Workflow Templates

How it works: Get multi social platform data for SaaS clients with their email and send personalized comms to onboard them as organic creators, partners and ambassadors. Step by step workflow to enrich customer emails with multi social (Instagram, Tiktok, Youtube, Twitter, Onlyfans, Twitch and more) profiles, analytics and metrics using the influencers.club API and sending tailored outreach to activate them as creators. Set up: Hubspot (can be swapped for any CRM like Salesforce, Attio or DB) Influencers.club Gmail Sendgrid (can be swapped for any programmatic email sender like Mailgun)

Quick overview This workflow runs on a schedule to pull leads from an n8n Data Table, fetches and cleans each lead’s website content, uses Google Gemini to draft a personalized cold outreach email in structured JSON, sends it via Gmail, and updates the lead status back in the Data Table. How it works Runs on a schedule and loads sender details, the n8n Data Table ID, email length limits, and rate-limiting settings. Retrieves all leads from the n8n Data Table and checks each lead’s email address against a strict regex format. Marks leads with invalid email addresses as INVALID_EMAIL in the n8n Data Table with an updated timestamp. Fetches the lead’s website HTML and strips scripts, styles, and tags to produce a short plain-text website summary. Sends the lead details, website summary, and sender context to Google Gemini to generate a personalized outreach email returned as a JSON object (subject, greeting, opening line, main body, ending). Sends the generated email to the lead using Gmail with the AI-generated subject and body. Updates the lead record in the n8n Data Table to SENT (including sent time and email subject) and waits for the configured delay to rate-limit sending. Setup Create or choose an n8n Data Table for your leads, ensure it includes fields like id, email, first_name, last_name, company_name, and website plus status tracking columns, and paste its ID into data_table_id in the Set Context step. Add a Google Gemini (PaLM) API credential for the Google Gemini Flash model used to generate the outreach email. Configure Gmail sending credentials (Google API) for the Gmail node, and verify the sending account is allowed to send outbound email. Update the sender/company values and constraints in Set Context (sender name/email, company name/solution, max words, and rate-limit seconds) before activating the workflow. Requirements n8n Version:* Built and tested on *n8n 2.20.0+*. *(Note: You may encounter errors on older versions. It is highly recommended to update to the latest n8n version to use this workflow effectively). Google Gemini** API key credentials. Gmail OAuth2** credentials. Built-in n8n Data Table feature enabled. Customization Change the Email Provider:* Swap out the *Gmail* node for an *Outlook* or *SMTP** node if you use a different mailing service. Change the AI Model:* Replace the *Google Gemini* chat model with *OpenAI (ChatGPT)* or *Anthropic (Claude)** depending on your preference. Integrate your CRM:* Instead of using n8n Data Table, replace the fetch and update nodes with your CRM of choice, such as *HubSpot* or *Pipedrive**. Additional info About the Author Created by: Nguyễn Thiệu Toàn (Jay Nguyen) Email: me@nguyenthieutoan.com Website: nguyenthieutoan.com Company: GenStaff (genstaff.net) Socials (Facebook / X / LinkedIn): @nguyenthieutoan More templates: n8n.io/creators/nguyenthieutoan

How It Works This workflow automates patient risk assessment and clinical alerting for healthcare providers using NVIDIA AI models. Designed for hospitals, clinics, and healthcare organizations, it addresses the critical challenge of timely identification and response to high-risk patients requiring immediate intervention. The system monitors patient data webhooks, enriches records with external EHR data, and analyzes aggregated information through Claude AI for comprehensive risk stratification. Healthcare operations data is fetched and combined with patient metrics to provide contextual risk assessment. NVIDIA's structured generation capabilities ensure standardized clinical outputs, while parallel execution routes enable simultaneous processing: critical cases trigger immediate alerts via email and escalation flags, whereas routine cases follow standard documentation paths. The workflow maintains an audit trail, merges execution results, and generates detailed reports for compliance and quality improvement initiatives. Setup Steps Configure Patient Event Webhook with your EHR system endpoint URL and authentication headers Add NVIDIA API credentials (API key) in Fetch Patient Data and Structured Generation nodes Connect Claude Model node with Anthropic API key and configure healthcare risk assessment prompt Set up Gmail node with sender credentials and configure recipient email addresses for clinical alerts Enable Google Sheets integration for audit logging and specify spreadsheet ID for execution reports Prerequisites NVIDIA API access, Anthropic Claude API key, Google Workspace account (Gmail, Sheets) Use Cases Emergency department triage automation, post-operative monitoring for deterioration detection Customization Modify risk scoring algorithms, add disease-specific assessment criteria Benefits Reduces clinical response time through automated risk detection

