by Yanagi Chinatsu
Who's it for? This template is perfect for teams, communities, or anyone who wants a fun, automated way to remember and celebrate birthdays. If you love space and want to make someone's special day a little more cosmic, this is for you. It's a great way to boost morale and ensure no one's birthday is forgotten. How it works / What it does The workflow runs automatically every morning. It reads a list of birthdays from your Google Sheet and checks if any match the current date. If a match is found, it fetches the latest Earth image from NASA's EPIC API and uses an AI model to generate a unique, space-themed birthday greeting. Finally, it sends a personalized HTML email to the birthday person and posts a celebratory message in your designated Slack channel. Requirements A Google Sheet with columns for Name, Email, and Birthday (in a format like YYYY-MM-DD). Credentials for Google Sheets, Gmail, OpenAI, and Slack configured in your n8n instance. How to set up Configure Credentials: Add your API credentials for Google (for both Sheets and Gmail), OpenAI, and Slack in the respective nodes. Set Up Google Sheet: In the "Get Birthday Roster" node, enter your Google Sheet ID and the name of the sheet where the birthday list is stored. Configure Slack: In the "Post Slack Notification" node, select the channel where you want birthday announcements to be posted. Activate Workflow: Save and activate the workflow. It will now run automatically every day! How to customize the workflow Change the schedule: Modify the CRON expression in the "Every Morning at 7:00" node to change when the workflow runs. Adjust the AI prompt: Edit the system message in the "Generate Space Birthday Message" node to alter the tone, length, or style of the AI-generated greetings. Customize the email design: Modify the HTML in the "Send Birthday Email" node to change the look and feel of the birthday message.
by Rahul Joshi
Description This workflow is designed to evaluate newly added CVs for Diversity, Equity, and Inclusion (DEI) eligibility. It automatically ingests CVs from Google Drive, extracts key fields, analyzes them with Azure OpenAI, logs structured DEI outcomes in Google Sheets, and sends a concise DEI-focused summary email to the hiring manager. The entire flow prioritizes consistent, auditable DEI checks and controlled logic paths. What This Template Does Watches Google Drive for new CV files to trigger DEI evaluation. Downloads and extracts text/structured fields from PDF CVs. Assesses DEI eligibility using Azure OpenAI, following defined criteria and prompts. Appends DEI results (eligible/not eligible, rationale, confidence) to Google Sheets for tracking. Generates and sends a DEI-focused summary email to the hiring manager for review. Key Benefits Standardized DEI screening to support equitable hiring decisions. Centralized, structured logging in Sheets for transparency and audits. Automated DEI summaries for faster, consistent manager review. Reliable routing with true/false logic to enforce DEI evaluation steps. Features Google Drive trigger (fileCreated) for CV intake tied to DEI checks. PDF extraction mapped to fields relevant for DEI evaluation. Azure OpenAI Chat Model prompts tuned for DEI criteria and rationale. Google Sheets append with eligibility status, notes, and timestamps. Email node that delivers DEI summaries and next-step guidance. Logic branching (true/false) to control DEI evaluation and notifications. Requirements n8n instance (cloud or self-hosted). Google Drive access to the CV intake folder. Google Sheets access for DEI results logging. Azure OpenAI access and configured prompts reflecting DEI criteria. Email node credentials to send DEI summaries to managers. Step-by-Step Setup Instructions Connect Google Drive and select the CV folder for the fileCreated trigger. Configure the Download CV and Extract From PDF nodes to capture fields needed for DEI checks. Add Azure OpenAI credentials and set DEI-specific prompts (criteria, rationale, confidence). Connect Google Sheets and select the target sheet; map columns for status, rationale, and timestamps. Configure the Email to Manager node with a DEI-focused subject and template. Test with sample CVs, verify sheet entries and email content, then enable the workflow. DEI-Focused Best Practices Clarify DEI criteria and document them in your prompt and sheet schema. Avoid including sensitive PII in emails; store only necessary fields for DEI decisions. Use n8n Credentials; never hardcode API keys or private data. Maintain an audit trail (timestamps, model version, prompt version, decision rationale). Periodically review prompts and sheet schema to align with policy updates.
by Jitesh Dugar
Automated Event Badge Generator Streamline your event registration process with this fully automated badge generation system. Perfect for conferences, seminars, corporate events, universities, and training programs. 🎯 What This Workflow Does Receives Registration Data via webhook (POST request) Validates & Sanitizes attendee information (email, name, role) Generates Unique QR Codes for each attendee with scannable IDs Creates Beautiful HTML Badges with gradient design and branding Converts to High-Quality PNG Images (400x680px) via HTMLCSStoImage API Logs Everything to Google Sheets for tracking and analytics Sends Personalized Emails with badge attachment and event instructions Handles Errors Gracefully with admin notifications ✨ Key Features Professional Badge Design**: Gradient purple background, attendee photos (initials), QR codes Automatic QR Code Generation**: Unique scannable codes for quick check-in Email Delivery**: Personalized HTML emails with download links Google Sheets Tracking**: Complete audit trail of all badge generations Error Handling**: Admin alerts when generation fails Scalable**: Process registrations one-by-one or in batches 🔧 Required Setup APIs & Credentials: HTMLCSStoImg API - Sign up at https://htmlcsstoimg.com Get API Key Gmail OAuth2 Connect your Gmail account Grant send permissions Google Sheets OAuth2 Create a tracking spreadsheet Add headers: Name, Email, Event, Role, Attendee ID, Badge URL, Timestamp Connect via OAuth2 Before Activation: Replace YOUR_GOOGLE_SHEETS_ID with your Google Sheet ID Replace admin@example.com with your admin email address Add all three credentials Test with sample data 📊 Use Cases Conferences & Seminars**: Generate badges for 100+ attendees Universities**: Student ID cards and event passes Corporate Events**: Employee badges with QR check-in Training Programs**: Course participant badges Workshops**: Professional badges with role identification Trade Shows**: Exhibitor and visitor badges 🎨 Customization Options Badge Design**: Modify HTML/CSS for custom branding, colors, logos QR Code Size**: Adjust dimensions for different use cases Email Template**: Personalize welcome message and instructions Role-Based Badges**: Different designs for VIP, Speaker, Staff, Attendee Multi-Event Support**: Handle multiple events with different templates 📈 What You'll Track Total badges generated Attendee names, emails, roles Badge image URLs for reprints Generation timestamps Event names and dates ⚡ Processing Time Average**: 5-8 seconds per badge Includes**: Validation, QR generation, HTML rendering, image conversion, logging, email 🔒 Security Features Email format validation Continue-on-fail error handling Admin notifications on failures Secure credential storage 💡 Pro Tips Use a dedicated Gmail account for automation Monitor HTMLCSStoImg API limits Create separate sheets for different events Archive old data periodically Set up webhook authentication for production 🚀 Getting Started Import this workflow Add the three required credentials Update Sheet ID and admin email Test with sample registration data Activate and integrate with your registration form Perfect for event organizers, HR teams, universities, and anyone managing events with 10-1000+ attendees!
