Workflow Templates

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.

AI-Powered Hiring Pipeline: Auto-Screen CVs, Score Candidates & Send Interview Invites Stop manually reading every CV. This workflow watches your inbox, extracts CV text using Mistral OCR, scores every candidate against your job description using Google Gemini AI, and automatically routes them - shortlisted candidates get a professional interview invite, rejected ones get a polite decline, and HR receives a full AI summary with the CV attached. All hands-free. Who Is This For? HR teams and recruiters** at startups or growing companies who receive a high volume of CV emails Technical hiring managers** who want AI-assisted pre-screening before spending time on interviews Solo founders** who are hiring but don't have a dedicated recruiter No-code automation builders** looking for a production-ready hiring automation template What Problem Does This Solve? Manually reviewing CVs is time-consuming, inconsistent, and expensive. This workflow eliminates the bottleneck by automatically: Extracting CV text from PDF attachments (including scanned documents) via Mistral OCR Evaluating every candidate against your specific job description using Gemini AI Routing candidates and sending the right email to the right person - instantly You focus on interviewing. The pipeline handles everything else. Key Features 📥 Email-triggered** → fires automatically when a CV arrives in your inbox, no manual steps 📄 Mistral OCR** → works on both digitally-created and scanned/image-based PDF CVs 🤖 Gemini AI scoring** → returns a 0–100 score, shortlist/reject decision, candidate summary, and key skills 🔀 Smart routing** → shortlisted and rejected candidates are handled differently in the same workflow 📧 3 beautiful HTML email templates** → HR notification (with CV attached), interview invite, and polite decline ⚙️ Binary passthrough** → original CV PDF is preserved and forwarded to HR's email as an attachment 📋 Sticky note documentation** → every node is documented inside the workflow canvas How It Works (Step-by-Step) 📥 Watch Inbox → IMAP trigger fires when a new email arrives with a CV attachment 📄 OCR Extraction → Mistral's mistral-ocr-latest model reads the CV and outputs clean structured text 🤖 AI Scoring → Google Gemini evaluates the CV against your job description and returns a structured JSON with score, decision, candidate name, 3–4 sentence summary, and top 5 skills ⚙️ Parse & Route → a Code node cleans Gemini's response, extracts candidate email from the IMAP from field, and passes the binary CV forward 🔀 IF Decision → routes shortlisted candidates to the true branch and rejected to the false branch 📧 HR Email → HR receives a branded email with the AI score, candidate summary, key skills, and the original CV attached 📧 Interview Invite → shortlisted candidate receives a professional invitation with a scheduling link and "What to Expect" section 📧 Polite Decline → rejected candidate receives a warm, empathetic decline with a link to your careers page 🛠️ Setup Instructions Step 1 - Credentials Required You need to set up 4 credentials in n8n: | Credential | Node Used | Where to Get It | |---|---|---| | IMAP account | Email Trigger | Your email provider settings (Gmail: use App Password) | | Mistral Cloud API | OCR Extraction | Mistral AI Studio → API Keys | | Google Gemini (PaLM) API | AI Scoring | Google AI Studio → Get API Key | | SMTP account | All 3 email nodes | Your email provider SMTP settings | > 💡 Gmail users: Enable 2FA and generate an App Password for both IMAP and SMTP. Use imap.gmail.com:993 and smtp.gmail.com:587. Step 2 - Update Email Addresses In all 3 Send Email nodes, replace the placeholder emails: fromEmail → your sending address (e.g. hr@yourcompany.com) toEmail in the HR node → your HR team's inbox The candidate email fields are already dynamic ({{ $json.candidate_email }}) Step 3 - Add Your Job Description Open the 🤖 AI Score CV (Gemini) node and replace the JOB DESCRIPTION: section in the prompt with your actual role requirements. The current template uses an AI Engineer JD from AppStoneLab as a working example. Step 4 - Add Your Interview Scheduling Link In the 📧 Send Interview Invite to Candidate node, find YOUR_CALENDLY_OR_CAL_LINK_HERE in the HTML and replace it with your actual booking link (Calendly, Cal.com, TidyCal, etc.). How to Customize for Your Use Case | What to Change | Where | Example | |---|---|---| | Job description | Gemini node prompt | Swap in your own role requirements | | Scoring threshold | IF node condition | Change "shortlisted" to score-based logic e.g. score >= 70 | | Company name & branding | All 3 HTML email templates | Replace "AppStoneLab Technologies" with your company | | Careers page URL | Decline email HTML | Replace appstonelab.com/career with your URL | | AI model | Gemini node | Switch to gemini-3-flash-preview or gemini-3.1-pro-preview for different speed/quality | | Watched mailbox | IMAP trigger | Change INBOX to a dedicated folder like INBOX.careers | | Interview questions | Invite email HTML | Add/edit the "What to Expect" section steps | API Keys — Quick Links Mistral AI** → Mistral AI Studio - Free tier includes OCR. Pricing: $1 per 1,000 pages for mistral-ocr-latest Google Gemini** → Google AI Studio - Free tier available. gemini-3-flash-preview is fast and cheap for production Gmail App Password** → Google App Passwords n8n IMAP docs** → docs.n8n.io/integrations/core-nodes/n8n-nodes-base.emailimap n8n SMTP docs** → docs.n8n.io/integrations/core-nodes/n8n-nodes-base.sendemail Important Notes The IMAP Format field must be set to Resolved (not Simple) - this is required for binary attachment data to flow correctly through the workflow The Code node carries the binary CV attachment forward from the IMAP trigger to the HR email node. If you add new nodes between them, make sure binary passthrough is preserved Mistral OCR works on both text-based and scanned/image PDFs, making it more reliable than n8n's built-in Extract from File node The workflow uses the from.value[0].address path to extract the candidate's email from the IMAP trigger output - this is the correct path for the Resolved format 💬 Questions or Issues? Drop a comment on this template or reach out on the n8n community forum. Happy to help you adapt this for your specific hiring use case.