How It Works This workflow automates platform trust and safety operations by deploying a multi-agent AI system that detects abuse signals, investigates behaviour, scores risk, checks policy compliance, and enforces actions automatically. Designed for platform safety teams, content moderation managers, and compliance officers, it eliminates manual triage delays and ensures high-severity violations are actioned immediately. An abuse signal webhook triggers behaviour analysis via OpenAI, classifying signals by severity. A routing node directs cases to a Governance Agent, which orchestrates Investigation, Risk Scoring, and Policy Compliance Checker sub-agents. Enforcement data is prepared, then routed by action type-logging to abuse records, alerting the security team via Slack, sending escalation emails, or triggering auto-enforcement actions based on threshold checks—before all outcomes are logged. Setup Steps Configure Abuse Signal Webhook URL and authenticate incoming POST requests. Add OpenAI API credentials to all OpenAI Model nodes. Connect Google Sheets for abuse records and enforcement action logging. Configure Slack credentials and set security team alert channel. Add Gmail/SMTP credentials to Send Escalation Email node. Prerequisites Slack workspace with bot token Gmail or SMTP credentials Google Sheets for abuse and enforcement logging Use Cases Real-time abuse detection and auto-suspension on social platforms Customization Replace OpenAI with Anthropic Claude or NVIDIA NIM models Benefits Eliminates manual abuse triage with real-time AI signal processing

Quick Overview This workflow runs every day at 8 AM, pulls the last 24 hours of emails from your Gmail Primary inbox, summarizes their full content using Groq’s Llama 3.3, and posts an actionable daily inbox briefing to a Slack channel. How it works Runs daily at 8 AM on a schedule. Fetches all Gmail messages from the last day in the Primary category using a Gmail search query. Strips HTML, truncates long bodies, and combines all email subjects, senders, dates, and content into a single capped text block. Sends the compiled inbox text to Groq (Llama 3.3 70B) to generate a Slack-formatted briefing with a TL;DR, urgent items, and an email-by-email summary with tags. Posts the generated briefing to the selected Slack channel. Setup Connect a Gmail OAuth2 credential and ensure the Gmail query (default: newer_than:1d category:primary) matches the emails you want to include. Add a Groq API key credential and confirm the model selection (default: llama-3.3-70b-versatile) and prompt meet your formatting needs. Connect a Slack API credential and choose the target channel to post the briefing. Update the schedule time and confirm your n8n instance timezone so the workflow runs at the intended hour.

Quick Overview This workflow triggers on failed Stripe invoice payments, uses OpenAI to draft an escalating dunning email, sends it via Gmail, logs the outreach to Google Sheets, and notifies the billing team in Slack when the final attempt threshold is reached. How it works Triggers when Stripe emits an invoice.payment_failed event. Extracts and normalizes invoice details like customer email, amount due, currency, attempt count, and hosted invoice URL. Uses OpenAI (GPT-4o-mini) to generate a structured dunning email subject and body that escalates tone based on the attempt number. Sends the generated dunning email to the customer through Gmail. Appends the email/send details to a Google Sheets spreadsheet for dunning tracking. Checks whether the attempt count is 3 or higher and, if so, posts an escalation message to a Slack channel (for example, #billing). Setup Connect Stripe credentials and ensure your Stripe account sends invoice.payment_failed events to the workflow. Add an OpenAI credential for the Chat model used to draft the dunning email. Add Gmail credentials and confirm the sending account is allowed to email your customers. Add Google Sheets credentials, replace the spreadsheet ID in the Google Sheets node, and ensure a sheet/tab named "Dunning" exists. Add Slack credentials and set the target channel (for example, #billing) for final-attempt escalation messages.

