Workflow Templates

This n8n template demonstrates how to automatically analyze all your accumulated notes from the past week and generate actionable insights, task lists, and priorities using AI. Use cases are many: Try automating weekly planning sessions, extracting action items from meeting notes, identifying recurring themes in your thoughts, or creating data-driven weekly reports for personal productivity tracking! Good to know ChatGPT analysis costs approximately $0.01-0.05 per week depending on the volume of notes The workflow uses advanced date filtering to process exactly 7 days of content Email sending requires SMTP configuration (Gmail, Outlook, etc.) Perfect companion:* Works seamlessly with the "Audio Notes to Google Docs*" workflow - it reads and analyzes all notes created by that system! How it works A schedule trigger runs every Sunday at your preferred time (default: 11 PM) The workflow reads your complete Google Doc containing all accumulated notes A smart filter function extracts only entries from the past 7 days using date stamp recognition The filtered content gets sent to ChatGPT which analyzes patterns and extracts: Actionable tasks for next week Important deadlines and appointments Key insights and learnings Top 3 priorities Category distribution (Work, Private, Health, etc.) A second AI call creates a personalized email summary with context and recommendations The structured analysis gets appended to your Google Doc as a weekly summary You receive a Telegram notification when the review is complete A detailed email report lands in your inbox with the full analysis and action items How to use The workflow runs automatically every Sunday - no manual intervention needed Adjust the schedule trigger to your preferred day/time for weekly planning Review the email summary and use the extracted tasks for your upcoming week planning The Google Doc serves as your permanent archive of weekly insights Requirements Google Docs API access to read your notes document OpenAI API account for ChatGPT analysis (GPT-4 recommended for best results) SMTP email configuration for sending summary reports Telegram Bot Token for notifications Prerequisite:* The *"Audio Notes to Google Docs**" workflow or similar system that creates timestamped entries Customising this workflow Modify the AI analysis prompt to focus on specific areas (business metrics, health tracking, learning goals) Add multiple analysis modes (daily, bi-weekly, monthly reviews) Include additional outputs like calendar event creation, task manager integration, or team sharing Connect to project management tools like Notion, Asana, or Monday.com for automatic task creation

This n8n template allows you to automatically monitor your company's budget by comparing live Bexio accounting data against targets defined in Google Sheets, sending automated weekly email reports. It also exports your financial data from Bexio into a flexible spreadsheet environment. Financial overspending often goes unnoticed until it's too late. This workflow transforms reactive accounting into proactive management by automatically calculating monthly actuals and flagging budget overages in real-time, eliminating the need for manual spreadsheet updates. Who’s it for This workflow is built for Founders and CFOs who want to replace reactive accounting with proactive financial management. It is the ideal solution for leadership teams needing to eliminate manual data entry, synchronize live Bexio actuals against Google Sheet targets, and receive automated weekly email reports that proactively flag budget overages before they become critical issues. How it works The workflow automates the extraction and analysis of your Bexio accounting journal through several stages: Data Extraction: It uses a recursive pagination loop to fetch journal entries from the Bexio API in batches of 1,000 records. Data Synchronization: It utilizes the "Append or Update" operation in Google Sheets to ensure records stay current without creating duplicates. Financial Analysis: The system reads target thresholds from a "Budgets" sheet and aggregates costs per account by calculating the delta between Debits and Credits. Automated Reporting: A logic engine compares monthly actuals against budgets and generates a summary report sent via Gmail if thresholds are exceeded. How to set up Credentials: Connect your Bexio (Bearer Token), Google Sheets (OAuth2), and Gmail accounts in their respective nodes. Target Sheet: In the "Update Records" node, select your specific Google Spreadsheet and target tab for the journal entries. Use this template to create your database - Google Sheet Template Budget Configuration: Clone the template spreadsheet and define your specific metrics and monthly budget limits in the "Budgets" sheet. Date Filtering: Open the "Get Records" node and adjust the from and to query parameters (currently set for the 2025 fiscal year) to match your reporting period. Gmail: Enter the recipient email address in the "To" field of the Gmail node. Requirements Bexio Account: Must have API access enabled. Google Workspace: Access to Google Sheets for data storage and Gmail for sending reports. How to customize the workflow Budget: You can set budgets for as many metrics as you want for every accounting period. Sync Frequency: The "Schedule Trigger" can be adjusted from its weekly default to daily or hourly for more frequent updates. Notification Channels: Swap the Gmail node for Slack or Microsoft Teams to receive report via different channels. Rate Limiting: If processing a very large journal, increase the "Delay" node duration to remain within Bexio’s API rate limits. Pagination Reuse: The pagination logic can be adapted to retrieve any other Bexio data limited by API batch sizes.

