by WeblineIndia
AI-Powered Email Monitoring & Compliance Risk Detection > Gmail + Gemini + Google Sheets This workflow automatically monitors incoming Gmail messages, analyzes them using Google Gemini AI for compliance risks (fraud, phishing, data leaks), filters high-confidence threats, logs incidents securely in Google Sheets and sends alert emails to your security team. Quick Implementation Steps Connect your Gmail and Google Sheets accounts. Add your Google Gemini API credentials. Set the Gmail node to monitor your desired inbox. Create a Google Sheet with required columns: Incident_Hash Incident_Time Risk_Type Risk_Confidence Replace the alert email in the final Gmail node. Activate the workflow. That’s it — your AI-powered compliance monitoring system is live! What It Does This workflow acts as an intelligent email security and compliance monitoring system. It continuously scans incoming emails and uses AI to detect potential risks such as fraud attempts, phishing emails or sensitive data leaks. When an email arrives, the system extracts clean text by removing HTML clutter, signatures and hidden elements. This ensures that only relevant content is sent to the AI model, improving both accuracy and cost efficiency. The workflow then leverages Google Gemini to analyze the email in its original language, eliminating the need for translation. The AI returns a structured JSON response including risk type, severity level, confidence score and reasoning. To ensure reliability, a custom code node safely parses the AI output using regex and error handling. Based on the detected risk level, the workflow routes the email, filters out low-confidence alerts, logs incidents securely and sends formatted alerts to your compliance or security team. Who It's For Compliance teams monitoring sensitive communications Security teams handling phishing and fraud detection Enterprises managing high-volume email workflows Customer support teams dealing with external communications Organizations requiring audit trails for regulatory compliance Requirements To use this workflow, you need: n8n account (Cloud or Self-hosted) Google account with: Gmail access Google Sheets access Google Gemini API credentials A Google Sheet for logging incidents Basic understanding of n8n workflows How It Works & How To Set Up 1. Setup Credentials Connect Gmail OAuth2 in n8n Connect Google Sheets OAuth2 Add Google Gemini API credentials 2. Configure Gmail Trigger Node: Catch Incoming Emails Operation: getAll Set filters if needed (label, inbox, etc.) 3. Clean Email Content Node: Strip Email Formatting Extracts <body> content from HTML Outputs clean text as clean_body 4. AI Risk Analysis Node: Analyze Compliance Risk Uses Google Gemini to analyze: Subject Email body Returns structured JSON: { "risk_type": "", "risk_level": "", "confidence": 0, "reason": "" } 5. Safe Parsing (Critical Step) Node: Clean & Parse AI Output Uses: Regex to extract JSON try/catch for error handling Prevents workflow failure if AI output is malformed 6. Prepare Variables Node: Prep Variables for Routing Extracts: risk_type risk_level confidence reason 7. Route Based on Risk Node: Route by Risk Level Splits into: High Medium Low 8. Filter False Positives Node: Block Low-Confidence Alerts Condition: confidence > 80 Ensures only high-confidence threats proceed 9. Generate Secure Incident ID Node: Generate Secure Incident ID Uses SHA256 hash of: Sender email Timestamp Masks sensitive data (PII) 10. Log to Google Sheets Node: Save to Audit Log Appends data: Incident_Hash Incident_Time Risk_Type Risk_Confidence 11. Format Report Node: Format AI Report Converts AI reasoning (Markdown → HTML) 12. Send Alert Node: Send Security Alert Sends styled HTML email to your team Replace: REPLACE_WITH_YOUR_EMAIL How To Customize Nodes Adjust AI Prompt Modify the prompt in Analyze Compliance Risk Add custom risk categories or rules Change Confidence Threshold Update filter node (default: > 80) Lower for aggressive detection, higher for stricter filtering Customize Alert Email Edit HTML in Send Security Alert Add branding, logos or additional data Modify Logging Fields Extend Google Sheets columns Add fields like: Sender Subject Department Add-Ons (Extend Functionality) Slack / Microsoft Teams alerts instead of email Dashboard using Power BI or Looker Studio Auto-response to suspicious emails Integration with SIEM tools Store historical data for ML-based trend analysis Use Case Examples Detect phishing emails targeting employees Monitor customer support inbox for fraud attempts Identify accidental data leaks in outgoing communications Automate compliance monitoring for regulated industries Flag suspicious vendor or financial emails And many more use cases depending on your business needs. Troubleshooting Guide | Issue | Possible Cause | Solution | |------|--------------|---------| | No emails detected | Gmail trigger not configured | Check Gmail credentials and filters | | AI output parsing fails | Invalid JSON from AI | Verify