Who's it for This workflow is perfect for content creators, international teams, and businesses that need to translate documents into multiple languages automatically. Whether you're localizing documentation, translating marketing materials, or creating multilingual content, this workflow saves hours of manual work. What it does Automatically monitors a Google Drive folder for new documents (PDF, DOCX, TXT, or Markdown) and translates them into multiple languages using DeepL API. Each translated document is saved with a language-specific filename (e.g., document_en.pdf, document_zh.pdf) in a designated folder. You receive an email notification when all translations are complete. How it works Monitors a Google Drive folder for new files Detects file format (PDF/DOCX/TXT/Markdown) and extracts text Translates the content into your chosen languages (default: English, Chinese, Korean, Spanish, French, German) Saves translated files with language codes in the filename Sends an email notification with translation summary Optional: Records translation history in Notion database Set up instructions Requirements Google Drive account (for file storage) DeepL API key (free tier: 500,000 characters/month) Gmail account (for notifications) Notion account (optional, for tracking translation history) Setup steps Create Google Drive folders: Create a "Source" folder for original files Create a "Translated" folder for output Copy the folder IDs from the URLs Get DeepL API key: Sign up at DeepL API Copy your API key Configure the workflow: Open the "Configuration (Edit Here)" node (yellow node) Replace folder IDs with your own Set your notification email Choose target languages Set up credentials: Add Google Drive OAuth2 credentials Add DeepL API credentials Add Gmail OAuth2 credentials Activate the workflow and upload a test file! Customization options Change target languages**: Edit the targetLanguages array in the Configuration node (supports 30+ languages) Adjust polling frequency**: Change trigger from "every minute" to hourly or daily for batch processing Enable Notion tracking**: Set enableNotion to true and provide your database ID Add more file formats**: Extend the Switch node to handle additional file types Filter by file size**: Add conditions to skip files larger than a certain size Supported languages EN (English), ZH (Chinese), KO (Korean), JA (Japanese), ES (Spanish), FR (French), DE (German), IT (Italian), PT (Portuguese), RU (Russian), and 20+ more. Performance Short files** (1 page): ~30 seconds for 6 languages Medium files** (10 pages): ~2 minutes for 6 languages Large files** (100 pages): ~15 minutes for 6 languages Technical Details Trigger**: Google Drive folder monitoring (1-minute polling) Translation**: DeepL API with automatic source language detection Loop implementation**: Split Out + Aggregate pattern for parallel translation Error handling**: Catches API failures and sends email alerts Storage**: Original file format preserved in translated outputs Notes DeepL free tier provides 500,000 characters/month (approximately 250 pages) For high-volume translation, consider upgrading to DeepL Pro The workflow creates new files instead of overwriting, preserving translation history Google Docs are automatically converted to the appropriate format before translation What You'll Learn This workflow demonstrates several n8n patterns: File format detection and routing (Switch node) Loop implementation with Split Out + Aggregate Binary data handling for file operations Conditional logic with IF nodes (optional features) Cross-node data references Error handling and user notifications Perfect for learning automation best practices while solving a real business problem!