📊 Description IPL fans expect more than a scoreboard. They want to know what the score means — is the batting team ahead of the game, is the chase getting away from them, who has the pressure right now. This workflow answers all of that automatically by fetching live IPL match data every 6 minutes, computing key cricket indicators, and sending everything to GPT-4o which generates a punchy 2-sentence analyst-style narrative ready to embed in any fan app, widget, or dashboard without a single line of custom backend code. Built for fantasy cricket platforms, sports media companies, IPL fan apps, and broadcast technology teams who want to add intelligent real-time commentary to their products without hiring a commentary team or training machine learning models. What This Workflow Does ⏰ Fires automatically every 6 minutes between 2PM and 11PM covering all IPL match windows 🌐 Accepts manual triggers via webhook for on-demand narrative generation at any time 🏏 Fetches all current cricket matches from CricAPI in real time on every execution 🔍 Dynamically identifies the live IPL match from the API response — no hardcoded match IDs 🧮 Detects which innings is active and computes all key match indicators automatically 🤖 Sends structured match context to GPT-4o which generates a 2-sentence human-sounding narrative 📝 Logs every narrative to Google Sheets with full match context for audit and analytics 📤 Returns a clean JSON response via webhook that any app or widget can poll in real time ⚠️ Fires an email alert if any node fails so you always know when the workflow needs attention Key Benefits ✅ Fully dynamic — no hardcoded match IDs, works across the entire IPL season ✅ Handles both 1st and 2nd innings with different logic and prompts per scenario ✅ GPT-4o sounds like a human analyst not a notification system ✅ Webhook response makes it embeddable in any fan app or widget instantly ✅ Complete match log in Google Sheets — every narrative timestamped and stored ✅ Falls back to any live T20 match when IPL is off-season so testing never breaks ✅ Error trigger ensures failures never go unnoticed How It Works Trigger Layer Two triggers run this workflow. The Schedule Trigger fires every 6 minutes between 2PM and 11PM IST covering both day games starting around 3:30PM and evening games starting around 7:30PM. The Webhook Trigger provides a manual entry point so developers can fire the workflow on demand for testing or to power a real-time polling architecture where a frontend app hits the webhook URL every few minutes to get the latest narrative. Both triggers feed into the same API call so the logic is completely identical regardless of how the workflow was triggered. Data Fetch & Match Detection A single HTTP Request node fetches all current cricket matches from CricAPI's /v1/currentMatches endpoint. The Code node then scans the response and dynamically finds the live IPL match by checking that the match name contains "IPL" or "Indian Premier League", the match type is T20, and the match has started but not ended. No match IDs are hardcoded anywhere — the workflow finds the right match on every execution. When IPL is not in season the workflow falls back to any live T20 match so development and testing are never blocked. Indicator Computation Once the match is identified the Code node detects which innings is active based on how many score entries the API returns. For the 1st innings it computes the current run rate, overs remaining, wickets in hand, projected total, match phase (Powerplay / Middle / Death), and pressure level. For the 2nd innings it additionally computes the required run rate, runs needed, run rate gap between RRR and CRR, and a pressure index based on how difficult the chase is becoming. Both scenarios produce a structured flat object that gets assembled into a context-rich GPT-4o prompt tailored to the specific innings situation. AI Narrative Generation The prompt is sent to GPT-4o via HTTP Request with a system prompt that instructs the model to write exactly 2 sentences, use the specific numbers provided, sound like a human cricket analyst, use cricket language fans understand, and never use percentages. The result is a narrative like "Mumbai Indians need 45 off 24 balls with 7 wickets in hand — the muscle is there but one collapse changes everything. Jasprit Bumrah has to be kept for the final two overs or this chase gets away from Kolkata." The narrative is then parsed from the API response and passed to both output nodes. Output & Logging Every narrative is appended to a Google Sheets log with the full match context — timestamp, match name, innings, current over, score, target, RRR, CRR, phase, pressure