In most teams, feedback is: spread across emails, forms, and chat messages manually copy–pasted into Jira (when someone remembers) hard to prioritize objectively nearly impossible to review at the end of the month This workflow solves that by: Centralizing feedback from Telegram, Google Forms/Sheets, and Gmail Automatically normalizing all inputs into the same JSON structure Using AI to categorize, tag, summarize, and score each request Calculating a RICE-based priority adapted to your tiers (free / pro / enterprise) Creating a Jira issue with all the context and acceptance criteria Generating a Notion page for each feedback+ticket pair Sending a monthly “Product Intelligence Report” by email with insights & recommendations The result: less manual work, better prioritization, and a clear story of what users are asking for. Target Users This template is designed for: Product Managers and Product Owners SaaS teams with multiple feedback channels Support / CS teams that need a structured escalation path Project Managers who want objective, data-driven prioritization Any team that wants “feedback → backlog” automation without building a custom platform Technical Requirements You’ll need: Google Sheets credential Gmail credential Telegram Bot + Chat ID Google Form connected to a Google Sheet Jira credential (Jira Cloud) Notion credential OpenAI/ Anthropic credential for the AI analysis node An existing Jira project where tickets will be created A Notion database or parent page where feedback pages will be stored Workflow Steps The workflow is organized into four main sections: 1) Triggers (Multi-channel Intake) Telegram Trigger – Listens for new messages sent to your bot Google Form / Sheet Trigger – Listens for new form responses / rows Gmail Trigger – Listens for new emails matching your filter (e.g. [Feedback] in subject) All three paths send their payloads into a “Data Normalizer” node that outputs a unified structure: 2) Request Treated and Enriched (AI Analysis) Instant Reply (Telegram only) – Sends a quick “Thanks, we’re analysing your feedback” message User Enrichment – Enriches user tier based on mapping Message a Model (AI) classifies the feedback extracts tags scores sentiment, pain, business impact, effort generates a short summary & acceptance criteria JSON Parse / Merge – Merges AI output back into the original feedback object 3) Priority Calculation & Jira Ticket Creation Priority Calculator applies a RICE-style formula using: pain level business impact implementation effort user tier weight assigns internal priority: P0 / P1 / P2 / P3 maps to Jira priority: Highest / High / Medium / Low Create Jira Issue – Creates a ticket with: summary from AI description including raw feedback, AI analysis, and RICE breakdown labels based on tags priority based on the calculator Post-processing – Prepares a clean payload for notifications & logging IF (Source = Telegram) – Sends a rich Telegram message back to the user with: Jira key + URL category, priority, RICE score, tags, and estimated handling time Append to Google Sheet (Analytics Log) – Logs each feedback with: source, user, category, sentiment, RICE score, priority, Jira key, Jira URL Create Notion Page – Creates a documentation page linking: the feedback the Jira ticket AI analysis acceptance criteria 4) Monthly Reporting (Product Intelligence Report) Monthly Trigger – Runs once a month Query Google Sheet – Fetches all feedback logs for the previous month Aggregate Monthly Stats – Computes: feedback volume breakdown by category / sentiment / source / tier / priority average RICE, pain, and impact top P0/P1 issues and top feature requests Message a Model (AI) – Generates a written “Product Intelligence Report” with: executive summary key insights & trends top pain points strategic recommendations Parse Response: Extracts structured insights + short summary Create Notion Report Page with: metrics, charts-ready tables, insights, and recommendations Append Monthly Log to Google Sheet – Stores high-level stats for historical tracking Send Email with a formatted HTML report to stakeholders with: key metrics top issues recommendations link to the full Notion report Key Features Multi-channel intake: Telegram + Google Forms/Sheets + Gmail AI-powered triage: automatic category, sentiment, tags, and summary RICE-style priority scoring with tier weighting Automatic Jira ticket creation with full context Notion documentation for each feedback and for monthly reports Google Sheets analytics log for exploration and dashboards Monthly “Product Intelligence Report” sent