Categories: Business Automation, E-commerce, Intelligence, AI This workflow automates high-frequency price tracking across e-commerce platforms. It combines the data-handling power of the Decodo node with the intelligence of Google Gemini to eliminate manual price checks. It is for businesses seeking real-time market intelligence. Benefits Total Automation: Handles data sourcing, and email notifications without human help. Intelligent Extraction: Uses AI to analyze the full page content. Precision Alerting: Triggers notifications when a product's price meets or falls below the "Desired Price." Scalable Architecture: Processes large batches of products. How It Works Scheduled Data Retrieval: The Schedule Trigger pulls a list of URLs and target prices from Google Sheets. Raw Data Processing: Data flows through a Decodo node. Full-Body Extraction: The workflow captures the entire body of the webpage. AI-Driven Analysis: An AI Agent, powered by Google Gemini, analyzes the text to identify the product name and price. Regex Data Cleaning: A JavaScript node uses Regular Expressions to sanitize the AI's response. Smart Comparison & Alerting: An If Node compares the live price against the "Desired Price." If the condition is met, an automated alert is sent via Gmail. Requirements n8n Instance Google Account Google Gemini API Key Decodo Credentials How to Use Setup your Spreadsheet: Create a Google Sheet with columns for the product link and "Desired price." Authenticate Nodes: Connect your Google Sheets, Gmail, and Gemini credentials within n8n. Configure Parameters: Ensure the If node correctly references the "Desired price" column from your Google Sheet output. Deploy: Activate the workflow. The system will now run automatically, monitoring the list and notifying of deals. Business Use Cases Retail Arbitrage Agencies: Spot price drops on supplier sites to maximize profit margins. Competitor Intelligence: Monitor rival pricing strategies. Procurement Departments: Automate the "buy" signal for raw materials when they hit a specific price point. E-commerce Managers: Track MAP (Minimum Advertised Price) compliance. Revenue Potential Increased Margins: Buy inventory at the lowest prices. Market Leadership: React faster than competitors to market-wide price shifts. Service Offering: Provide "Price Watch" services for e-commerce clients. Difficulty Level: Intermediate Estimated Setup Time: 40 min Monthly Operating Cost: Low (based on Gemini API tokens)

Quick Overview This workflow monitors a list of competitor web pages daily using ScraperAPI, detects meaningful content changes, summarizes them with Anthropic Claude, stores the latest snapshots in an n8n Data Table, and sends a daily digest to Slack and email (Gmail or SMTP). How it works Runs on a daily schedule at 8am (and can be run manually to initialize the storage table). Builds a list of competitor URLs to monitor, including the ScraperAPI proxy country code for each target. Iterates through the URLs, scrapes each page via ScraperAPI, cleans/truncates the markdown content, and computes a hash for change detection. Looks up the previous snapshot for each URL in an n8n Data Table and determines whether the content has materially changed. For changed pages, sends the previous and current snapshots to Anthropic Claude to generate a short change summary and upserts the updated snapshot and summary back into the Data Table. For unchanged pages, upserts the latest “last seen” timestamp and hash into the Data Table. After processing, fetches today’s changed summaries from the Data Table, assembles a daily digest, and posts it to Slack and sends it via Gmail and/or SMTP. Setup Add a ScraperAPI credential and ensure it is selected in the ScraperAPI node. Add an Anthropic credential for the Claude chat model used by the AI agent. Configure the competitor URL list (and optional countryCode) in the “Prepare URL List” code step. Add Slack credentials and set the target channel for posting the digest. Configure email delivery by setting up either Gmail credentials and the recipient address, or SMTP settings (from/to addresses and SMTP credential details).

How It Works This workflow automates enterprise claims cost leakage detection by identifying overpayments, policy deviations, and pricing inconsistencies across claims data. It supports claims operations, finance, and audit teams by providing continuous, AI-driven monitoring without manual review. Claims data is ingested through parallel HTTP requests, including claim history, policy details, pricing rules, and enrichment data. Historical claim patterns feed calculator-based risk scoring to flag potential leakage scenarios. All data streams are consolidated and analyzed using GPT-4 with structured outputs to detect anomalies, quantify leakage risk, and recommend corrective adjustments. The workflow generates claim-level findings and routes outcomes by severity: high-risk leakage triggers immediate email and Slack alerts, while lower-risk issues are compiled into periodic audit and recovery reports. Setup Steps Configure HTTP nodes with competitor website APIs Add OpenAI API key to Chat Model node for AI analysis Connect Gmail account and set leadership distribution list Integrate Slack workspace and configure strategy team Adjust Schedule node timing for preferred monitoring frequency Prerequisites OpenAI API key, competitor data source API access, vendor monitoring service credentials Use Cases SaaS companies tracking competitor feature releases and pricing changes Customization Modify risk scoring formulas in Calculator nodes for industry-specific metrics Benefits Transforms hours of manual competitor research into automated minutes-long cycles