level, and the narrative text. This creates a complete over-by-over record of every narrative generated across the entire match. Simultaneously the Respond to Webhook node returns a clean JSON payload containing the match name, innings, score, over, phase, pressure, narrative, and timestamp — ready for any frontend app or dashboard to consume directly. Features Cron-based schedule trigger covering all IPL match hours Manual webhook trigger for on-demand generation and frontend polling Single API call architecture — one HTTP node, no unnecessary API calls Dynamic live IPL match detection — no hardcoded IDs 1st innings mode — CRR, projected total, wickets in hand, phase, pressure 2nd innings mode — RRR, CRR, run rate gap, runs needed, overs remaining, pressure Three-tier match phase detection — Powerplay, Middle overs, Death overs Pressure index computation based on RRR and wickets GPT-4o via HTTP Request — stable across all n8n versions Structured system prompt enforcing 2-sentence format and cricket language Google Sheets append logging with full match context per narrative Webhook JSON response for real-time frontend integration No Operation node on false branch for clean workflow termination Workflow-level Error Trigger with Gmail alert on any failure Requirements CricAPI account and API key — free tier at cricapi.com OpenAI API key (GPT-4o access) Google Sheets OAuth2 connection Gmail OAuth2 connection (for error alerts) Setup Steps Sign up at cricapi.com and get your free API key Create a Google Sheet called "IPL Win Probability Log" with the columns listed above Paste your Sheet ID into the Google Sheets node Connect your Google Sheets OAuth2 credentials Add your OpenAI API key to the Authorization header of the GPT-4o HTTP Request node in the format Bearer YOUR_KEY Connect your Gmail OAuth2 credentials to the error alert node Activate the workflow Target Audience 🏏 Fantasy cricket platforms who want to add real-time match intelligence to their user experience 📱 IPL fan apps and cricket portals looking for AI-generated commentary without a commentary team 📺 Broadcast technology teams building real-time graphics and insight widgets 🤖 Automation agencies building sports intelligence products for IPL franchise and media clients

This n8n template from Intuz provides a complete and automated solution for full-cycle invoicing, orchestrating a seamless flow between Airtable, QuickBooks, and Stripe. This is the ultimate sales-to-cash automation. When a deal in Airtable is marked "Approved for Invoicing," this workflow intelligently syncs customer data across QuickBooks and Stripe (creating them if they don't exist), generates an official QuickBooks invoice, creates a Stripe payment link, and then updates the original Airtable record with all the new IDs and links. Eliminate manual data entry and keep your systems perfectly in sync. Who's this workflow for? Finance, Accounting, and Operations Teams SalesOps and RevOps Teams Small Business Owners and Founders Agencies and Freelancers How It Works: 1. Airtable Trigger & Approval Gate: The workflow starts when a record in your Airtable base is updated. An If node immediately checks if the Status field is set to "Approved for Invoicing." If not, the workflow for that item stops. 2. Customer Sync (QuickBooks & Stripe): The workflow searches for the customer in both QuickBooks and Stripe using the details from Airtable. Using If nodes, it intelligently checks if the customer exists. If a customer is not found in either platform, it creates a new one. This "find-or-create" logic prevents duplicate records. 3. Update Airtable with IDs: Once the customer IDs from both QuickBooks and Stripe are secured (either found or newly created), the workflow updates the original Airtable record with these new IDs for future reference. 4. Generate Financials: Stripe Payment Link: It sends an HTTP request to Stripe to create a unique, ready-to-use payment link for the specified amount. QuickBooks Invoice: It fetches your product list from QuickBooks, finds the matching item from the Airtable record, and generates a formal, detailed invoice. 5. Close the Loop: In the final step, the workflow updates the Airtable record one last time to: Add the QuickBooks Invoice #. Add the Stripe Payment Link. Change the Status to "Invoiced." Step-by-Step Setup Instructions This is an advanced workflow. Follow these setup steps carefully. 