Code node logic and prompt format | | Alerts not sent | Email not configured | Replace recipient email in final node | | No data in Google Sheets | Sheet mapping incorrect | Verify document ID and column names | | Too many false alerts | Low confidence threshold | Increase threshold above 80 | | Workflow crashes | Missing credentials | Reconnect all services | Need Help? If you need help setting up this workflow, customizing nodes or building advanced process automation solutions: Reach out to our n8n workflow developers at WeblineIndia / Global We can help you with: Custom workflow development AI-powered automation solutions Integration with enterprise tools Scaling and optimization Let us help you turn automation into a competitive advantage
by Kumar SmartFlow Craft
🚀 How it works Handles GDPR Article 15 (access) and Article 17 (erasure) requests end-to-end — from inbound email to legally-compliant response — with zero manual intervention and a full audit trail. 📬 Monitors Gmail inbox for incoming data subject requests 🤖 AI Agent classifies the request (access or erasure), extracts the requester email and data subject email with structured JSON output 🗄️ Queries Supabase for all personal data records matching the subject 📋 Queries Airtable CRM for matching contact records 📝 Second AI Agent compiles all found data into a GDPR-compliant HTML report ✉️ Access requests — sends a full data report to the requester 🗑️ Erasure requests — deletes records from both Supabase and Airtable, then sends a deletion confirmation 🔒 Logs every request to Google Sheets with timestamp for your audit trail 🛠️ Set up steps Estimated setup time: ~20 minutes Gmail Trigger — connect Gmail OAuth2; point it at your DSR inbox OpenAI — connect OpenAI API credential (used by both AI Agent nodes) Supabase — connect Supabase API credential; update the table name from users to match your schema Airtable — connect Airtable Personal Access Token; replace YOUR_BASE_ID and YOUR_TABLE_NAME Google Sheets — connect Google Sheets OAuth2; replace YOUR_AUDIT_SHEET_ID; create a tab named DSR Audit Log Follow the sticky notes inside the workflow for per-node guidance 📋 Prerequisites Gmail account receiving GDPR requests OpenAI API key (GPT-4o) Supabase project with a users/contacts table Airtable base with a Contacts table containing an Email field Google Sheets for audit log Custom Workflow Request with Personal Dashboard kumar@smartflowcraft.com https://www.smartflowcraft.com/contact More free templates https://www.smartflowcraft.com/n8n-templates
by sato rio
This workflow automates the initial screening process for new job applications, freeing up your recruitment team to focus on qualified candidates. It receives applications from a webhook, uses OpenAI (GPT-4) to analyze resumes for skill and culture fit, generates interview questions, logs the results to Google Sheets, sends interview invitations via Gmail, and notifies your team on Slack. 🚀 Who is this for? HR and Recruitment Teams** looking to automate repetitive screening tasks. Hiring Managers** who want a consistent, data-driven first pass on applicants. Startups and SMBs** aiming to build an efficient, scalable hiring pipeline without a large HR team. 💡 How it works Receive Application: The workflow triggers when a new application is submitted via a webhook from your job board or application form. Extract & Analyze: It downloads the resume/CV, extracts the text, and sends it to OpenAI (GPT-4) with a custom prompt. Score & Generate: The AI scores the candidate on skill match and culture fit, provides a summary, and generates tailored interview questions based on their experience. Log Data: The evaluation scores, AI summary, and candidate information are appended to a new row in a Google Sheet for tracking. Schedule Interview: A personalized email is sent to the candidate via Gmail with a link to schedule their interview. Notify Team: A summary card with the AI evaluation and links to the full report is posted in a Slack channel to keep the hiring team informed. ⚙️ How to set up Configure Credentials: Set up your credentials for OpenAI, Google (for both Sheets and Gmail), and Slack in n8n. Webhook URL: Copy the "Production URL" from the "Webhook: New Application" node and set it as the destination in your job board's webhook settings (e.g., Greenhouse, Lever, Ashby, or a web form). Google Sheet: Create a Google Sheet to track applicants. Update the "G Sheets: Save Evaluation" node with your Spreadsheet ID and Sheet Name. Ensure the columns in your sheet match the data you want to save. Customize Prompts & Email: Modify the prompts in the two OpenAI nodes to match your company's values and the specific job requirements. Update the Gmail node with your email content and the logic for your scheduling link (e.g., Calendly, SavvyCal). 📋 Requirements An n8n instance (Cloud or self-hosted). An OpenAI API key. A Google account for Google Sheets and Gmail. A Slack workspace. A job application source capable of sending webhooks.