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

Automated Sales Rep Clone Outreach Video and Voice Note for B2B Outbound This workflow automatically transforms new leads from Google Sheets into hyper-personalized outreach videos, voice notes, and emails using AI research, scriptwriting, video cloning, and voice generation. Perfect for SDRs, founders, and agencies who want to scale outreach without sacrificing personalization. 🎥 Watch step by step build: https://www.youtube.com/watch?v=q9AAh9zRou4 What this template does Whenever a new row is added to your Google Sheets CRM, this workflow: Reads the new lead (Name, Email, Phone, Company, Industry, LinkedIn URL) Runs deep research on the person & company using Perplexity Generates a personalized 30-second outreach script Creates a cloned-face, AI-generated HeyGen video with the script Creates an ElevenLabs voice note using the same personalized insights Uploads the audio file to Google Drive Sends an email to yourself containing: Outreach subject line Email body Personalized video link Personalized voice note link (Optional) Sends a WhatsApp/SMS/MMS message via Twilio with the files or links This template builds a complete AI-powered outbound engine—research, video, voice note, and email—fully automated. Why this is useful Turns manual outbound into a hands-free, 360° AI workflow Personalized video outreach dramatically increases reply rates Consistent research quality for every lead SDRs save hours per day on manual prep Perfect for: Influencer agencies SaaS outbound teams Founders doing cold outreach Recruitment agencies Real estate & service businesses Requirements Before running this workflow, connect: Google Sheets OAuth (trigger + CRM sheet) Perplexity API Key OpenAI API Key (GPT-5.1, GPT-4.1-mini) OpenRouter API Key HeyGen API Key (for video avatar) ElevenLabs API Key (for voice note) Google Drive OAuth (for file upload) Twilio credentials (optional SMS/WhatsApp) ⚠️ All credentials must be added manually after importing. This ensures security and complies with n8n Template Guidelines. How it works (Node Breakdown) Google Sheets Trigger Watches your CRM sheet and fires whenever a new lead row is added. Code Node — Extract Latest Row Ensures only the newly added row continues through the workflow. Research Agent Powered by OpenAI + Perplexity Scrapes professional history, company insights, marketing gaps Identifies outreach opportunities & triggers Produces a structured research summary Scripting Agent Writes a natural, human-sounding 30-second outreach script tailored to that exact lead. HeyGen Video Generator Creates a personalized avatar video narrating the script (720×1280). ElevenLabs Voice Generation Generates a custom voice note version of the pitch. Google Drive Upload Saves the voice note file for sharing or sending via WhatsApp. Twilio Message (optional) Sends the voice note or video link via SMS/WhatsApp. Email Output Creates a fully structured JSON email including: Subject line Personalized body HeyGen video link Voice note link Delivered via Gmail node. Setup (Step-by-Step) Import the template into n8n Open Google Sheets Trigger → choose your CRM sheet Add all required credentials: Perplexity OpenAI OpenRouter HeyGen ElevenLabs Google Drive Gmail Twilio (optional) In HeyGen node, choose: Your avatar Your preferred voice ID In ElevenLabs node, set: Your preferred voice model Review the system prompts of: Research Agent Script Agent Email Agent Adjust for your brand tone if needed. Run once manually to test. Turn on the workflow—your AI outbound engine is live. Customization Ideas Swap HeyGen avatar to match your brand identity Add a Slack notification when each video is ready Save research & scripts into a Notion database Create a HubSpot contact for each lead Add duplicate detection logic Auto-post video to social channels for public outreach Troubleshooting Video stuck in “processing”? → Increase the Wait node duration (30–60 sec). Voice note too robotic? → Switch to a premium ElevenLabs voice. Research not specific enough? → Strengthen the system prompt with more constraints. Emails not arriving? → Ensure Gmail OAuth has send permission configured. API authentication errors? → Check credentials in each node (OpenAI, Perplexity, HeyGen, etc.).