by Tsubasa Shukuwa
How it works This workflow automatically detects new image files uploaded to a Google Drive folder, extracts Japanese text using OCR, summarizes it with AI, and records the result in Google Sheets. Finally, it sends a completion email notification with the file name and summary. Workflow steps: Google Drive New File Trigger – Watches a specific Google Drive folder for new image uploads. Download Image File – Downloads the newly uploaded image for processing. Extract Text with OCR.space – Sends the image to the OCR.space API to extract text (Japanese supported). Format OCR Result & Check for Empty – Cleans and validates the extracted text. Generate Summary with OpenRouter AI – Uses an AI model to generate a short summary of the text. OpenRouter Chat Model – Connects the AI Agent to the OpenRouter language model. Append row in sheet – Adds the file name, AI summary, and processing date to Google Sheets. Send Completion Notification via Gmail – Sends an email with the summarized content and Google Sheets link. Process Completed – Marks the workflow’s successful end. Setup steps Connect your Google Drive, Google Sheets, and Gmail accounts through credentials. Set your OCR.space API key in the HTTP Request node. Add your OpenRouter API key credential for the AI node. Replace the Google Sheet ID and folder ID with your own. Customize the Gmail recipient and email message as needed. Adjust the polling frequency (e.g., every 1 minute) depending on your workflow needs. Ideal for Digitizing and summarizing handwritten or printed book pages. Automatically extracting and archiving text from scanned reports or notes. Businesses or educators automating document reading and summarization tasks. ⚙️ Note: Each node includes a clear English Sticky Note above it for easier understanding and documentation.
by Limbraj More
Automate admin tasks for manufacturing companies by processing emails, extracting key data from invoices & purchase orders, and delivering instant alerts via Gmail and Telegram. 📝 Description This workflow automatically: Fetches incoming emails from Gmail Classifies emails (invoices, purchase orders, payment follow-up, etc.) using AI Sends tailored auto-replies based on content and attachment presence Extracts structured data from attached invoices/POs (PDFs etc.) Delivers alerts and document files to your team via Telegram Logs or routes data for further use in accounting or internal systems ⚙️ Pre-Conditions & Requirements Before using this workflow, you need: Gmail Account with API access (for OAuth2 authentication) Telegram Bot API Token (create a Telegram bot and get your API key) Optional: API credentials for Google Sheets or other data sinks if you want to log extracted data OpenRouter API credentials (for LLM-powered nodes, if used) Access to an n8n instance (cloud or self-hosted) 🛠 Setup Instructions Import the Workflow: Download the JSON file and import it into your n8n instance. Connect Accounts: Configure the Gmail Trigger node with your Gmail OAuth2 credentials Set up the Telegram node with your bot API token Set Required Variables: Adjust AI instructions or prompt text if needed (for your company’s tone/templates) Customize labels, keywords, or filters in code nodes for your use case Set target Telegram chat/group IDs Test the Workflow: Send a sample email with attachments to your Gmail account Confirm that emails are classified, replies are sent, and Telegram notifications/mobile alerts are delivered as expected Review and Connect Optional Modules: For logging or archiving extracted data, connect additional “Google Sheets” or “Webhook” nodes as needed 🧩 Customization Tips Modify Email Categories: Update AI prompt instructions or filters to add/change labels (“Vendor Query,” “Partial Payment,” etc.) Attachment Handling: Edit the code node logic to detect and process additional file types (DWG, XLSX, ZIP, etc.) Notification Logic: Change the Telegram destination or add Slack/Microsoft Teams for broader team alerts Data Logging: Add nodes for CRM, inventory, or ERP integration (push to your accounting or workflow management tool) Example AI Prompt (for categorization) text You are the personal emailing assistant for Zenith Engineering, a manufacturing company... Your tasks: Categorize each email by priority Draft polite, professional replies... Identify and label attachments such as invoices, POs, drawings Response should be a valid JSON object: {"Label":"Important", "Response":"..."} If you have any doubts and questions let me know : smonu2303@gmail.com from Pune. Linkedin: https://www.linkedin.com/in/raj-more-171560bb/
by Jitesh Dugar
Customer Testimonial Collector Workflow Transform scattered testimonials into organized marketing assets - achieving 500 percent increase in testimonial collection, instant multi-channel optimization, and turning happy customers into brand advocates with automated rewards and recognition. What This Workflow Does Revolutionizes testimonial management with AI-powered analysis and multi-channel optimization: Centralized Collection via Jotform with structured fields for consistency AI Tone Detection using GPT-4 to analyze sentiment, authenticity, and emotional impact with 0-100 scoring Smart Quote Extraction that automatically identifies best soundbites for different marketing channels Organized Library using Google Sheets database with searchable tags, ratings, and usage permissions Automated Thank-You emails with exclusive coupon codes (20 percent for 5-star reviews) Social Media Optimization where AI creates Twitter, LinkedIn, and website versions automatically Marketing Team Alerts with real-time notifications including priority levels and usage recommendations Smart Rewards using dynamic discount codes based on rating quality Use Case Matching where AI identifies which marketing channels and audiences fit each testimonial Marketing-Ready Assets including headlines, callout words, and visual suggestions Key Features AI Testimonial Analyst: GPT-4 evaluates testimonials across 20 plus dimensions including tone, authenticity, emotional impact, and competitive advantages revealed Multi-Channel Optimization: Automatically generates Twitter-ready (280 characters), LinkedIn professional (150 words), and website polished (50-75 words) versions Tone and Sentiment Detection: Classifies testimonials as Enthusiastic, Professional, Grateful, Impressed, Transformative, or Skeptical-to-Believer with 0-100 sentiment scores Best Quote Extraction: AI identifies the single most impactful sentence plus 2-3 alternate quotes for different contexts Authenticity Scoring: Filters generic testimonials by rating authenticity as very-authentic, authentic, or generic Key Benefits Identification: Automatically extracts specific benefits mentioned such as time savings, cost reduction, and quality improvement Pain Points Mapping: Identifies what problems the customer solved by using your product or service Specific Results Tracking: Captures measurable outcomes like revenue increase, efficiency gains, and customer satisfaction improvements Marketing Priority Levels: AI assigns high, medium, or low priority to help marketing teams focus on most impactful testimonials Target Audience Matching: Identifies which customer segments would most relate to each testimonial Buyer Journey Staging: Tags testimonials by awareness, consideration, or decision stage for funnel optimization Competitive Differentiation: Identifies what each testimonial reveals about your competitive advantages Visual Design Suggestions: AI recommends graphic styles and callout words for testimonial graphics Permission Tracking: Automatically logs customer consent for public