by Cheng Siong Chin
How It Works This workflow automates financial reconciliation by orchestrating multiple AI agents to detect mismatches, analyze root causes, and apply corrections across bank statements, invoices, and e-commerce platforms. Designed for finance teams, accountants, and business owners managing high transaction volumes, it eliminates manual reconciliation tedious work that typically consumes hours weekly. The system retrieves financial data from Stripe, banking APIs, and e-commerce platforms, then feeds it to specialized AI agents: one detects discrepancies using pattern recognition, another performs root cause analysis, and a third generates ledger corrections. An orchestrator agent coordinates these specialists, ensuring systematic processing. Results are logged to Google Sheets and trigger email notifications for critical issues, creating an audit trail while reducing reconciliation time from hours to minutes with 95%+ accuracy. Setup Steps Configure Stripe API credentials in "Get Stripe Transactions" node Add banking API authentication for "Get Bank Feed Data" node Connect e-commerce platform (Shopify/WooCommerce) credentials Input NVIDIA API key for all OpenAI Model nodes Set OpenAI API key in Orchestrator Agent Configure Gmail credentials for notification node Prerequisites NVIDIA API access, OpenAI API key, Stripe account Use Cases Monthly financial close automation, daily transaction reconciliation Customization Modify detection thresholds, add custom financial data sources Benefits Reduces reconciliation time by 90%, eliminates manual data entry errors
by WeblineIndia
Portfolio Exposure Risk Summary Generator > n8n + Google Sheets + Gemini + Slack + Gmail This workflow automatically analyzes portfolio data from Google Sheets on a scheduled basis, calculates exposure metrics such as sector allocation and concentration and generates a professional risk summary using Google Gemini. The report is then sent via email, shared on Slack and logged for historical tracking. Quick Implementation Steps Connect your Google Sheets portfolio data Add Gemini API credentials Configure Gmail and Slack nodes Set schedule trigger timing Run once to verify output and logging What It Does This workflow performs a complete portfolio risk analysis pipeline. It starts by fetching portfolio data from a Google Sheet and validating whether the required data exists. If valid data is present, it calculates key exposure metrics such as total portfolio value, sector allocation and concentration levels using a Code node. These calculated metrics are then passed to an AI model (Google Gemini), which generates a concise and professional risk summary. The workflow ensures the output is structured properly before preparing a final report. The final output is distributed through multiple channels: an email report, a Slack notification and a log entry in Google Sheets. If no portfolio data is available, the workflow gracefully handles the scenario by generating a fallback report and logging it. Who It's For Financial analysts monitoring portfolio risk Investment advisors managing client portfolios Business owners tracking asset exposure Automation enthusiasts building financial workflows Requirements to Use This Workflow n8n account (cloud or self-hosted) Google Sheets with portfolio data Google Gemini API credentials Gmail account connected in n8n Slack workspace connected in n8n How It Works & Setup Guide Step 1: Schedule Trigger Configure the "Schedule Risk Review" node Default: Weekly run (Monday at 9 AM) Step 2: Connect Portfolio Data Use "Read Portfolio From Sheet" node Ensure sheet contains columns like: Asset Name Sector Quantity Price Market Value (optional) Step 3: Validate Data "Check Portfolio Data Exists" ensures valid entries exist If no data → fallback branch executes Step 4: Calculate Exposure Metrics Code node calculates: Total