1. Connect Your Credentials Airtable: Create and connect a Personal Access Token with data.records:read and data.records:write scopes. QuickBooks: Connect your QuickBooks Online account using OAuth2 credentials. Stripe: Connect your Stripe account using your Secret Key. 2. Airtable Base Setup (Crucial) Your Airtable base must have a table with the following columns. The names must match exactly: Deal Name (Text) Client Name (Text) Client Email (Email) Status (Single-select with options: Draft, Approved for Invoicing, Invoiced) QuickBooks Customer ID (Text) Stripe Customer ID (Text) Stripe Payment Link (URL) QuickBooks Invoice # (Text) Stripe Price Id (Text - The API ID of your price in Stripe, e.g., price_123...) Quantity (Number) Quickbooks Product Name (Text) Created (Created Time) - This is used by the trigger. 3. Configure the n8n Nodes All Airtable Nodes: In each Airtable node, select your Base and Table from the dropdown lists. Get all Quickbook products (HTTP Request Node): You must replace {YOUR_QUICKBOOKS_COMPANY_ID} in the URL with your actual QuickBooks Company ID (also known as a Realm ID). 4. Activate the Workflow Save the workflow and toggle the Active switch to "on". The workflow will now trigger whenever the Created field is updated for a record in your Airtable base. Customization Guidance Changing the Trigger Status: If you use a different status than "Approved for Invoicing," simply update the value in the "IF - Status Check" node. Modifying Invoice Details: You can customize the Description or other line item details in the "Create an invoice" (QuickBooks) node by pulling more fields from your Airtable record. Adding Email Notifications: To notify a customer when their invoice is ready, add a Gmail or SendGrid node after the last Airtable Update node. You can include the Stripe Payment Link and a PDF of the QuickBooks invoice directly in the email. Advanced Error Handling: For a production environment, consider connecting the false output of the various IF nodes or using the .onError() workflow setting to send a Slack or email alert if a customer can't be found or an API call fails. Support For further support, or to develop a custom workflow, reach out to: Website: https://www.intuz.com/services Email: getstarted@intuz.com LinkedIn: https://www.linkedin.com/company/intuz Get Started: https://n8n.partnerlinks.io/intuz For Custom Worflow Automation Click here- Get Started

Overview This n8n template automates finding roofing contractors in any city using Google Maps. It deep-scrapes listings via ScrapeOps Proxy, deduplicates results against Google Sheets, saves fresh leads, and sends alerts via Gmail and Slack - all triggered from a simple web form. Who is this for? Roofing companies building local lead lists without manual research Sales teams prospecting contractors in new cities or regions Agencies running lead generation campaigns for home services clients Anyone who needs structured local business data from Google Maps What problem does it solve? Manually searching Google Maps, copying business details, and checking for duplicates is slow and error-prone. This workflow automates the entire process - from search to deduplication to saved leads - so you get fresh, structured contractor data with zero manual effort. How it works A web form captures the target city. ScrapeOps Proxy scrapes Google Maps for roofing contractors in that city. Each listing is deep-scraped for full details: phone, website, rating, reviews, and address. Results are compared against existing Google Sheet entries to remove duplicates. Only new leads are saved to the sheet. Gmail and Slack alerts notify you of new leads instantly. Set up steps (~10–15 minutes) Register for a free ScrapeOps API key: https://scrapeops.io/app/register/n8n Add ScrapeOps credentials in n8n. Docs: https://scrapeops.io/docs/n8n/overview/ Duplicate the Google Sheet template and connect it to the Read Previous Entries and Save New Leads nodes. Configure Gmail credentials in the Send Gmail Alert node and set your recipient. Configure Slack credentials in the Send Slack Alert node and set your channel. Open the form URL, enter a city, and run. Pre-conditions Active ScrapeOps account (free tier available): https://scrapeops.io/app/register/n8n ScrapeOps community node installed in n8n: https://scrapeops.io/docs/n8n/overview/ Google Sheets credentials configured in n8n Duplicated Google Sheet template with correct column headers Gmail credentials for alert emails Slack credentials for channel notifications Disclaimer This template uses ScrapeOps n8n integration as a community node. You are responsible for complying with Google's Terms of Use, robots.txt directives, and applicable laws in your jurisdiction. Scraping targets may change at any time; adjust render, scroll, and wait settings and parsers as needed. Use responsibly and only for legitimate business purposes.