use across different channels Smart Coupon Generation: Creates unique codes with expiration dates and rating-based discount tiers Referral Incentives: Thank-you emails include referral program details to drive word-of-mouth Perfect For SaaS Companies needing social proof for landing pages and product pages E-commerce Stores showcasing customer satisfaction and product quality B2B Service Providers including consulting, agencies, and professional services building credibility Course Creators and online educators leveraging student success stories Healthcare Practices with patient testimonials (HIPAA-compliant with proper permissions) Real Estate Agents collecting client feedback for marketing materials Restaurants and Hospitality businesses gathering guest reviews and experiences Fitness and Wellness brands showcasing transformation stories What You Will Need Required Integrations Jotform - Testimonial submission form (free tier works) OpenAI API - GPT-4 for AI testimonial analysis (approximately 20-40 cents per testimonial) Gmail - Automated thank-you emails and marketing team notifications Google Sheets - Testimonial library and searchable database Optional Integrations Social Media APIs to auto-post testimonials to Twitter, LinkedIn, Facebook CRM Integration to link testimonials to customer profiles in HubSpot or Salesforce WordPress or Website integration to auto-publish approved testimonials to website testimonial pages Quick Start Import Template - Copy JSON and import into n8n Add OpenAI Credentials - Set up OpenAI API key (GPT-4 recommended for best analysis) Create Jotform Testimonial Form with fields for Customer Name, Email, Company, Job Title, Product Used, Testimonial Text, Rating, Permission to Share, Photo Upload, and Use Case Configure Gmail - Add Gmail OAuth2 credentials (same for both Gmail nodes) Setup Google Sheets - Create spreadsheet with Testimonial Library sheet and replace sheet ID in workflow Customize Coupon Logic if needed by editing the Generate Coupon Code node Brand Email Templates by updating company name, logo URLs, and colors Set Marketing Team Email address in notification node Test Workflow by submitting test testimonial through Jotform Launch Campaign by sharing form link in post-purchase emails Customization Options Multi-Language Support by translating forms and AI prompts for international customers Video Testimonials by adding video upload field and storing URLs in sheets Anonymous Options to allow customers to submit testimonials without public attribution Approval Workflow by adding manager approval step before testimonials go live A/B Testing to tag testimonials for split testing different versions on landing pages Industry-Specific Fields customized for your vertical such as results achieved, ROI, time saved Automated Publishing to connect to WordPress or CMS to auto-publish approved testimonials Social Media Auto-Posting to schedule tweets and LinkedIn posts with testimonial content Reward Tiers to create VIP rewards for customers who refer others after submitting testimonials NPS Integration to combine with Net Promoter Score surveys Review Platform Sync to auto-request reviews on Google, Yelp, Trustpilot, G2, Capterra Case Study Pipeline to flag high-impact testimonials for full case study development Customer Success Alerts to notify CSMs when their customers submit testimonials Testimonial Rotation to auto-rotate testimonials on website based on visitor industry Sentiment Trending to track sentiment scores over time Expected Results 500 percent increase in testimonial submissions due to easy form and rewards 90 percent reduction in manual testimonial management through automated categorization 10 hours per month saved as marketing team instantly finds perfect testimonials 40 percent improvement in conversion rates from authentic testimonials on landing pages 85 percent customer satisfaction with reward process driving loyalty 60 percent of testimonials rated high priority by AI filtering 100 percent organized testimonial library ensuring no great testimonial is lost 3x increase in referrals from thank-you emails with incentives 75 percent reduction in testimonial editing time as AI creates ready-to-use content 50 percent more social media engagement from optimized testimonial posts Use Cases SaaS Company Example A marketing manager with 150 customers needs social proof for new landing page launching next week. Scattered testimonials exist in emails, support tickets, and social media messages with no time to organize them. Solution: Sends form link to 50 happiest customers and receives 35 testimonials within 48 hours. AI analyzes all submissions and extracts best quotes. Manager filters by high priority and landing page use case to find 8 perfect testimonials with website versions already optimized. Result: Landing page launches on time with authentic testimonials. Conversion rate increases 42 percent. Customer uses discount code to upgrade plan. Refers 2 colleagues who become customers. Total impact exceeds 1400 dollars in incremental revenue. E-commerce Fashion Brand Example Post-purchase emails have generic review links. Most customers ignore them. Social proof on product pages is weak with only 2-3 old reviews while competitors have hundreds of testimonials. Solution: Adds form link to order confirmation emails 7 days post-delivery with incentive messaging. 500 customers submit testimonials in first month (10 percent response rate). AI identifies best testimonials for each product category. Result: Product pages updated with enthusiastic testimonials. Add-to-cart rate increases 65 percent. Customer uses discount code for repeat purchase. Posts social media content that brand reposts to followers. One testimonial workflow generates over 3500 dollars in attributed revenue. B2B Consulting Firm Example Proposals need client testimonials but they are trapped in old email threads. Asking clients feels awkward and time-consuming with no systematic collection process. Solution: Sends form link at project completion milestones via personal email from account manager. 22 of 30 clients submit testimonials (73 percent response rate). AI extracts ROI stories and specific results. Result: Testimonial added to proposal template addressing exact objection about being better than current firm. Close rate on proposals increases 30 percent. Client refers colleague who becomes high-value client. Full case study developed generates inbound leads. One testimonial workflow generates over 80000 dollars in new business. Online Course Creator Example Students post success stories in Facebook group and via email with no organized collection system. Website has only 3 old testimonials from 2 years ago. Low enrollment due to lack of social proof. Solution: Adds form link to course completion emails and shares in Facebook group with incentive. 180 students submit testimonials in first month (9 percent of students). AI identifies transformation stories and specific skills gained. Result: Testimonial added to course landing page as featured transformation story. Enrollment rate increases 55 percent as specific details address will-this-work objection. Student enrolls in advanced course using discount code. Testimonial shared in ads generates high ROAS. Workflow drives over 15000 dollars in additional course revenue. Healthcare Practice Example Patients verbally express gratitude but practice has only 15 online reviews. Need more social proof for website to attract new patients. Asking patients in-person feels pushy. Solution: Sends form link in post-appointment follow-up emails with clear HIPAA disclosure. Permission checkboxes for sharing testimonial publicly and using name and photo. 