portfolio value Sector exposure and percentages Top holding concentration Top 3 holdings Step 5: Generate AI Risk Summary "Generate Risk Summary" uses Gemini model Input includes calculated metrics Output is structured JSON with risk summary Step 6: Parse AI Output "Parse Risk Summary" ensures valid JSON output Handles fallback parsing if needed Step 7: Prepare Final Report "Prepare Risk Report Data" formats final fields: Total value Top sector and exposure Top holding and concentration Risk summary Run date and ID Step 8: Deliver Report Email sent via Gmail node Slack message posted Data logged in Google Sheets Step 9: Fallback Handling If no portfolio data exists: Default summary is generated Logged to sheet for consistency How To Customize Nodes Modify schedule timing in Schedule node Update Google Sheet structure as per your data Adjust Code node logic for additional metrics Customize AI prompt for different analysis styles Change email/Slack message formatting Add‑ons Add risk scoring system (low/medium/high) Integrate historical trend analysis Add client-specific reporting Include asset-level risk breakdown Connect dashboards (e.g., Google Data Studio) Use Case Examples Weekly portfolio risk monitoring Client portfolio reporting for advisors Internal investment review automation Risk alerts for concentrated holdings Portfolio diversification analysis Troubleshooting Guide | Issue | Possible Cause | Solution | | --------------------------- | ------------------------- | ----------------------------------- | | No data processed | Empty Google Sheet | Ensure portfolio data exists | | AI output not parsed | Invalid JSON response | Check prompt format or parsing node | | Email not sent | Gmail credentials missing | Reconnect Gmail account | | Slack message not delivered | Incorrect channel setup | Verify Slack channel ID | | Incorrect calculations | Missing numeric values | Validate sheet data types | Need Help? If you need assistance setting up this workflow, customizing it for your business or building advanced automation solutions, feel free to reach out to our n8n automation developers at WeblineIndia / Global. Our team specializes in building scalable and production-ready automation workflows tailored to your needs. We can help you extend this workflow with advanced analytics, dashboards, integrations and enterprise-grade solutions.
by Milos Vranes
Quick overview This workflow receives web form submissions via webhook, uses OpenAI to score and classify each lead, then emails hot leads through Gmail and logs them to separate Google Sheets tabs for hot versus cold review. How it works Receives a POST webhook request containing lead details (name, email, company, role, message). Normalizes the incoming fields and adds a timestamp. Sends the lead details to OpenAI Chat Completions to return a JSON score (1–10), intent label, and one-sentence rationale. Parses and validates the AI JSON output and merges it back into the lead record. If the score is 7 or higher, sends a Gmail alert and appends the lead to the “Hot Leads” tab in Google Sheets. If the score is below 7, appends the lead to the “Cold Review” tab in Google Sheets. Responds to the webhook caller with a JSON payload including ok, score, and intent. Setup Add an OpenAI API key (used via HTTP Header Auth) and ensure the Authorization header is set for requests to https://api.openai.com/v1/chat/completions. Connect a Gmail OAuth2 credential and set the recipient email (update the workflow variable alertInbox or replace the default you@example.com). Create a Google Sheet with two tabs named exactly “Hot Leads” and “Cold Review”, add the expected header columns, and replace REPLACE_WITH_YOUR_SHEET_ID in both Google Sheets nodes. Activate the workflow, copy the production webhook URL for the lead-qualifier endpoint, and configure your form tool to POST submissions to it as JSON.