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

Competitor Price Monitoring with AI-Powered Alerts What this workflow does This workflow automatically monitors competitor product prices on a scheduled basis, detects meaningful price changes, and delivers actionable alerts enriched with AI-powered competitive analysis. It compares current and historical price datasets, identifies increases, decreases, new products, and removals, and uses AI to assess market impact and recommend strategic actions. Alerts are intelligently routed to Slack or Email based on urgency, while all results are logged for auditing and trend analysis. This template is ideal for pricing teams, product managers, and competitive intelligence workflows that require timely, data-driven insights without manual monitoring. How it works Scheduled execution Runs on a configurable cron schedule (default: every 6 hours). Initializes a monitoring session with timestamps and tracking IDs. Price data collection Fetches current competitor pricing via HTTP APIs. Retrieves previous price snapshots from Google Sheets. Data normalization & comparison Normalizes current and historical data into a unified schema. Uses the Compare Datasets node to detect: New products Removed products Price increases or decreases Unchanged prices Change evaluation Calculates percentage price changes. Classifies severity: Urgent: ≥ 10% change Routine: 5–10% change No alert: < 5% or unchanged AI-powered analysis An AI agent evaluates competitive impact. Generates concise recommendations (match, hold, differentiate). Justifies urgency based on market implications. Smart alert routing Urgent changes are sent to Slack. Routine updates are sent via Email. All alerts and runs are logged in Google Sheets. Historical storage Updates price history for future comparisons. Maintains a complete monitoring audit trail. Setup requirements Before activating the workflow, configure the following: Replace the competitor price API endpoint with your own data source. Define product identifiers consistently (SKU, product ID, etc.). Configure Google Sheets documents and sheet names for: Price history Alert logs Monitoring logs Adjust alert thresholds or schedules as needed. Required credentials This workflow requires the following credentials to be set up in n8n: HTTP Header Auth** (for competitor price APIs) OpenAI** (for AI-based price analysis) Slack** (urgent alerts) Gmail** (routine email notifications) Google Sheets** (price history and logging) Customization ideas Add additional alert channels (Microsoft Teams, Discord, Webhooks). Extend AI analysis with competitor positioning or elasticity insights. Monitor multiple regions or currencies. Add dashboards using BI tools connected to Google Sheets. Trigger downstream pricing or promotion workflows automatically. Who this is for Pricing & revenue operations teams E-commerce and SaaS product managers Competitive intelligence analysts Growth and strategy teams needing real-time market awareness This template provides an end-to-end, scalable foundation for AI-assisted competitive price monitoring—turning raw price changes into actionable business decisions.

This n8n workflow automates job discovery by scanning company career pages, extracting open positions using AI, filtering them by department, and sending real-time alerts via Slack and email. It is ideal for monitoring targeted job roles (such as Engineering) across multiple companies without manual checking. Use Cases Targeted Job Monitoring: Automatically track new job postings for a specific department or role. Faster Job Alerts: Receive instant Slack and email notifications when relevant positions are found. Multi-Company Career Tracking: Monitor multiple company career pages from a single Airtable base. Reduced Noise: Filter out irrelevant roles and avoid empty or misleading notifications. Good to Know The workflow runs on a schedule and processes career pages stored in Airtable. Jobs are processed in batches with a delay node to avoid rate limits or scraping issues. Google Gemini is used for intelligent job extraction and filtering, which may incur API costs. If no relevant jobs are found, the workflow safely returns “No matching positions found” to prevent false alerts. Some Gemini models may be geo-restricted depending on your region. How it Works Step 1: Job Source & Scheduling A Schedule Trigger starts the workflow and defines the job category to monitor (e.g., Engineering). Airtable is queried to fetch all company career page URLs. Step 2: Scraping & Extraction Each career page is scraped using Decodo. Google Gemini analyzes the raw page content and extracts job titles with application URLs while ignoring navigation and non-job content. Step 3: Data Cleaning & Structuring A JavaScript code node cleans the AI output, removes noise (e.g., “No open positions”), and converts results into structured job items. Step 4: AI-Based Filtering A second AI Agent compares extracted jobs against the target department and keeps only relevant roles. Step 5: Notifications Matching jobs are sent instantly to Slack and email. How to Use Airtable Credentials: Connect Airtable and store career page URLs in the table. Google Gemini Credentials: Add your Gemini API key for AI extraction and filtering. Slack Credentials: Select a user or channel to receive job alerts. Gmail Credentials: Configure Gmail to receive job notification emails. Schedule Setup: Adjust the trigger interval based on how often you want job checks. Activate Workflow: Enable the workflow to start automated job monitoring. Requirements n8n instance (self-hosted or cloud) Airtable base with company career page URLs Google Gemini API key Slack workspace Gmail account for email notifications