75 patients submit testimonials in first month. AI identifies compassionate care themes and specific improvements. Result: Testimonial added to service page. Inquiry rate increases 40 percent as testimonial addresses surgery fear objection. Patient agrees to video testimonial which becomes centerpiece of landing page. Multiple new patients mention seeing testimonial during consultations. One testimonial workflow generates multiple new patients and significant revenue. Practice review rating improves substantially. Pro Tips Timing is Everything: Send form 7-10 days after purchase or project completion when customers are still excited Incentivize Generously: 15-20 percent discount codes dramatically increase submission rates Make It Easy: Pre-fill customer information when possible and keep form under 10 fields Photo Requests Work: 60 percent of customers will upload headshots if you explain it increases credibility Video Follow-Ups: After receiving strong text testimonial, reach out personally to request video version Permission Clarity: Be explicit about where and how testimonials will be used Response Templates: Create templates for personal follow-ups to high-priority testimonials Quarterly Campaigns: Run testimonial collection campaigns quarterly with bonus rewards Showcase Submissions: Feature new testimonials in monthly newsletter A/B Test Formats: Test different testimonial layouts on website Industry Segmentation: Filter testimonials by industry for targeted landing pages NPS Integration: Send testimonial forms only to Promoters for higher quality submissions Social Proof Everywhere: Use testimonial snippets in email signatures and proposal templates Update Regularly: Refresh website testimonials quarterly to maintain relevance Track Attribution: Tag testimonials with UTM parameters when shared on social media Learning Resources This workflow demonstrates advanced automation including AI Agents for Content Optimization, Dynamic Reward Logic, Marketing Asset Generation, Sentiment Analysis, Data Organization, Multi-Channel Optimization, Customer Journey Mapping, Competitive Intelligence, Workflow Efficiency, and Permission Management. Business Impact Metrics Track these key metrics to measure success: Testimonial Collection Rate: Monitor percentage of customers who submit testimonials (target 10-15 percent) Submission Quality Score: Monitor average AI authenticity and sentiment scores (target 80 plus out of 100) Marketing Team Efficiency: Measure time saved finding and formatting testimonials (expect 10 plus hours per month saved) Conversion Rate Impact: A/B test pages with and without optimized testimonials (expect 30-50 percent lift) Reward Redemption Rate: Track percentage of customers who use thank-you coupon codes (typical 40-60 percent) Referral Generation: Count referrals attributed to testimonial thank-you emails (expect 3-5 percent referral rate) Social Media Engagement: Monitor engagement on testimonial posts versus other content (expect 2-3x higher) High-Priority Testimonial Ratio: Track percentage of testimonials rated high priority by AI (target 50-70 percent) Time to Marketing Use: Measure days from submission to live testimonial on website (aim for under 1 day) Customer Satisfaction: Survey customers about testimonial submission experience (target 90 percent plus positive) Template Compatibility Compatible with n8n version 1.0 and above Works with n8n Cloud and Self-Hosted No coding required for basic setup Fully customizable for industry-specific needs Ready to turn customers into brand advocates? Import this template and transform scattered testimonials into organized marketing assets with AI-powered analysis and automation!
by Khairul Muhtadin
Promo Seeker automatically finds, verifies, and delivers active promo codes to users via Telegram or email using SerpAPI + Gemini (OpenRouter). Saves hours of manual searching and deduplicates results into an n8n Data Table for fast reuse. Why Use This Workflow? Time Savings: Reduces manual promo hunting from 2 hours to 5 minutes per query. Cost Reduction: Cuts reliance on paid scraping tools or manual services — potential savings of $50–$200/month. Error Prevention: Cross-references sources and enforces a 30‑day recency filter to reduce expired-code hits by ~60% vs single-source checks. Scalability: Handles hundreds of queries per day with Data Table upserts and optional scheduling for continuous discovery. Ideal For Marketing / Growth Managers:** Quickly discover competitor or partner discounts to promote in campaigns. Customer Support / Operations:** Respond to user requests with verified promo codes via Telegram or email. Affiliate / Content Teams:** Aggregate and maintain a clean promo feed for newsletters or site widgets. How It Works Trigger: Incoming request via Webhook, Telegram message, Google Form submission, or scheduled run. Data Collection: The LangChain agent uses SerpAPI search results and Gemini (OpenRouter) to locate recent promo codes. Processing: Filter for recency (last 30 days), extract code, value, terms, and expiry. Intelligence Layer: Gemini 2.5 Pro (OpenRouter) + LangChain agent structure and verify results, outputting a standardized JSON. Output & Delivery: If a code exists in the Data Table, notify the requester via Telegram and Gmail; otherwise, return results and upsert them into the Data Table. Storage & Logging: Results stored/upserted in an n8n Data Table to prevent duplicates and enable fast lookups. Setup Guide Prerequisites | Requirement | Type | Purpose | |-------------|------|---------| | n8n instance | Essential | Execute the workflow — import JSON to your n8n instance | | SerpAPI account | Essential | Web search results for promo code discovery | | OpenRouter (Gemini) account | Essential | Language model (Gemini 2.5 Pro) for extraction and verification | | Telegram Bot (BotFather) | Essential | Receive queries and send promo notifications | | Gmail OAuth2 | Essential | Send rich email notifications | | n8n Data Tables | Essential | Store and deduplicate promo code records | Get your n8n instance here: n8n instance — import the JSON and begin configuration. (Repeat link for convenience) n8n instance Installation Steps Import the JSON workflow into your n8n instance. Configure credentials (use n8n's Credentials UI — do NOT paste keys into nodes): SerpAPI: paste your SerpAPI API Key from your SerpAPI dashboard. OpenRouter API: paste your OpenRouter API Key (for Gemini 2.5 Pro). Telegram API: create bot via @BotFather, then add Bot Token to Telegram credentials. Gmail OAuth2: use n8n's Gmail OAuth2 credential flow and authorize the account. Update environment-specific values: Webhook path: /v1/promo-seeker (configured in the Webhook node) or replace with your preferred path. Data Table ID: point to your own Data Table Form/webhook recipient fields (email/chatId mappings). Customize settings: Adjust the LangChain agent prompt (Promo Seeker Agent) for different recency windows or regional focus. Change max results/limit on the Data Table node (default limit = 3). Test execution: Trigger via Telegram or a POST to the webhook with sample payload: { "platform":"example.com", "email":"you@domain.com" } Confirm notifications arrive and Data Table rows are upserted. Technical Details Core Nodes | Node | Purpose | Key Configuration | |------|---------|-------------------| | SerpAPI | Fetch web search results | Provide credential; adjust search params in agent prompt | | Gemini 2.5Pro (OpenRouter) | Extract & verify promo details | Use OpenRouter credential; model google/gemini-2.5-pro | | Promo Seeker Agent (LangChain) | Orchestrates search + parsing | System prompt enforces 30‑day recency & result format | | Structured Output Parser | Validates agent output | JSON schema example for platform/code/value/terms/validUntil | | Data Table (Get row(s)) | Lookup existing promos | Filters by platform; limit = 3 | | If (Code Exist?) | Branching logic | Checks existence of platform field | | Data Table (Upsert row(s)) | Insert or update promo | Mapping from agent output to Data Table columns | | Telegram Trigger / Telegram | Receive queries & notify users | Webhook-based trigger; parse_mode = HTML for messages | | Gmail | Send rich HTML emails | Uses Gmail OAuth2 credential | | Webhook / Form Trigger | Alternate inputs | Webhook path /v1/promo-seeker and Form trigger for manual submissions | Workflow Logic On trigger, the Platform Set node normalizes the incoming query and receiver. Get row(s) checks Data Table for existing promos. If found: notify via Telegram and send Gmail (email template included). If not found: the Promo Seeker Agent runs SerpAPI searches, parses structured output, then Upsert row(s) saves results and notifications are sent. Structured Output Parser enforces correct JSON to avoid bad upserts. Customization Options Basic Adjustments Recency window: change the agent prompt to 7/14/30 days. Result limit: increase Data Table Get limit or change Upsert batch size. Advanced Enhancements Add Slack or Microsoft Teams notifications (moderate complexity). Add caching layer (Redis) to reduce repeated SerpAPI calls (advanced). Parallelize searches across multiple search engines (higher API usage & complexity). Performance & Optimization | Metric | Expected Performance | Optimization Tips | |--------|----------------------|-------------------| | Execution time | 8–30s per new search (depends on SerpAPI + LM response) | Reduce SerpAPI page depth; cache recent results | | API calls | 3–10 SerpAPI calls per complex query | Batch queries; use higher-quality search params | | Error handling | Agent retries on malformed output | Use retry nodes and set onError strategy for downstream nodes | Troubleshooting | Problem | Cause | Solution | |---------|-------|----------| | No results returned | Query too vague or rate-limited API | Improve query specificity; check SerpAPI quota | | Gmail send fails | OAuth scope not granted or token expired | Reconnect Gmail OAuth2 credential in n8n | | Telegram webhook not firing | Incorrect bot token or webhook setup | Recreate Telegram credential and check bot permissions | | Duplicate rows | Upsert mapping mismatch | Ensure promoCode mapping in Upsert matches structured output | | Agent returns malformed JSON | LM prompt too permissive | Tighten the agent system prompt and validate with Structured Output Parser | Created by: khaisa Studio Category: Marketing Automation Tags: promo-codes, coupons, serpapi, telegram, gmail, openrouter, data-tables Need custom workflows or help adapting this template? Contact us
by Julian Kaiser
n8n Forum Job Aggregator - AI-Powered Email Digest Overview Automate your n8n community job board monitoring with this intelligent workflow that scrapes, analyzes, and delivers opportunities straight to your inbox. Perfect for freelancers, agencies, and developers looking to stay on top of n8n automation projects without manual checking. How It Works Scrapes the n8n community job board to find new postings from the last 7 days Extracts key metadata including job titles, descriptions, posting dates, and client details Analyzes each listing using OpenRouter AI to generate concise summaries of project requirements and client needs Delivers a professionally formatted email digest with all opportunities organized and ready for review Prerequisites OpenRouter API Key**: Sign up at OpenRouter.ai to access AI summarization capabilities SMTP Email Account**: Gmail, Outlook, or any SMTP-compatible email service Setup Steps Time estimate: 5-10 minutes Configure OpenRouter Credentials Add your OpenRouter API key in n8n credentials manager Recommended model: GPT-3.5-turbo or Claude for cost-effective summaries Set Up SMTP Email Configure sender email address Add recipient email(s) for digest delivery Test connection to ensure delivery Customize Date Range (Optional) Default: Last 7 days of job postings Adjust the date filter node to match your preferred frequency Test & Refine Run a test execution Review email formatting and AI summary quality Customize HTML template styling to match your preferences Customization Options Scheduling**: Set up cron triggers (daily, weekly, or custom intervals) Filtering**: Add keyword filters for specific technologies or project types AI Prompts**: Modify the summarization prompt to extract different insights Email Design**: Customize HTML/CSS styling in the email template node Example Use Cases Freelance Developers**: Never miss relevant n8n automation opportunities Agencies**: Monitor market demand and competitor activity Job Seekers**: Track n8n-related positions and consulting gigs Market Research**: Analyze trends in automation project requests Example Output Each email digest includes: Job title and posting date AI-generated summary (e.g., "Client needs workflow automation for Shopify order processing with Slack notifications") Direct link to original posting Organized by recency
by Jordan Hoyle
🤖 AI-Powered Job Matcher & Resume Customizer Description This advanced workflow automates the entire job search and preparation process, moving beyond simple notifications to provide AI-driven career intelligence. It connects to LinkedIn to scrape fresh job postings, filters against jobs you've already seen, and then uses powerful LLMs (Mistral Large/Small) to perform a detailed resume-to-job match, generate tailored cover letters, and provide concrete resume improvement suggestions. All data is logged into a Google Sheet for comprehensive tracking, and a clean, single Daily Digest Email summarizes the top 5 matches found each day. ✨ Key Features Automated Scheduling:** Runs daily to find new job postings. Multi-Keyword Search:** Uses your main job title and three alternate titles generated by an AI Agent for maximum search coverage. LinkedIn Web Scraping:** Pulls new job URLs, details, location, and salary data from LinkedIn Search results. Duplicate Prevention:* Uses the *Compare Datasets** node to ensure only new, unseen jobs are processed against your master Google Sheet. Intelligent Matching (LLM):** The workflow performs a detailed job-to-resume comparison, generating: A Match Score (0-100) with evidence for alignment in skills, experience, and domain. A Tailored Cover Letter specific to the job title and company. Actionable Resume Improvement points (e.g., [ADD], [QUANTIFY]) to optimize your resume for the specific role. Centralized Tracking:* Saves all job data, match scores, cover letters, and resume suggestions to a *Google Sheet**. Professional Daily Digest:* Sends a single, clean *HTML email** summarizing the top 5 highest-scoring job matches for easy review. 🛠️ Prerequisites n8n Credentials: Google Drive: To download your resume (PDF/DOCX file URL). Google Sheets: To connect to your job tracking sheet. Gmail: To send the daily digest email. Mistral Cloud: For the LLM processing (Resume Breakdown, Job Matching, and Resume Analysis). External Files: A Job Tracking Google Sheet (used as a master database). Your current Resume file (PDF recommended, hosted on Google Drive). Setup Notes: Update the file links (Download Resume node) and Google Sheet details (Get row(s)/Append nodes). Set your personal email address in the Send Digest Email node. Review the LLM prompts to tailor the AI agent's persona and output fields to your exact needs.