by Yassin Zehar
Description Automatically triage Product UAT feedback using AI, route it to the right tools and teams, and close the feedback loop with testers, all in one workflow. This workflow analyzes raw UAT feedback, classifies it (critical bug, feature request, UX improvement, or noise), validates AI confidence, escalates when human review is needed, and synchronizes everything across Jira, Slack, Notion, Google Sheets, and email. Context Product teams often receive unstructured UAT feedback from multiple sources (forms, Slack, internal tools), making triage slow, inconsistent, and error-prone. This workflow ensures: Faster bug detection Consistent categorization Zero feedback lost Clear accountability between Product, Engineering, and Design It combines AI automation with human-in-the-loop control, making it safe for real production environments. Who is this for? Product Managers running UAT or beta programs Project Managers coordinating QA and release validation Product Ops / PMO teams Engineering teams who want faster, cleaner bug escalation Any team managing high-volume UAT feedback Perfect for teams that want speed without sacrificing control. Requirements Webhook trigger (form, internal tool, Slack integration, etc.) OpenAI account (for AI triage) Jira (bug tracking) Slack (team notifications) Notion (product roadmap / UX backlog) Google Sheets (UAT feedback log) Gmail (tester & manual review notifications) How it works Trigger The workflow starts when UAT feedback is submitted via a webhook (form, Slack, or internal tool). Normalize & Clean Incoming data is normalized into a consistent structure (tester, build, page, message) and cleaned to be AI-ready. AI Triage An AI model analyzes the feedback and returns: Type (Critical Bug, Feature Request, UX Improvement, Noise) Severity & sentiment Summary and suggested title Confidence score Quality Control If the AI output is unreliable (low confidence or parsing error), the feedback is automatically routed to manual review via email and Slack. Routing & Actions If confidence is sufficient: Critical Bugs → Jira issue + Engineering Slack alert Feature Requests → Notion roadmap UX Improvements → Design / UX tracking Noise → Archived but traceable Closed Loop The tester is notified via Slack or email, and the workflow responds to the original webhook with a structured status payload. What you get One unified UAT triage system Faster bug escalation Clean product and UX backlogs Full traceability of every feedback Automatic tester communication Safe AI usage with human fallback About me : I’m Yassin a Product Manager Scaling tech products with a data-driven mindset. 📬 Feel free to connect with me on Linkedin
by Cheng Siong Chin
How It Works This workflow automates continuous data integrity monitoring and intelligent alert management across multiple data sources. Designed for data engineers, IT operations teams, and business intelligence analysts, it solves the critical challenge of detecting data anomalies and orchestrating appropriate responses based on severity levels. The system operates on scheduled intervals, fetching data from software metrics APIs and BI dashboards, then merging these sources for comprehensive analysis. It employs AI-powered validation and orchestration agents to detect anomalies, assess severity, and determine optimal response strategies. The workflow intelligently routes alerts based on severity classification, triggering critical notifications via email and Slack for high-priority issues while sending standard reports for routine findings. By maintaining detailed compliance audit logs and preparing executive summaries, it ensures stakeholders receive timely, actionable intelligence while creating audit trails for data quality monitoring initiatives. Setup Steps Configure Schedule Data Integrity Check trigger with monitoring frequency Connect Workflow Configuration node with data source parameters Set up Fetch Software Metrics and Fetch BI Dashboard Data nodes with respective API credentials Configure Merge Data Sources node for data consolidation logic Connect Data Validation Agent with OpenAI/Nvidia API credentials for anomaly detection Set up Orchestration Agent with AI API credentials for severity assessment Configure Check for Anomalies node with routing conditions Connect Route by Severity node with classification logic Prerequisites OpenAI or Nvidia API credentials for AI-powered analysis, API access to software metrics platforms Use Cases SaaS platforms monitoring service health metrics, e-commerce businesses tracking inventory data quality Customization Adjust scheduling frequency for monitoring intervals, modify severity thresholds for alert classification Benefits Reduces mean time to detection by 75%, eliminates manual data quality checks