automatically by email Designed to be adaptable: you can plug in your own labels, tiers, and scoring rules Expected Output When the workflow is running, you can expect: A Jira issue created automatically for each relevant feedback A confirmation email A Telegram confirmation message when the feedback comes from Telegram A Google Sheet filled with normalized feedback and scoring data A Notion page per feedback/ticket with AI analysis and acceptance criteria Every month: a Notion “Monthly Product Intelligence Report” page a summary email with key metrics and insights for your stakeholders How it works Trigger – Listens to Telegram / Google Forms / Gmail Normalize – Converts all inputs to a unified feedback format Enrich with AI – Category, sentiment, pain, impact, effort, tags, summary Score – Computes RICE-style priority and maps to Jira priority Create Ticket – Opens a Jira issue + Notion page + logs to Google Sheets Notify – Sends Telegram confirmation (if source is Telegram) Report – Once a month, aggregates everything and sends a Product Intelligence Report Tutorial Video Tutorial video: Watch the Youtube Tutorial video About me I’m Yassin a Project & Product Manager Scaling tech products with data-driven project management. 📬 Feel free to connect with me on Linkedin

Introduction Automates scholarship tracking by scraping university sites, assessing eligibility via AI, and publishing results to WordPress or Slack. Eliminates manual searches for students, counselors, and education platforms, enabling scalable curation and timely notifications. How it Works Webhook triggers parallel scraping of NUS, NTU, SIT, SUTD → merge data → AI evaluates eligibility → aggregate qualified scholarships → generate summaries → post to WordPress/Slack → send email notifications with appeal options. Setup Steps Configure OpenAI credentials and eligibility prompt template Update HTTP requests with university URLs and selectors Add WordPress site URL and API credentials Create Slack webhook and notification channel Configure Gmail/SMTP for email notifications Workflow Webhook → Scrape 4 Universities (Parallel) → Merge Data → Prepare Context → AI Eligibility Check → Aggregate Results → Generate Summary → Check Status → Publish Slack/Email/WordPress → Handle Appeals Workflow Steps Scraping: Fetch scholarship pages from four universities simultaneously Merge: Combine data into a unified dataset AI Processing: Analyze eligibility criteria, deadlines against student profile Aggregation: Consolidate qualified scholarships with match scores Publishing: Post to WordPress, send Slack/email with results Appeals: Webhook handles rejection appeals with AI review Prerequisites OpenAI API key, WordPress site with REST API, Slack workspace with webhook, Gmail/SMTP credentials, student profile data (GPA, citizenship, major) Use Cases Counselors automating recommendations for 100+ students, financial aid offices aggregating departmental opportunities Customization Add universities (SMU, SUSS, international institutions), include government schemes (MOE, Edusave, Mendaki) Benefits Saves 10+ hours weekly per counselor, monitors 50+ scholarships automatically, provides AI eligibility matching (85%+ accuracy)

Introduction Automates Singapore COE price tracking, predicts trends using AI, and recommends optimal car purchase timing. Scrapes LTA data biweekly, analyzes historical trends, forecasts next 6 bidding rounds, and sends alerts when buying windows appear—saving time and identifying cost-saving opportunities. How it Works Biweekly trigger scrapes LTA COE data → processes historical trends → AI predicts 6-month prices → compares current vs forecast → generates buy/wait recommendations → alerts sent via Gmail or Telegram. Setup Steps Add NVIDIA/OpenAI API credentials in n8n Connect Google Sheets for data storage Authenticate Gmail/Telegram for notifications Schedule trigger for Wednesdays 8PM SGT Configure alert thresholds in conditional nodes Workflow Schedule Trigger → HTTP Request (Scrape LTA) → Data Processing → Google Sheets (Store) → AI Prediction → Analysis Engine → Conditional Logic → Gmail/Telegram Notification Workflow Steps Scraping: Extract COE prices from OneMotoring Processing: Calculate moving averages, volatility, seasonal trends Storage: Save to Google Sheets with timestamps Prediction: AI forecasts next 6 bidding rounds Analysis: Compare current vs predicted prices, generate recommendation Notification: Alerts via email/Telegram Prerequisites NVIDIA/OpenAI API key, Google account (Sheets), Gmail/Telegram for notifications, basic COE category knowledge Use Cases First-time buyers monitoring price dips, fleet managers timing bulk purchases Customization Add economic indicators, integrate car loan calculators, track parallel imported car prices Benefits Saves hours of manual monitoring, captures 10–15% price dips, provides data-driven purchase timing (potential $5K–$15K savings)