by Cheng Siong Chin
Introduction Automate peer review assignment and grading with AI-powered evaluation. Designed for educators managing collaborative assessments efficiently. How It Works Webhook receives assignments, distributes them, AI generates review rubrics, emails reviewers, collects responses, calculates scores, stores results, emails reports, updates dashboards, and posts analytics to Slack. Workflow Template Webhook → Store Assignment → Distribute → Generate Review Rubric → Notify Slack → Email Reviewers → Prepare Response → Calculate Score → Store Results → Check Status → Generate Report → Email Report → Update Dashboard → Analytics → Post to Slack → Respond to Webhook Workflow Steps Receive & Store: Webhook captures assignments, stores data. Distribute & Generate: Assigns peer reviewers, AI creates rubrics. Notify & Email: Alerts via Slack, sends review requests. Collect & Score: Gathers responses, calculates peer scores. Report & Update: Generates reports, emails results, updates dashboard. Analyze & Alert: Posts analytics to Slack, confirms completion. Setup Instructions Webhook & Storage: Configure endpoint, set up database. AI Configuration: Add OpenAI key, customize rubric prompts. Communication: Connect Gmail, Slack credentials. Dashboard: Link analytics platform, configure metrics. Prerequisites OpenAI API key Gmail account Slack workspace Database or storage system Dashboard tool Use Cases University peer review assignments Corporate training evaluations Research paper assessments Customization Multi-round review cycles Custom scoring algorithms Benefits Eliminates manual distribution Ensures consistent evaluation
by explorium
Outbound Agent - AI-Powered Lead Generation with Natural Language Prospecting This n8n workflow transforms natural language queries into targeted B2B prospecting campaigns by combining Explorium's data intelligence with AI-powered research and personalized email generation. Simply describe your ideal customer profile in plain English, and the workflow automatically finds prospects, enriches their data, researches them, and creates personalized email drafts. DEMO Template Demo Credentials Required To use this workflow, set up the following credentials in your n8n environment: Anthropic API Type:** API Key Used for:** AI Agent query interpretation, email research, and email writing Get your API key at Anthropic Console Explorium API Type:** Generic Header Auth Header:** Authorization Value:** Bearer YOUR_API_KEY Used for:** Prospect matching, contact enrichment, professional profiles, and MCP research Get your API key at Explorium Dashboard Explorium MCP Type:** HTTP Header Auth Used for:** Real-time company and prospect intelligence research Connect to: https://mcp.explorium.ai/mcp Gmail Type:** OAuth2 Used for:** Creating email drafts Alternative options: Outlook, Mailchimp, SendGrid, Lemlist Go to Settings → Credentials, create these credentials, and assign them in the respective nodes before running the workflow. Workflow Overview Node 1: When chat message received This node creates an interactive chat interface where users can describe their prospecting criteria in natural language. Type:** Chat Trigger Purpose:** Accept natural language queries like "Get 5 marketing leaders at fintech startups who joined in the past year and have valid contact information" Example Prompts:** "Find SaaS executives in New York with 50-200 employees" "Get marketing directors at healthcare companies" "Show me VPs at fintech startups with recent funding" Node 2: Chat or Refinement This code node manages the conversation flow, handling both initial user queries and validation error feedback. Function:** Routes either the original chat input or validation error messages to the AI Agent Dynamic Input:** Combines chatInput and errorInput fields Purpose:** Creates a feedback loop for validation error correction Node 3: AI Agent The core intelligence node that interprets natural language and generates structured API calls. Functionality: Interprets user intent from natural language queries Maps concepts to Explorium API filters (job levels, departments, company size, revenue, location, etc.) Generates valid JSON requests with precise filter criteria Handles off-topic queries with helpful guidance Connected to MCP Client for real-time filter specifications AI Components: Anthropic Chat Model:** Claude Sonnet 4 for query interpretation Simple Memory:** Maintains conversation context (100 message window) Output Parser:** Structured JSON output with schema validation MCP Client:** Connected to https://mcp.explorium.ai/mcp for Explorium specifications System Instructions: Expert in converting natural language to Explorium API filters Can revise previous responses based on validation errors Strict adherence to allowed filter values and formats Default settings: mode: "full", size: 10000, page_size: 100, has_email: true Node 4: API Call Validation This code node validates the AI-generated API request against Explorium's filter specifications. Validation Checks: Filter key validity (only allowed filters from approved list) Value format correctness (enums, ranges, country codes) No duplicate values in arrays Proper range structure for experience fields (total_experience_months, current_role_months) Required field presence Allowed Filters: country_code, region_country_code, company_country_code, company_region_country_code company_size, company_revenue, company_age, number_of_locations google_category, naics_category, linkedin_category, company_name city_region_country, website_keywords has_email, has_phone_number job_level, job_department, job_title business_id, total_experience_months, current_role_months Output: isValid: Boolean validation status validationErrors: Array of specific error messages Node 5: Is API Call Valid? Conditional routing node that determines the next step based on validation results. If Valid:** Proceed to Explorium API: Fetch Prospects If Invalid:** Route to Validation Prompter for correction Node 6: Validation Prompter Generates detailed error feedback for the AI Agent when validation fails. This creates a self-correcting loop