How It Works This automated disaster response workflow streamlines emergency management by monitoring multiple alert sources and coordinating property protection teams. Designed for property managers, insurance companies, and emergency response organizations, it solves the critical challenge of rapidly identifying at-risk properties and deploying resources during disasters.The system continuously monitors weather, seismic, and flood alerts from authoritative sources. When threats are detected, it cross-references property databases to identify affected locations, calculates insurance exposure, and generates damage assessments using OpenAI's GPT-4. Teams receive automated maintenance schedules while property owners and insurers get instant email notifications with comprehensive reports. This eliminates manual monitoring, reduces response time from hours to minutes, and ensures no vulnerable properties are overlooked during emergencies. Setup Steps Configure alert fetch nodes with weather/seismic/flood API endpoints Connect property database credentials (specify database type) Add OpenAI API key for GPT-4 damage assessments Set up Gmail/SMTP credentials for owner and insurer notifications Customize insurance calculation formulas and team scheduling logic Prerequisites Weather/seismic/flood alert API access, property database (SQL/Sheets/Airtable) Use Cases Insurance companies automating claims preparation, property management firms protecting rental portfolios Customization Modify alert source APIs, adjust damage assessment prompts Benefits Reduces emergency response time by 90%, eliminates manual alert monitoring

How It Works Top Branch Workflow* 1. The Data Scientist: Ingest: Pulls historical sales data from Google Sheets. Math Engine: Runs 7 statistical algorithms (e.g., Seasonal Naive, Linear Trend, Regression). It backtests them against your history and scientifically selects the winner with the lowest error rate. 2. The Data Analyst: Interpret: The AI Agent takes the mathematical output and translates it into business insights, assigning confidence scores based on error margins. Report: Generates a visual trend chart (PNG) and sends a complete briefing to your phone. Bottom Branch Workflow* 3. The Consultant: AI Agent 2 handles the follow-up questions. It pulls the latest analysis context and checks historical rate data to give an informed answer. Recall: When you ask a question via WhatsApp, the bot retrieves the saved forecast state. Answer: It acts as an on-demand analyst, comparing current forecasts against historical actuals to give you instant answers. Setup Steps 1) Google Sheet: Prepare columns: Year, Month, Sales. Map the Sheet ID in the "Workflow Configuration" node. 2) Forecast Engine: No config needed. It automatically detects seasonality vs. linear trends. 3) Database: Create a table latest_forecast to store the JSON output. 4) Credentials: Connect Google Sheets, OpenAI, and WhatsApp Use Cases & Benefits For Business Owners: Gain enterprise-grade forecasting on autopilot. Always have a sophisticated financial outlook running in the background 24/7. For Sales Leaders: Get immediate visibility into future revenue trends. Bypass the wait for end-of-month manual reports and get a strategic "pulse check" delivered instantly to your phone. 🤖Virtual Data Team: Instantly add the capabilities of a Data Scientist and Data Analyst to your business or division. It works alongside your existing team to handle the heavy lifting, or stands in as your dedicated automated department. 🧠Precision & Trust: Combines the best of both worlds: rigorous, deterministic code for the math (no hallucinations) and advanced AI for the strategic explanation. You get numbers you can trust with context you can use. ⚡Decision-Ready Insights: Stop digging through dashboards. High-level intelligence is pushed directly to you on WhatsApp, allowing you to make faster, data-driven decisions from anywhere. 📬 Want to Customize This? leelin.business@gmail.com

Quick Overview This workflow collects a construction Scope of Work PDF via an n8n form, uses Azure OpenAI to extract BOQ-style line items, prices them using a Google Sheets unit-rate database, generates a formatted Google Docs bid report, logs the estimate to Google Sheets, and emails the result via Gmail. How it works Receives project details and a Scope of Work PDF through an n8n form submission. Extracts text from the uploaded PDF and sends it to Azure OpenAI (GPT-4o-mini) to return structured JSON line items. Cleans and parses the AI response into individual BOQ items enriched with project name, client name, and estimator email. Looks up matching unit rates in a Google Sheets UnitRates sheet using keyword matching and applies category-based fallback rates when no match is found. Calculates total cost per line item, aggregates all items, and builds a bid summary with category totals and grand totals including 18% GST. Creates a Google Docs report, writes the full bid content into the document, and appends the generated estimate text to a Google Sheets BidLog sheet. Emails the estimator via Gmail with key totals and a link to the Google Docs report. Setup Add credentials for Azure OpenAI, Google Sheets OAuth2, Google Docs OAuth2, Gmail OAuth2, and Slack OAuth2 (for error alerts). Create or update a Google Sheets file with a UnitRates sheet containing columns like “Description Keyword”, “Unit Rate (₹)”, and “Source / Project Ref”, and ensure a BidLog sheet exists for appended logs. Replace the placeholder Google Sheets document ID and the Google Drive folder ID in the Google Sheets and Google Docs nodes. Activate the workflow and share the generated n8n form URL with estimators so they can upload SOW PDFs and receive emailed estimates.