Overview: Automated Occasion Wisher How it works Runs daily to check if today matches any birthday, anniversary, or special occasion in your Google Sheet AI Agent reads the sheet and returns a list of users having a special occasion to wish with details and a personalized wishing message If there is no one to wish, no email is sent. If there are multiple people to wish, multiple personalized emails are sent Setup steps Connect your Google Sheet containing columns as: Name, Occasion_Date, Email, Occasion_Type, Relationship, Personal_Note Insert the AI prompt ensuring strict JSON output (list format only) Configure the Email node for sending the final message Customization Edit AI prompt to change message tone, length, or emojis Add support for multiple reminder styles (e.g., early notification) Extend with logging, Slack alerts, or saving sent email history

This workflow automates the repair request process between tenants and building managers, keeping all updates organized in a single spreadsheet. It is composed of two coordinated workflows, as two separate triggers are required — one for new repair submissions and another for repair updates. A Unique Unit ID that corresponds to individual units is attributed to each request, and timestamps are used to coordinate repair updates with specific requests. General use cases include: Property managers** who manage multiple buildings or units. Building owners** looking to centralize tenant repair communication. Automation builders** who want to learn multi-trigger workflow design in n8n. ⚙️ How It Works Workflow 1 – New Repair Requests Behind the Scenes: A tenant fills out a Google Form (“Repair Request Form”), which automatically adds a new row to a linked Google Sheet. Steps: Trigger: Google Sheets rowAdded – runs when a new form entry appears. Extract & Format: Collects all relevant form data (address, unit, urgency, contacts). Generate Unit ID: Creates a standardized identifier (e.g., BUILDING-UNIT) for tracking. Email Notification: Sends the building manager a formatted email summarizing the repair details and including a link to a Repair Update Form (which activates Workflow 2). Workflow 2 – Repair Updates Behind the Scenes:\ Triggered when the building manager submits a follow-up form (“Repair Update Form”). Steps: Lookup by UUID: Uses the Unit ID from Workflow 1 to find the existing row in the Google Sheet. Conditional Logic: If photos are uploaded: Saves each image to a Google Drive folder, renames files consistently, and adds URLs to the sheet. If no photos: Skips the upload step and processes textual updates only. Merge & Update: Combines new data with existing repair info in the same spreadsheet row — enabling a full repair history in one place. 🧩 Requirements Google Account (for Forms, Sheets, and Drive) Gmail/email node connected for sending notifications n8n credentials configured for Google API access ⚡ Setup Instructions (see more detail in workflow) Import both workflows into n8n, then copy one into a second workflow. Change manual trigger in workflow 2 to a n8n Form node. Connect Google credentials to all nodes. Update spreadsheet and folder IDs in the corresponding nodes. Customize email text, sender name, and form links for your organization. Test each workflow with a sample repair request and a repair update submission. 🛠️ Customization Ideas Add Slack or Telegram notifications for urgent repairs. Auto-create folders per building or unit for photo uploads. Generate monthly repair summaries using Google Sheets triggers. Add an AI node to create summaries/extract relevant repair data from repair request that include long submissions.