where the AI learns from validation errors and regenerates compliant requests by routing back to Node 2 (Chat or Refinement). Node 7: Explorium API: Fetch Prospects Makes the validated API call to Explorium's prospect database. Method:** POST Endpoint:** /v1/prospects/fetch Authentication:** Header Auth (Bearer token) Input:** JSON with filters, mode, size, page_size, page Returns:** Array of matched prospects with prospect IDs based on filter criteria Node 8: Pull Prospect IDs Extracts prospect IDs from the fetch response for bulk enrichment. Input:** Full fetch response with prospect data Output:** Array of prospect_id values formatted for enrichment API Node 9: Explorium API: Contact Enrichment Single enrichment node that enhances prospect data with both contact and profile information. Method:** POST Endpoint:** /v1/prospects/enrich Enrichment Types:** contacts, profiles Authentication:** Header Auth (Bearer token) Input:** Array of prospect IDs from Node 8 Returns: Contacts:** Professional emails (current, verified), phone numbers (mobile, work), email validation status, all available email addresses Profiles:** Full professional history, current role details, company information, skills and expertise, education background, experience timeline, job titles and seniority levels Node 10: Clean Output Data Transforms and structures the enriched data for downstream processing. Node 11: Loop Over Items Iterates through each prospect to generate individualized research and emails. Batch Size:** 1 (processes prospects one at a time) Purpose:** Enable personalized research and email generation for each prospect Loop Control:** Processes until all prospects are complete Node 12: Research Email AI-powered research agent that investigates each prospect using Explorium MCP. Input Data: Prospect name, job title, company name, company website LinkedIn URL, job department, skills Research Focus: Company automation tool usage (n8n, Zapier, Make, HubSpot, Salesforce) Data enrichment practices Tech stack and infrastructure (Snowflake, Segment, etc.) Recent company activity and initiatives Pain points related to B2B data (outdated CRM data, manual enrichment, static workflows) Public content (speaking engagements, blog posts, thought leadership) AI Components: Anthropic Chat Model1:** Claude Sonnet 4 for research Simple Memory1:** Maintains research context Explorium MCP1:** Connected to https://mcp.explorium.ai/mcp for real-time intelligence Output: Structured JSON with research findings including automation tools, pain points, personalization notes Node 13: Email Writer Generates personalized cold email drafts based on research findings. Input Data: Contact info from Loop Over Items Current experience and skills Research findings from Research Email agent Company data (name, website) AI Components: Anthropic Chat Model3:** Claude Sonnet 4 for email writing Structured Output Parser:** Enforces JSON schema with email, subject, message fields Output Schema: email: Selected prospect email address (professional preferred) subject: Compelling, personalized subject line message: HTML formatted email body Node 14: Create a draft (Gmail) Creates email drafts in Gmail for review before sending. Resource:** Draft Subject:** From Email Writer output Message:** HTML formatted email body Send To:** Selected prospect email address Authentication:** Gmail OAuth2 After Creation: Loops back to Node 11 (Loop Over Items) to process next prospect Alternative Output Options: Outlook:** Create drafts in Microsoft Outlook Mailchimp:** Add to email campaign SendGrid:** Queue for sending Lemlist:** Add to cold email sequence Workflow Flow Summary Input: User describes target prospects in natural language via chat interface Interpret: AI Agent converts query to structured Explorium API filters using MCP Validate: API call validation ensures filter compliance Refine: If invalid, error feedback loop helps AI correct the request Fetch: Retrieve matching prospect IDs from Explorium database Enrich: Parallel bulk enrichment of contact details and professional profiles Clean: Transform and structure enriched data Loop: Process each prospect individually Research: AI agent uses Explorium MCP to gather company and prospect intelligence Write: Generate personalized email based on research Draft: Create reviewable email drafts in preferred platform This workflow eliminates manual prospecting work by combining natural language processing, intelligent data enrichment, automated research, and personalized email generation—taking you from "I need marketing leaders at fintech companies" to personalized, research-backed email drafts in minutes. Customization Options Flexible Triggers The chat interface can be replaced with: Scheduled runs for recurring prospecting Webhook triggers from CRM updates Manual execution for ad-hoc campaigns Scalable Enrichment Adjust enrichment depth by: Adding more Explorium API endpoints (technographics, funding, news) Configuring prospect batch sizes Customizing data cleaning logic Output Destinations Route emails to your preferred platform: Email Platforms:** Gmail, Outlook, SendGrid, Mailchimp Sales Tools:** Lemlist, Outreach, SalesLoft CRM Integration:** Salesforce, HubSpot (create leads with research) Collaboration:** Slack notifications, Google Docs reports AI Model Flexibility Swap AI providers based on your needs: Default: Anthropic Claude (Sonnet 4) Alternatives: OpenAI GPT-4, Google Gemini Setup Notes Domain Filtering: The workflow prioritizes professional emails—customize email selection logic in the Clean Output Data node MCP Configuration: Explorium MCP requires Header Auth setup—ensure credentials are properly configured Rate Limits: Adjust Loop Over Items batch size if hitting API rate limits Memory Context: Simple Memory maintains conversation history—increase window length for longer sessions Validation: The AI self-corrects through validation loops—monitor early runs to ensure filter accuracy This workflow represents a complete AI-powered sales development representative (SDR) that handles prospecting, research, and personalized outreach with minimal human intervention.