This workflow acts as your personal inbox assistant. It automatically filters, classifies, and responds to incoming emails using AI, saving you from manually sorting through leads or inquiries 24/7. 👥 Who’s it for Freelancers & Consultants** handling their own sales pipeline. Sales Professionals** who need to book meetings instantly. Small Business Owners** who want to automate customer support or lead triage. Agencies** managing inbound inquiries for multiple clients. ⚙️ How it works This workflow monitors your Gmail inbox and processes emails in three main stages: Filtering: It first checks if the sender is on your "Whitelist" (a Google Sheet). It also ignores automated calendar replies (like "Accepted" or "Declined" notifications) to prevent loops. AI Analysis: OpenAI (GPT-4) reads the email body to understand the sender's intent. Action: Based on the intent, it takes one of three paths: Schedule Meeting: If the lead wants to meet, it creates a Google Calendar event, sends a confirmation email with the link, and notifies you on Telegram. Auto Reply: If the lead declines or isn't interested, it sends a polite, context-aware "thank you" email. Needs Review: If the email is unclear, it waits (configurable delay) and sends a gentle follow-up email to re-engage them. 📋 Requirements n8n** (Self-hosted or Cloud) Gmail Account** (Connected via OAuth2) Google Sheets** (For the whitelist) Google Calendar** (For booking meetings) OpenAI API Key** (GPT-4o-mini or similar model) Telegram** (Optional, for notifications) 🛠️ How to set up Prepare the Whitelist: Create a Google Sheet with three columns: email, first_name, and company. Add the email addresses you want the bot to respond to. Configure Credentials: Connect your Google (Gmail, Sheets, Calendar) and OpenAI accounts in the workflow credentials settings. Link the Sheet: In the "Get row(s) in sheet" node, select your whitelist spreadsheet. Set the Model: Check the "Message a model" nodes to ensure your OpenAI model (e.g., gpt-4o-mini) is selected. Telegram (Optional): If you want notifications, create a bot with @BotFather and add your Chat ID/Credentials. If not, you can disable/remove the Telegram nodes. 🎨 How to customize the workflow Adjust the Delay:* The *"Wait"* node is currently set to *minutes for testing. Change this to 3 Days (or your preferred duration) for a real-world scenario. Brand Your Emails:* Open the *Code** nodes (e.g., "Personalize AI Reply"). You will see HTML code inside. Update the senderName, senderEmail, and footer text to match your brand identity. Refine AI Prompts:* You can modify the system prompt in the *"Message a model"** node to change the AI's tone (e.g., make it more formal or casual). 🧑‍💻 Creator Information Developed by: Adem Tasin 🌐 Website: ademtasin.com 💼 LinkedIn: Adem Tasin

Overview This workflow is designed to monitor the Top 5 cryptocurrencies in real-time, calculate trading signals (BUY, SELL, HOLD), and send human-readable alerts through multiple channels. It integrates data fetching, signal processing, AI-generated insights, and multi-channel notifications to provide a professional-grade crypto monitoring solution. Setup Schedule the trigger Fetch real-time coin data (CoinGecko, Binance API) Filter only required fields Check each data from loop Add the logic for minimum percentage comparison Use AI for analysis enhanced insights Send the notification only if signal is 'SELL' or 'BUY' Key Features Real-Time Crypto Monitoring: Continuously evaluates the top 5 cryptocurrencies for trading signals. Dynamic Signal Calculation: Generates BUY, SELL, HOLD signals based on 24h price change. If price changed below or above 2% the dynamic signal will assign to dedicated coin. Signal Change Alerts: Sends notifications only when meaningful changes occur. Human-Readable Messaging: Converts numeric signals into readable alerts. AI Insights: Provides explanations or trading advice via OpenAI. Multi-Channel Delivery: Supports WhatsApp, Telegram, and Email. Looped Processing: Each coin is processed independently for accurate alerting. Wait / Delay Node: Prevents API rate limit issues and controls alert flow. Requirements OpenAI API WhatsApp API Telegram API SMTP Credentials or Gmail Credentials.