by Avkash Kakdiya
How it works This workflow automatically creates a weekly report of tasks. Every Friday morning, it collects all task details from Airtable, checks progress, and prepares a summary. It also highlights important or late tasks and sends the report to Slack, email, and saves it for record. Step-by-step Trigger & fetch** Schedule: Every Friday 9AM – Triggers the workflow automatically every Friday at 9 AM. Airtable: Fetch This Week – Collects all task records from the Airtable base for the current week. Analysis & formatting** Code: Analyze & Format – Checks all tasks, detects fields, calculates completion rate, identifies overdue and urgent items, and builds the full Slack message with an {{AI_SUMMARY}} placeholder. AI summary generation** OpenAI: Generate AI Summary – Sends the weekly stats to GPT-4.1-mini with a structured prompt to produce a concise 2–3 sentence plain-English project manager summary. Merge & prepare** Code: Merge AI Summary – Injects the AI summary into the Slack message and prepares urgent alert messages for overdue or high-priority tasks. Parallel output actions** Slack: Post Weekly Digest – Posts the full formatted digest to a Slack channel with mrkdwn formatting. Gmail: Send Digest Email – Sends an HTML-formatted email with stats cards, AI summary, and a task table. Google Sheets: Log Weekly Stats – Appends week range, totals, completion rate, overdue count, AI summary, and status to a tracking sheet. Conditional urgent alert** IF: Has Urgent or Overdue? – Checks if overdue or urgent task count is greater than zero. Slack: DM Urgent Alert – Sends a separate urgent action-required message to Slack if flagged items exist. Gmail: Send Urgent Alert – Sends a red-header alert email listing overdue and urgent counts if flagged items exist. Why use this? Eliminates manual weekly reporting by automatically collecting, analyzing, and summarizing all Airtable task data Keeps the entire team informed across Slack and Email every Friday without lifting a finger AI-generated summaries give instant clarity on project health and what needs attention Logs every weekly digest to Google Sheets for long-term trend tracking and reporting Sends a separate urgent alert so critical or overdue tasks never get buried in the digest
by WeblineIndia
Commodity Portfolio Tracker using n8n, Google Sheets, Gemini AI & Gmail Alerts This workflow automatically monitors a commodity portfolio stored in Google Sheets, compares actual allocation against predefined targets, detects deviations and sends intelligent rebalance alerts via email using Gemini AI. It also logs every run (success, failure or no action) into a tracking sheet for audit purposes. Quick Implementation Steps Connect Google Sheets, Gmail and Gemini credentials in your n8n account Add holdings data in Google Sheets Configure targets in "Workflow Settings" node Create rebalance_log sheet with required columns Test workflow → Activate schedule What It Does This workflow acts as an automated portfolio monitoring system specifically designed for commodity-based investments such as Gold, Silver, Oil, Copper and Natural Gas. It reads portfolio holdings using the Read Holdings node and combines them with configuration from the Workflow Settings node. The workflow validates data through Validate Portfolio Data, calculates allocation via Calculate Portfolio Allocation and identifies deviations using Detect Portfolio Drift. If deviations exceed limits, Classify Alert Severity determines how critical the situation is. Finally, Build Alert Prompt and Generate Alert Message (Gemini AI) create a human-readable alert, which is processed in Prepare Alert Payload, sent via Send Rebalance Email and logged using Log Sent Alert, Log Validation Failure or Log No Action depending on the outcome. Who It's For Financial advisors managing client portfolios Individual investors tracking commodity allocations Portfolio managers looking for automation FinTech developers building advisory tools Anyone who wants rule-based rebalancing alerts Requirements n8n account (cloud or self-hosted) Google Sheets account (for holdings + logs) Gmail account (for sending alerts) Google Gemini API credentials Basic understanding of n8n nodes and workflows How It Works & Setup Instructions Step 1: Prepare Google Sheets Create two sheets: Holdings Sheet Columns example: asset, units, price, current_value, last_updated Log Sheet (rebalance_log) Columns: run_date,total_value,rebalance_needed,severity,affected_assets,alert_sent,summary,reason_skipped Step 2: Configure Workflow Settings Node Update values inside Workflow Settings node: Target allocation (must sum to 100) Min/Max ranges Alert email Severity thresholds Currency Step 3: Connect Credentials Google Sheets → used in Read Holdings, Log Sent Alert, Log Validation Failure, Log No Action Gmail → used in Send Rebalance Email Gemini → used in Generate Alert Message Step 4: Workflow Execution Flow (Node-by-Node) Schedule Trigger starts the workflow Read Holdings fetches portfolio data Workflow Settings provides configuration Synchronize Inputs merges both sources Prepare Portfolio Context structures the data Validate Portfolio Data ensures correctness Check Validation Status routes valid/invalid data Calculate Portfolio Allocation computes percentages Detect Portfolio Drift identifies deviations Check Rebalance Requirement decides action path Classify Alert Severity assigns severity level Build Alert Prompt prepares AI input Generate Alert Message creates final message Merge Alert Data combines AI + data Prepare Alert Payload formats output Send Rebalance Email sends alert Log Sent Alert / Log No Action / Log Validation Failure store results How To Customize Nodes Workflow Settings**: Change targets, thresholds, email Schedule Trigger**: Modify frequency (hourly/daily/weekly) Gemini Node**: Adjust tone of alert messages Email Node**: Add CC/BCC or change format Code Nodes**: Customize calculation logic (e.g., percentage vs amount-based rebalancing) Add-ons Slack integration for high severity alerts Dashboard visualization using Google Data Studio Multi-client portfolio support Real-time price API integration (NSE, Alpha Vantage, etc.) Risk scoring system for portfolios Use Case Examples Daily monitoring of commodity portfolios Automated advisory alerts for wealth managers DIY investor portfolio tracking system Risk management for diversified assets Audit trail for compliance and reporting There can be many more variations of this workflow depending on business needs. Troubleshooting Guide | Issue | Possible Cause | Solution | | ----------------------- | ----------------------- | ----------------------------------------------- | | No columns found | Sheet missing headers | Add header row in first row | | Undefined values in log | Wrong node connection | Connect from payload node instead of email node | | Email not sent | Gmail credentials issue | Reconnect Gmail account | | AI output empty | Prompt or API issue | Check Gemini node input | | Validation failed | Incorrect data format | Fix holdings sheet values | Need Help If you need assistance setting up this workflow, customizing features or building automation solutions, feel free to reach out to our n8n experts at WeblineIndia. We can help you: Customize workflows for your business Integrate advanced AI capabilities Build scalable automation systems Develop end-to-end FinTech solutions Get in touch to turn your ideas into production-ready workflows.
by WeblineIndia
Zoho CRM – Deal Health Predictor with AI Scoring This n8n automation monitors open Zoho CRM Deals every week, identifies stalled opportunities, scores their health using Google Gemini AI and triggers sales intervention by emailing the deal owner and creating a high-priority task in Zoho CRM — before the deal goes cold. Quick Start — Implementation in 6 Steps Import workflow into your n8n instance. Connect Zoho OAuth2 credential in all Zoho nodes. Connect Gmail OAuth2 account for outbound alerts. Confirm stage names & inactivity thresholds match your CRM. Test with sample deals before scheduling. Activate the workflow once validated by your sales team. What It Does This workflow dynamically analyzes every open sales deal retrieved from Zoho CRM. It calculates key metrics per deal such as inactivity duration, stage aging and deal age to understand whether the opportunity has stalled. Only deals with significant inactivity move forward to AI scoring. Using Google Gemini, each deal receives a Health Score (0–100), along with a risk level, reasons and recommended next actions. If a deal is considered “At-Risk,” the system automatically: Sends an alert email to the assigned sales rep Creates a high-priority Task in Zoho CRM linked to that deal It ensures timely sales intervention without needing manual checks. Who’s It For Sales teams using Zoho CRM RevOps & Sales Managers monitoring deal movement Teams wanting data-backed alerts for slow-moving deals Businesses wanting proactive pipeline management with AI Requirements | Requirement | Why | |------------|-----| | n8n