by Jameson Kanakulya
Overview This automated workflow intelligently qualifies interior design leads, generates personalized client emails, and manages follow-up through a human-approval process. Built with n8n, Claude AI, Telegram approval, and Notion database integration. ⚠️ Hosting Options This template works with both n8n Cloud and self-hosted instances. Most nodes are native to n8n, making it cloud-compatible out of the box. What This Template Does Automated Lead Management Pipeline: Captures client intake form submissions from website or n8n forms AI-powered classification into HOT/WARM/COLD categories based on budget, project scope, and commitment indicators Generates personalized outreach emails tailored to each lead type Human approval workflow via Telegram for quality control Email revision capability for rejected drafts Automated client email delivery via Gmail Centralized lead tracking in Notion database Key Features ✅ Intelligent Lead Scoring: Analyzes 12+ data points including budget (AED), space count, project type, timeline, and style preferences ✅ Personalized Communication: AI-generated emails reference specific client details, demonstrating genuine understanding ✅ Quality Control: Human-in-the-loop approval via Telegram prevents errors before client contact ✅ Smart Routing: Different workflows for qualified leads (meeting invitations) vs. unqualified leads (respectful alternatives) ✅ Revision Loop: Rejected emails automatically route to revision agent for improvements ✅ Database Integration: All leads stored in Notion for pipeline tracking and analytics Use Cases Interior design firms managing high-volume lead intake Architecture practices with complex qualification criteria Home renovation companies prioritizing project value Any service business requiring budget-based lead scoring Sales teams needing approval workflows before client contact Prerequisites Required Accounts & API Keys: Anthropic Claude API - For AI classification and email generation Telegram Bot Token - For approval notifications Gmail Account - For sending client emails (or any SMTP provider) Notion Account - For lead database storage n8n Account - Cloud or self-hosted instance Technical Requirements: Basic understanding of n8n workflows Ability to create Telegram bots via BotFather Gmail app password or OAuth setup Notion database with appropriate properties Setup Instructions Step 1: Clone and Import Template Copy this template to your n8n instance (cloud or self-hosted) All nodes will appear as inactive - this is normal Step 2: Configure Form Trigger Open the Client Intake Form Trigger node Choose your trigger type: For n8n forms: Configure form fields matching the template structure For webhook: Copy webhook URL and integrate with your website form Required form fields: First Name, Second Name, Email, Contact Number Project Address, Project Type, Spaces Included Budget Range, Completion Date, Style Preferences Involvement Level, Previous Experience, Inspiration Links Step 3: Set Up Claude AI Credentials Obtain API key from https://console.anthropic.com In n8n: Create new credential → Anthropic → Paste API key Apply credential to these nodes: AI Lead Scoring Engine Personalized Client Outreach Email Generator Email Revision Agent Step 4: Configure Telegram Approval Bot Create bot via Telegram's @BotFather Copy bot token Get your Telegram Chat ID (use @userinfobot) In n8n: Create Telegram credential with bot token Configure Human-in-the-Loop Email Approval node: Add your Chat ID Customize approval message format if desired Step 5: Set Up Gmail Sending Enable 2-factor authentication on Gmail account Generate app password: Google Account → Security → App Passwords In n8n: Create Gmail credential using app password Configure Client Email Delivery node with sender details Step 6: Connect Notion Database Create Notion integration at https://www.notion.so/my-integrations Copy integration token Create database with these properties: Client Name (Title), Email (Email), Contact Number (Phone) Project Address (Text), Project Type (Multi-select) Spaces Included (Text), Budget (Select), Timeline (Date) Classification (Select: HOT/WARM/COLD), Confidence (Select) Estimated Value (Number), Status (Select) Share database with your integration In n8n: Add Notion credential → Paste token Configure Notion Lead Database Manager with database ID Step 7: Customize Classification Rules (Optional) Open AI Lead Scoring Engine node Review classification criteria in the prompt: HOT: 500k+ AED, full renovations, 2+ spaces WARM: 100k+ AED, 2+ spaces COLD: <100k AED OR single space Adjust thresholds to match your business requirements Modify currency if not using AED Step 8: Personalize Email Templates Open Personalized Client Outreach Email Generator node Customize: Company name and branding Signature placeholders ([Your Name], [Title], etc.) Tone and style preferences Alternative designer recommendations for COLD leads Step 9: Test the Workflow Activate the workflow Submit a test form with sample data Monitor each node execution in n8n Check Telegram for approval message Verify email delivery and Notion database entry Step 10: Set Up Error Handling (Recommended) Add error workflow trigger Configure notifications for failed executions Set up retry logic for API failures Workflow Node Breakdown 1. Client Intake Form Trigger Captures lead data from website forms or n8n native forms with all project details. 2. AI Lead Scoring Engine Analyzes intake data using structured logic: budget validation, space counting, and multi-factor evaluation. Returns HOT/WARM/COLD classification with confidence scores. 3. Lead Classification Router Routes leads into three priority workflows based on AI classification, optimizing resource allocation. 4. Sales Team Email Notifier Sends instant alerts to sales representatives with complete lead details and AI reasoning for internal tracking. 5. Personalized Client Outreach Email Generator AI-powered composer creating tailored responses demonstrating genuine understanding of client vision, adapted by lead type. 6. Latest Email Version Controller Captures most recent email output ensuring only final approved version proceeds to delivery. 7. Human-in-the-Loop Email Approval Telegram-based review checkpoint sending generated emails to team member for quality control before client delivery. 8. Approval Decision Router Evaluates reviewer's response, routing approved emails to client delivery or rejected emails to revision agent. 9. Email Revision Agent AI-powered editor refining rejected emails based on feedback while maintaining personalization and brand voice. 10. Client Email Delivery Sends final approved personalized emails demonstrating understanding of project vision with clear next steps. 11. Notion Lead Database Manager Records all potential clients with complete intake data, classification results, and tracking information for pipeline management. Customization Tips Adjust Classification Thresholds: Modify budget ranges and space requirements in the AI Lead Scoring Engine prompt to match your market and service level. Multi-Language Support: Update all AI agent prompts with instructions for your target language. Claude supports 100+ languages. Additional Routing: Add branches for special cases like urgent projects, VIP clients, or specific geographic regions. CRM Integration: Replace Notion with HubSpot, Salesforce, or Airtable using respective n8n nodes. SMS Notifications: Add Twilio node for immediate HOT lead alerts to mobile devices. Troubleshooting Issue: Telegram approval not received Verify bot token is correct Confirm chat ID matches your Telegram account Check bot is not blocked Issue: Claude API errors Verify API key validity and credits Check prompt length isn't exceeding token limits Review rate limits on your Anthropic plan Issue: Gmail not sending Confirm app password (not regular password) is used Check "Less secure app access" if using older method Verify daily sending limits not exceeded Issue: Notion database not updating Confirm integration has access to database Verify property names match exactly (case-sensitive) Check property types align with data being sent Template Metrics Execution Time**: ~30-45 seconds per lead (including AI processing) API Calls**: 2-3 Claude requests per lead (classification + email generation, +1 if revision) Cost Estimate**: ~$0.05-0.15 per lead processed (based on Claude API pricing) Support & Community n8n Community Forum**: https://community.n8n.io Template Issues**: Report bugs or suggest improvements via n8n template feedback Claude Documentation**: https://docs.anthropic.com Notion API Docs**: https://developers.notion.com License This template is provided as-is under MIT license. Modify and adapt freely for your business needs. Version: 1.0 Last Updated: October 2025 Compatibility: n8n v1.0+ (Cloud & Self-Hosted), Claude API v2024-10+