Overview This workflow implements a complete Retrieval-Augmented Generation (RAG) knowledge assistant with built-in document ingestion, conversational AI, and automated analytics using n8n, OpenAI, and Pinecone. The system allows users to upload documents, automatically convert them into embeddings, query the knowledge base through a chat interface, and receive daily reports about chatbot performance and document usage. Instead of manually searching through documentation, users can ask questions in natural language and receive answers grounded in the uploaded files. The workflow retrieves the most relevant document chunks from a vector database and provides them to the language model as context, ensuring accurate and source-based responses. In addition to answering questions, the workflow records all chat interactions and generates daily usage analytics. These reports summarize chatbot activity, highlight the most referenced documents, and identify failed lookups where information could not be found. This architecture is useful for teams building internal knowledge assistants, documentation chatbots, AI support tools, or searchable company knowledge bases powered by Retrieval-Augmented Generation. How It Works Document Upload Interface Users upload PDF, CSV, or JSON files through a form trigger. These documents become part of the knowledge base used by the chatbot. Document Processing Uploaded files are loaded and converted into text. The text is split into smaller chunks to improve embedding quality and retrieval accuracy. Embedding Generation Each text chunk is converted into vector embeddings using the OpenAI Embeddings node. Vector Database Storage The embeddings are stored in a Pinecone vector database. This creates a searchable semantic index of the uploaded documents. Chat Interface Users interact with the knowledge base through a chat interface. Each message becomes a query sent to the RAG system. RAG Retrieval The workflow retrieves the most relevant document chunks from Pinecone. These chunks are provided to the language model as context. AI Response Generation The chatbot generates an answer using only the retrieved document information. This ensures responses remain grounded in the knowledge base. Chat Logging User questions, AI responses, timestamps, and referenced documents are logged. This enables monitoring and analytics of chatbot usage. Daily Analytics Workflow A scheduled trigger runs every morning. The workflow retrieves chat logs from the previous 24 hours. Report Generation Usage statistics are calculated, including: total questions asked failed document lookups most referenced documents overall success rate. Email Summary A formatted HTML report is generated and sent via email to provide a daily overview of chatbot activity and knowledge base performance. Setup Instructions Configure Pinecone Create a Pinecone index for storing document embeddings. Enter the index name in the Workflow Configuration node. Add OpenAI Credentials Configure credentials for: OpenAI Chat Model OpenAI Embeddings node. Configure Data Tables Create the following n8n Data Tables: form_responses chat_logs Set Workflow Parameters In the Workflow Configuration node configure: Pinecone namespace chunk size chunk overlap retrieval depth (top-K). Configure Email Notifications Add Gmail credentials to send daily summary reports. Deploy the Workflow Share the document upload form with users. Enable the chat interface for question answering. Use Cases Internal Knowledge Assistant Allow employees to search internal documentation using natural language questions. Customer Support Knowledge Base Provide instant answers from support manuals, product documentation, or help center articles. Documentation Search Engine Turn large document collections into an AI-powered searchable knowledge system. AI Helpdesk Assistant Enable support teams to quickly retrieve answers from company knowledge repositories. Knowledge Base Analytics Monitor chatbot usage, identify missing documentation, and understand which files are most valuable to users. Requirements n8n with LangChain nodes enabled OpenAI API credentials Pinecone account and index Gmail credentials for sending reports n8n Data Tables: form_responses chat_logs