instance (Self-hosted or Cloud) | Runs the workflow | | Zoho CRM OAuth2 Credentials | Fetch deals + Create tasks | | Gmail (or SMTP) credentials | Send alert emails | | Google Gemini API access | AI scoring on deals | | Deals must have Stage + Owner + Activity history | Ensures accurate scoring | How It Works — Setup & Configuration Steps Step-by-Step Setup Import workflow into n8n Enable Zoho CRM OAuth2 credentials in: Fetch Open Deals Create At-Risk Task Enable Gmail OAuth2 on the email alert node Validate fields from Zoho API: Last_Activity_Time Stage Owner.email Update the deal stage list in the Fetch URL if needed: Example: Qualification, Negotiation, Proposal, etc. Confirm scanning frequency in the Weekly Trigger Run the workflow manually once → check logs + emails + tasks Turn workflow Active How To Customize Nodes | Node | What You Can Customize | Example | |------|-----------------------|---------| | Weekly Trigger | Change execution frequency | Daily scan | | Fetch Deals | Include additional deal stages | Add “Value Proposition” | | Filter Stalled Deals | Adjust inactivity threshold | > 15 days instead of 30 | | AI Prompt | Add more data points | Probability to close | | Email Alert | Modify message template | Localization | | Task creation | Add reminder / follow-up info | Due date +1 day | Add-Ons (Optional Enhancements) You can easily extend this workflow by adding: Stage Change Webhook Trigger** → near real-time monitoring Google Sheets or Database Logging** for reporting Duplicate task checker** so the same deal isn’t flagged repeatedly Slack / Microsoft Teams alerts** SLA-based scoring** (pipeline aging logic) Manager escalation** if no response in X days Practical Use Cases This workflow is ideal for: Sales manager auto-alert system for aging deals Leaderboard tracking for untouched deals Weekly CRM hygiene and rep performance tracking Early detection of churn risk in B2B sales cycles AI-assisted deal coaching and next-step suggestions Many more scenarios are possible based on deal movement automation. Troubleshooting Guide | Issue | Possible Cause | Fix / Solution | |------|----------------|----------------| | No deals processed | Stage filters too narrow | Update fetch URL stage list | | Emails not sent | Gmail credentials missing or expired | Reconnect Gmail OAuth2 | | Tasks not created | Zoho API permissions missing | Enable write permissions | | Owner email missing | CRM field not mapped correctly | Update sendTo expression | | Health score always null | Output parser mismatch | Check prompt & parser config | | Workflow runs but no alerts sent | No stalled deals or score >= threshold | Temporarily lower threshold for testing | Need Help? If you would like expert help customizing this workflow or implementing additional automation like stage-based triggers, dashboards or integration with Slack/Teams, our n8n automation team at WeblineIndia can assist you.
by Akshay Chug
Overview Stop spending 20 minutes writing each Upwork proposal from scratch. This workflow reads your Vollna job alert emails, scores every job against your skills and budget preferences, and uses Claude to write a personalised 55-75 word cover letter for every match and saved as a Gmail draft ready to review and send in one click. How it works Polls Gmail every 30 minutes for new Vollna job alert emails Parses every individual job title, budget, and URL from the Vollna email HTML Scores each job 1-10 against your skills, rate, and budget filters set in the Settings node Jobs below your threshold are logged as skipped — no proposal wasted Claude Haiku writes a 55-75 word cover letter for each match using the Nick Saraev formula The proposal is saved as a Gmail draft with the job title as the subject, ready for one-click review Every job is either matched or skipped and then is logged to Google Sheets for pipeline tracking Setup steps Vollna — Make sure you have a Vollna account with at least one active filter sending alerts to your Gmail Gmail — Connect your Gmail account in Check for Vollna Alerts and Save Proposal as Draft Settings node — Open Configure Profile and Settings and fill in your name, skills, bio, hourly rate, minimum budget, and score threshold. This is the only node you need to personalise Claude AI — Add your Anthropic API key to the Claude Haiku sub-node from console.anthropic.com Slack — Connect Slack in Notify New Draft and set your channel. Right-click and Disable if unused Google Sheets — Create a sheet called Upwork Jobs with columns: Timestamp, Job Title, Budget, Score, Status, Draft Saved, Job URL Activate — processes every new Vollna alert automatically