This workflow creates a fully automated B2B lead generation & outreach pipeline. It combines BrowserAct (for scraping) with Google Gemini AI (for writing) to automate the entire prospecting process. It takes a search request via a Form, scrapes verified leads from Apollo.io, uses AI to write a personalized cold email for EACH lead, saves everything to Google Sheets, and notifies you via Gmail when the batch is done. How it works Form Trigger:** You input the Target Role (e.g., "Engineer") and Location (e.g., "New York"). BrowserAct Automation:** Triggers a remote browser to search Apollo.io and extract contact details (Name, Job, Company, Email). AI Email Drafter:* *Google Gemini** reads the lead's info and automatically generates a personalized cold email draft tailored to their role and company. Data Merging:** Seamlessly combines the scraped contact info with the AI-generated email content. Google Sheets Storage:** Appends the full profile + the AI email draft into your spreadsheet. Email Notification:* Sends you a summary report via *Gmail** listing who was scraped and confirming the job is finished. Set up steps BrowserAct Configuration Double-click the "Run a workflow" node and paste your specific BrowserAct Workflow ID. Google Sheets Setup Create a new Google Sheet. Crucial: Add these headers in the first row: id, name, email, job_title, profile_url, company, location, email_draft. Update the "Save to Google Sheets" node to select this file. Credentials BrowserAct Account Google Gemini (PaLM) API (for AI generation) Google Sheets (Service Account or OAuth2) Gmail (OAuth2 - for notifications)

This workflow is designed to automate the initial screening process for your User-Generated Content (UGC) campaigns. It instantly calculates a performance score for every candidate using AI, filters out low-scoring applicants, and immediately initiates outreach to the qualified talent. 🧩 What Problem Does It Solve? Hiring managers waste valuable time manually reviewing hundreds of applications against a complex, weighted rubric, which leads to delays in contacting the best candidates. This workflow solves these by: Instant, Unbiased Scoring:** It uses an AI Agent (Google Gemini) to instantly assign a score (0–10) based on specific criteria. Automatic Qualification:** It filters out unqualified candidates and automatically processes those who meet your minimum score requirement. Immediate Outreach:** It instantly sends acceptance emails to qualified candidates and notifies your internal HR team to follow up. Centralized Tracking:** It logs the candidate's data and their final AI score into a central Google Sheet for easy long-term tracking. 🛠️ How to Configure It 1.Jotform Setup: Connect your Jotform API credentials in n8n. Specify the ID of your candidate application form in the Jotform Trigger node. 2.AI Setup: Connect your Google Gemini API key. Review the scoring prompt in the AI Agent node and confirm that the point system matches your current campaign requirements. 3.Google Sheets Setup: Connect your Google Sheets API credentials. Replace the placeholder TEMPLATE_GOOGLE_SHEETS_DOCUMENT_ID with the actual ID of your candidate tracking spreadsheet. 4.Email Setup: Connect your Gmail API credentials. Replace the placeholder TEMPLATE_HR_EMAIL@yourcompany.com in the "Send Internal Notification (HR)" node with your team's correct contact email. ⚙️ How It Works 1.Application Received: The Jotform Trigger instantly fires when a candidate submits their form. 2.AI Scores Candidate: The AI Agent uses the criteria prompt to calculate a definitive numerical score for the applicant. 3.Qualification Check: The If node checks if the score is 6 or higher. 4.If True (qualified): The candidate proceeds to the next steps. 5.If False (unqualified): The workflow stops for this candidate (or can be configured to send a rejection). 6.Record & Notify: The workflow saves the data to the Google Sheet and then simultaneously sends two emails: an acceptance email to the candidate and an internal notification to HR. 🎯 Perfect For UGC Campaigns:** Instantly qualify content creators for product reviews, endorsements, and social media ads based on objective, pre-defined rules. Influencer Marketing:** Automatically filter and prioritize micro- and nano-influencers who match all your specific demographic and product criteria. Mass Screening:** Use the AI to quickly narrow down a large pool of applicants, saving your recruiting team hours of manual data review and scoring. If you need any help Get in Touch

Overview This n8n template automates finding real estate agents in any city using Google Maps. It deep-scrapes listings via ScrapeOps Proxy, deduplicates results against Google Sheets, saves fresh leads, and sends alerts via Gmail and Slack — all triggered from a simple web form. Who is this for? Real estate marketing agencies building targeted agent lead lists PropTech companies prospecting realtors in new cities or regions Sales teams running outreach campaigns targeting real estate agencies Anyone who needs structured local real estate agent data from Google Maps What problem does it solve? Manually searching Google Maps for real estate agents, copying contact details, and checking for duplicates is slow and inconsistent. This workflow automates the entire process — from search to deduplication to saved leads — so you get fresh, structured agent data with zero manual effort. How it works A web form captures the target city. ScrapeOps Proxy scrapes Google Maps for real estate agents in that city. Each listing is deep-scraped for full details: phone, website, rating, reviews, and address. Results are compared against existing Google Sheet entries to remove duplicates. Only new leads are saved to the sheet. Gmail and Slack alerts notify you of new leads instantly. Set up steps (~10–15 minutes) Register for a free ScrapeOps API key: https://scrapeops.io/app/register/n8n Add ScrapeOps credentials in n8n. Docs: https://scrapeops.io/docs/n8n/overview/ Duplicate the Google Sheet template and connect it to the Read Previous Entries and Save New Leads nodes. Configure Gmail credentials in the Send Gmail Alert node and set your recipient. Configure Slack credentials in the Send Slack Alert node and set your channel. Open the form URL, enter a city, and run. Pre-conditions Active ScrapeOps account (free tier available): https://scrapeops.io/app/register/n8n ScrapeOps community node installed in n8n: https://scrapeops.io/docs/n8n/overview/ Google Sheets credentials configured in n8n Duplicated Google Sheet template with correct column headers Gmail credentials for alert emails Slack credentials for channel notifications Disclaimer This template uses ScrapeOps as a community node. You are responsible for complying with Google's Terms of Use, robots.txt directives, and applicable laws in your jurisdiction. Scraping targets may change at any time; adjust render, scroll, and wait settings and parsers as needed. Use responsibly and only for legitimate business purposes.