Description This workflow helps you find and evaluate job opportunities automatically, without spending hours searching and comparing roles. It uses your resume to look for relevant jobs on LinkedIn, checks how well each role matches your profile, and organises everything neatly in Google Sheets so you can focus on applying to the best opportunities. How it works On a schedule, the workflow downloads your resume from Google Drive and analyses it to understand your skills and experience. Based on this, it creates LinkedIn job searches and pulls in recent job listings. Each job is then reviewed using AI to compare the job description with your resume, produce a match score, suggest resume improvements, and generate a tailored cover letter. All results are saved to Google Sheets, and you’re notified by email when the run finishes. How to use Make a copy of the Google Sheets template and keep it for your own job tracking. Upload your resume (PDF) to Google Drive. Connect your Google Drive, Google Sheets, Gmail, and AI credentials in n8n. Update the Config node with your preferences (remote work, Easy Apply, job limit). Paste your copied Google Sheet IDs into the workflow. Turn on the Schedule Trigger and activate the workflow. Requirements Google Drive account for storing your resume Google Sheets account for tracking results Gmail account for notifications AI model access (Google Gemini or similar) n8n (cloud or self-hosted) Customising this workflow You can easily adapt this workflow to suit your goals. Change the job limits, locations, or remote preferences in the Config node. Update the AI prompts to target different roles or industries, or extend the workflow to send results to tools like Notion, a CRM, or your own application tracker. Good to know This workflow is designed to help you screen and prepare for jobs, not to apply automatically. Match scores are a guide, not a guarantee, so it’s always worth reviewing roles manually. Also, since LinkedIn pages can change over time, you may occasionally need to update HTML selectors to keep things running smoothly.

How It Works This workflow automates quality event risk assessment through AI-powered multi-agent analysis with mandatory human oversight for critical decisions. Designed for quality managers, compliance officers, and risk analysts in manufacturing, healthcare, or service industries, it solves the challenge of consistent, transparent risk evaluation while maintaining human accountability. When quality events are detected, the system orchestrates specialized AI agents (traceability, risk assessment, and recall evaluation) to analyze different risk dimensions simultaneously. Results are synthesized, routed through human approval gates based on risk severity, and distributed via automated notifications. This ensures high-risk decisions receive proper scrutiny while low-risk events flow efficiently through automated channels. Setup Steps Configure NVIDIA NIM API credentials with Llama-3.1-70B-Instruct model access Set up routing logic thresholds Connect Gmail SMTP for executive alerts and Slack webhook for team notifications Configure human approval nodes with designated approver email addresses Customize AI agent prompts for industry-specific risk criteria Prerequisites NVIDIA NIM API key, Gmail account with app password Use Cases Manufacturing defect escalation, food safety incident management Customization Modify risk scoring thresholds, add industry-specific compliance agents Benefits Reduces risk assessment time by 75%, ensures consistent evaluation methodology

AI-Powered Lead Qualification & Enrichment Pipeline 🎯 Who is this for? This template is perfect for: Marketing Teams** looking to automatically qualify inbound leads from campaigns Sales Teams** wanting to prioritize high-value prospects instantly Agencies** offering lead qualification as a service to clients SaaS Companies** routing trial signups to appropriate nurture sequences B2B Service Providers** scoring and enriching leads from multiple sources 💡 What problem does it solve? Manual lead qualification is slow, inconsistent, and expensive. Sales teams waste hours on unqualified leads while hot prospects go cold. This workflow: Eliminates manual research** - Automatically enriches company data via LinkedIn Scores leads instantly** - AI analyzes 15+ data points to score 0-100 Routes intelligently** - Hot leads get instant alerts, warm leads enter nurture Personalizes outreach** - AI generates custom emails based on company context ⚡ What this workflow does 1. Lead Capture & Validation Captures leads via built-in n8n Form (embeddable on any website) Validates email format and detects business vs personal emails Normalizes data from various field naming conventions 2. Company Enrichment via Apify Uses Google Search to find company's LinkedIn profile Scrapes LinkedIn for industry, size, description, specialties, and more Gracefully skips enrichment for personal emails (Gmail, Yahoo, etc.) 3. AI Lead Qualification (GPT-4.1) Scores leads 0-100 based on buying signals Assigns tier: Hot (80+), Warm (60-79), Cold (40-59), Disqualified (<40) Identifies buyer persona (Decision Maker, Influencer, Champion, etc.) Generates personalized talking points and risk factors 4. Intelligent Routing & Actions Hot Leads**: Instant Slack alert + AI-generated personalized email + HubSpot contact Warm Leads**: Slack notification for nurture sequence Cold Leads**: Logged for future reference All Leads**: Recorded to Google Sheets with full qualification data 🔧 Setup Required Credentials | Service | Purpose | |---------|---------| | OpenAI | AI qualification & email generation | | Apify | Google Search + LinkedIn scraping | Optional Credentials | Service | Purpose | |---------|---------| | Slack | Lead alerts and notifications | | HubSpot | CRM contact creation | | Gmail | Sending personalized emails | | Google Sheets | Lead database logging | Apify Setup Create account at apify.com Get API token from Settings → Integrations Open the Apify HTTP nodes and replace YOUR_API_KEY with the API token obtained in the above step Apify Actors Used Google Search Scraper PPR** (Actor ID: G9PR1B1upfS0mRvp0) - ~$0.004/search LinkedIn Company Scraper PPR** (Actor ID: G9y3V8J1hXYJTf1Ho) - ~$0.02/company Total cost: ~$0.02-0.03 per enriched lead 📊 Lead Scoring Criteria | Score | Tier | What it means | |-------|------|---------------| | 80-100 | 🔥 Hot | Strong buying signals, budget confirmed, urgent timeline | | 60-79 | 🌡️ Warm | Good fit, some buying signals, needs nurturing | | 40-59 | ❄️ Cold | Potential fit but unclear intent | | 0-39 | ⛔ Disqualified | Poor fit, spam, or invalid | 🎨 Customization Modify Form Fields Edit the "Lead Capture Form" node to add/remove fields for your use case. Adjust AI Scoring Edit the system prompt in "AI Lead Qualification" to customize: Score thresholds for your industry Buyer persona definitions Custom qualification criteria Add Integrations Easily extend with: Pipedrive, Salesforce, or other CRMs Email sequences (Mailchimp, ActiveCampaign) SMS notifications (Twilio) Calendar booking (Calendly) 📈 Example Output { "qualification": { "score": 85, "tier": "Hot", "buyerPersona": "Decision Maker", "urgencyLevel": "High" }, "insights": { "keyInsights": [ "VP-level with direct budget authority", "Company in growth phase (51-200 employees)", "Industry aligned with our ICP" ], "talkingPoints": [ "Reference their sustainability focus", "Highlight ROI for mid-market companies" ] } } 🙋 Need Help? Check the sticky notes in the workflow for section-by-section guidance Ensure Apify credentials are properly configured Test with a business email (not Gmail/Yahoo) to see full enrichment Created by Agentical AI - AI Automation Agency specializing in workflow automation and AI solutions.

Contract Template Generator with E-Signature Integration What this workflow does This workflow automates the full contract lifecycle—from request intake to document generation and electronic signature completion. It receives contract requests via webhook, generates customized contract documents using AI, converts them into professionally formatted HTML, and sends them to an e-signature service for execution. The workflow pauses until signatures are completed, then records outcomes and notifies all parties accordingly. This template is designed to reduce legal and operational overhead while ensuring consistent, trackable, and scalable contract management. How it works Contract request intake Triggered by a webhook or external form. Validates required fields such as contract type and signatories. Generates a unique contract ID for tracking. Contract data preparation Normalizes contract metadata (dates, value, currency). Stores party and term information for downstream processing. Template routing Routes requests based on contract type (e.g., NDA, Service Agreement, Employment). Applies predefined base terms for each contract category. Falls back to a generic template if no specific type is matched. AI-powered contract generation An AI agent generates a complete contract in Markdown format. Suggests additional clauses and provides a brief risk assessment. Ensures a consistent contract structure across types. Document processing Converts Markdown into HTML for professional presentation. Prepares signer metadata, signing order, and deadlines. E-signature request Sends the document to an e-signature service (e.g., DocuSign, HelloSign). Emails all signatories with signing instructions. Uses a Wait node to pause execution until a signature webhook is received. Signature result handling Processes webhook callbacks for completed, pending, or expired signatures. Updates contract status accordingly. Completion & notifications Logs signed or expired contracts to Google Sheets. Sends confirmation, reminder, or expiration emails to all parties. Responds to the original webhook with a structured status message. Setup requirements Before activating this workflow, make sure to: Connect the contract request webhook to your intake form or system. Configure contract types and base terms as needed. Set up your e-signature provider webhook callback URL. Prepare Google Sheets for contract logging. Customize email me