Who’s it for Teams that capture leads with Typeform and want a plug-and-play flow to validate emails, enrich profiles in Vero, send a Gmail welcome, and log activity to Google Sheets with a Slack heads-up. Ideal for growth, sales, and marketing ops. What it does / How it works When a Typeform response arrives, the workflow: Validates the email format. Maps answers into a clean contact object. Upserts the contact in Vero (email as ID). Checks a qualification score; if qualified, sends a personalized Gmail welcome. Logs the outcome (timestamp, contact, score, status, action) to Google Sheets. Notifies Slack with a concise summary. Optional branches log and/or notify on invalid email or low score. How to set up In Configuration (Set), fill placeholders: typeformFormId, qualificationScore, slackChannel, sheetId, sheetName, gmailFrom, gmailSubject, sourceTag. Connect credentials for Typeform, Vero, Gmail, Google Sheets, Slack. Map your Typeform fields (email, name, company, score, consent) if labels differ. Requirements Active accounts: Typeform, Vero, Gmail, Google Sheets, Slack. Do not hardcode secrets in HTTP or Code nodes; use n8n credentials. Replace any sample IDs/emails/channels with your own. Customize the workflow Tune qualificationScore. Edit the Gmail template (subject/body variables). Add more attributes to the Vero upsert. Expand logging columns in Sheets. Split Slack notifications (e.g., triage channel for invalid/low-score leads).

What this template does Transforms provider documentation (URLs) into an auditable, enforceable multicloud security control baseline. It: Fetches and sanitizes HTML Uses AI to extract security requirements (strict 3-line TXT blocks) Composes enforceable controls** (strict 7-line TXT blocks with true-equivalence consolidation) Builds the final baseline* (TXT or JSON, see *Outputs) with a Technology: header Returns a downloadable artifact via webhook and can append/create the file in Google Drive Why it’s useful Eliminates manual copy-paste and produces a consistent, portable baseline ready for review, audit, or enforcement tooling—ideal for rapidly generating or refreshing baselines across cloud providers and services. Multicloud support The workflow is multicloud by design. Provide the target cloud in the request and run the same pipeline for: AWS, **Azure, GCP (out of the box) Extensible to other providers/services by adjusting prompts and routing logic How it works (high level) POST /create (Basic Auth) with { cloudProvider, technology, urls[] } Input validation → generate uuid → resolve Google Drive folder (search-or-create) Download & sanitize each URL AI pipeline: Extractor → Composer → Baseline Builder → (optional) Baseline Auditor Append/create file in Drive and return a downloadable artifact (TXT/JSON) via webhook Request (webhook) Method: POST URL: https://<your-n8n>/webhook/create Auth: Basic Auth Headers: Content-Type: application/json Example input (Postman/CLI) { "cloudProvider": "aws", "technology": "Amazon S3", "urls": [ "https://docs.aws.amazon.com/AmazonS3/latest/userguide/security-best-practices.html", "https://www.trendmicro.com/cloudoneconformity/knowledge-base/aws/S3/", "https://repost.aws/knowledge-center/secure-s3-resources" ] } Field reference cloudProvider (string, required) — case-insensitive. Supported: aws, azure, gcp. technology (string, required) — e.g., "Amazon S3", "Azure Storage", "Google Cloud Storage". urls (string\[], required) — 1–20 http(s) URLs (official/reputable docs). Optional (Google Drive destination): gdriveTargetId (string) — Google Drive folderId used for append/create. gdrivePath (string) — Path like "DefySec/Baselines" (folders are created if missing). gdriveTargetName (string) — Folder name to find/create under root. Optional (Assistant overrides): assistantExtractorId, assistantComposerId, assistantBaselineId, assistantAuditorId (strings) Resolution precedence Drive: gdriveTargetId → gdrivePath → gdriveTargetName → default folder. Assistants: explicit IDs above → dynamic resolution by name (expects 1_DefySec_Extractor, 2_DefySec_Control_Composer, 3_DefySec Baseline Builder, 4_DefySec_Baseline_Auditor). Validation Rejects empty urls or non-http(s) schemes; normalizes cloudProvider to aws|azure|gcp. Sanitizes fetched HTML (removes scripts/styles/headers) before AI steps. Outputs Primary:* downloadable *TXT** file controls_<technology>_<timestamp>.txt (via webhook). Composer outcomes:** if no groups to consolidate → NO_CONTROLS_TO_BE_CONSOLIDATED; if nothing valid remains → NO_CONTROLS_FOUND.  JSON path:* when the Builder stage is configured for *JSON-only** output (strict schema), the workflow returns a .json artifact and the Auditor validates it (see next section).  Techniques used (from the built-in assistants) Provider-aware extraction with strict TXT contract (3 lines):* Extractor limits itself to the declared provider/technology, outputs only Description/Reference/SecurityObjective, and applies a *reflexive quality check** before emitting.  Normalization & strict header parsing:** Composer normalizes whitespace/fences, requires the CloudProvider/Technology header, and ignores anything outside the exact 3-line block shape.  True-equivalence grouping & consolidation:* Composer groups *only** when intent, enforcement locus/mechanism, scope, and mode/setting all match—otherwise items remain distinct.  7-line enforceable control format:* Composer renders each (consolidated or unique) control in *exactly seven labeled lines** to keep results auditable and automatable.  Builder with JSON-only schema & technology inference:* Builder parses 7-line blocks, infers technology, consolidates true equivalents again if needed, and returns *pure JSON** matching a canonical schema (with counters in meta).  Self-evaluation loop (Auditor):* Auditor *unwraps transport, validates **schema & content, checks provider terminology/scope/automation, and returns either GOOD_ENOUGH or a JSON instruction set for the Builder to fix and re-emit—enabling reflective improvement.  Reference prioritization:** Across stages, official provider documentation is preferred in References (AWS/Azure/GCP).  Customization & extensions Prompt-reflective techniques:** keep (or extend) the Auditor loop to add more review passes and quality gates.  Compliance assistants:* add assistants to analyze/label controls for *HIPAA, PCI DSS, SOX** (and others), emitting mappings, gaps, and remediation notes. Implementation context:* feed internal implementation docs, runbooks, or *Architecture Decision Records (ADRs); use these as **grounding to generate or refine controls (works with local/self-hosted LLMs, too). Local/self-hosted LLMs:** swap OpenAI nodes for your on-prem LLM endpoint while keeping the pipeline. Provider-specific outputs:** extend the final stage to export Policy-as-Code or IaC snippets (Rego/Sentinel, CloudFormation Guard, Bicep/ARM, Terraform validations). Assistant configuration & prompts Full assistant configurations and prompts (Extractor, Composer, Baseline Builder, Baseline Auditor) are available here: https://github.com/followdrabbit/n8nlabs/tree/main/Lab03%20-%20Multicloud%20AI%20Security%20Control%20Baseline%20Builder/Assistants Security & privacy No hardcoded secrets in HTTP nodes; use n8n’s Credential Manager. Drive operations are optional and folder-scoped. For sensitive environments, switch to a local LLM and provide only sanitized/approved inputs. Quick test (curl) curl -X POST "https://<your-n8n>/webhook/create" \ -u "<user>:<pass>" \ -H "Content-Type: application/json" \ -d '{ "cloudProvider":"aws", "technology":"Amazon S3", "urls":[ "https://docs.aws.amazon.com/AmazonS3/latest/userguide/security-best-practices.html" ] }' \ -OJ