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 Milo Bravo
Email Lead Router: Gmail → Gemini → Salesforce Pipeline Who is this for? Event sales teams & conference organizers processing 100+ sponsor/partner emails weekly who need instant lead qualification, Salesforce automation, & pipeline analytics. What problem is this workflow solving? Event email chaos kills revenue: 200+ sponsor emails/week → manual Salesforce entry No sentiment/intent scoring = missed $ opps 10+ hours/week routing + logging Fragmented pipeline visibility Zero-drop AI qualification → auto-Salesforce → team routing. What this workflow does Gmail Trigger captures event inbox emails Gemini #1 scores sentiment (Positive/Neutral/Negative + confidence) Gemini #2 extracts topic, intent, urgency (1-10), org, budget signals Upserts Salesforce Lead (deduped by email) w/ 9 custom fields: Sentiment__c, Urgency_Score__c, etc. Hot leads (Positive + urgency ≥7) → auto Salesforce Opportunity Creates Salesforce Task w/ AI-suggested follow-up action Logs to email_analytics Data Table + Google Sheets (Looker Studio dashboard) Routes: Positive → Hot email + Slack #hot-leads (2h); Neutral → Follow-up + #follow-ups (24h); Negative → Insights + #insights Setup (8 minutes): Gmail OAuth2 (event inbox) Google Gemini API Salesforce OAuth2* + *9 custom Lead fields** (Sentiment__c, Urgency_Score__c, etc.) Slack OAuth2 + channels (#hot-leads, #follow-ups, #insights) email_analytics Data Table ID Update Send Email recipients Test w/ Evaluation Dataset How to customize: Tune urgency threshold (7→8) Add event keywords (webinar/tradeshow) Swap Slack → Teams; Salesforce → HubSpot Multi-inbox territory routing ROI: 100% Salesforce coverage** (no manual entry) 8x faster qualification** (2min vs 16h/week) 30% opp velocity** (auto opps/tasks) Live Looker dashboard** → data-driven decisions Need help customizing?: Contact me for consulting and support: LinkedIn / Message Keywords: event sales leads, Salesforce automation, Gemini lead scoring, email sentiment, sales pipeline n8n, AI sales routing
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 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 Sona Labs
Automatically analyzes your Google Ads performance every Monday and sends a comprehensive report to your inbox with AI-powered insights, week-over-week comparisons, and prioritized recommendations to optimize your campaigns. How it works Step 1: Schedule Weekly Analysis Triggers automatically every Monday at midnight Can be customized to your preferred schedule Initiates the entire data collection and analysis process Step 2: Collect Performance Data Fetches last 7 days of Google Ads data via API Retrieves previous 7 days of data (days 8-14) for comparison Extracts key metrics including impressions, clicks, cost, conversions, CTR, and CPA Calculates and summarizes performance for each week Identifies top performers, problem campaigns, and efficiency trends Merges data to create comprehensive week-over-week comparison Step 3: AI-Powered Analysis Aggregates all performance data into a single view Sends data to AI Analyst powered by GPT-5.1 AI analyzes trends, identifies insights, and spots anomalies Diagnoses root causes of performance changes Generates actionable, prioritized recommendations based on business impact Calculates efficiency metrics and budget optimization opportunities Step 4: Deliver Insights Report Formats analysis into a professional HTML report Emails comprehensive insights directly to your inbox Includes executive summary, week-over-week comparison tables, and color-coded metrics Provides high/medium/low priority action items Ready for immediate action and strategy adjustments What you'll get The workflow delivers a comprehensive weekly analysis with: Performance Metrics**: Impressions, clicks, CTR, conversions, cost, CPA, and efficiency trends Week-over-Week Comparison**: Side-by-side analysis with percentage changes and visual indicators Top Performers Analysis**: Detailed breakdown of your best-performing campaigns Issues & Performance Risks**: Identification of campaigns with high spend but zero conversions, declining CTR, or rising CPA AI-Generated Insights**: Intelligent pattern recognition and trend analysis with root cause diagnosis Actionable Recommendations**: Prioritized action items (high/medium/low) with expected impact and risk levels Budget Efficiency Analysis**: Spend allocation recommendations and wasted spend identification Campaign Intelligence**: Clear understanding of what's working and what needs attention Data Confidence Assessment**: Commentary on sample size adequacy and metric reliability Automated Delivery**: Weekly HTML report sent directly to your email without manual effort Why use this Save time on reporting**: Eliminate 2-3 hours of manual weekly analysis and report creation Never miss insights**: AI catches trends and patterns humans might overlook Consistent monitoring**: Automated weekly reviews ensure you stay on top of performance Data-driven decisions**: Make strategic adjustments based on comprehensive analysis with clear priorities Early problem detection**: Spot performance issues and wasted spend before they impact your budget Optimize continuously**: Regular insights enable ongoing campaign refinement Focus on strategy**: Spend less time analyzing data, more time implementing improvements Scalable intelligence**: Works whether you manage 1 campaign or 100 Executive-ready reports**: Professional HTML format suitable for sharing with stakeholders Setup instructions Before you start, you'll need: Google Ads Account & API Access Go to your Google Ads account at https://ads.google.com Find your Customer ID (XXX-XXX-XXXX format in top-right corner) Get a Developer Token from Google Ads API Center Enable API access for your account OpenAI API Key (for GPT-5.1 AI analysis) Sign up at https://platform.openai.com Navigate to API keys section and create a new key Ensure you have access to GPT-5.1 model Gmail Account (for receiving reports) OAuth2 authentication will be used No app password needed Configuration steps: Replace Google Ads Customer ID: Open both "Get Last Week Data" and "Get Previous Week Data" HTTP Request nodes In the URL field, replace [Customer ID] with your actual Customer ID (format: XXX-XXX-XXXX) Add Developer Token: In both HTTP Request nodes, add your Google Ads Developer Token to the header parameters Connect Google Ads OAuth2: In both HTTP Request nodes, authenticate with your Google Ads credentials Select your ad account Connect OpenAI credentials: In the "OpenAI Chat Model" node, add your OpenAI API key Verify GPT-5.1 model is selected Configure email delivery: In the "Email Report to User" node, connect your Gmail OAuth2 credentials Update the recipient email address (default: lee@sonalabs.com) Customize subject line if desired Set your schedule (optional): In the "Weekly Trigger" node, configure your preferred day and time Default is Monday at midnight Test the workflow: Click "Execute Workflow" to run manually Verify data pulls correctly from Google Ads Check that AI analysis provides meaningful insights Confirm email report arrives formatted correctly Customize analysis focus (optional): Open the "AI Analyst" node Adjust the prompt to prioritize specific metrics or goals for your business Modify thresholds for "problem campaigns" in the calculation nodes Activate automation: Enable the workflow to run automatically every Monday Monitor the first few reports to ensure accuracy Note: The workflow analyzes the last 7 days vs. the previous 7 days, giving you rolling two-week comparisons every Monday. Adjust the date ranges in the HTTP Request nodes if you need different time periods.
by Nguyen Thieu Toan
📖 Overview A comprehensive flight price monitoring and AI assistant solution built entirely in n8n. Combines automated price tracking with intelligent conversational flight search via Telegram. Perfect for: ✈️ Tracking flight prices to favorite destinations 💰 Getting alerts when prices drop below threshold 🗓️ Planning trips with AI-powered flight searches 🌍 Finding best deals across airlines 📱 Managing travel plans through Telegram chat Requirements: n8n v1.123.0+ or v2.0.0+ SerpAPI key (500 free/month), Google Gemini API, Telegram bot token ⚡ What's in the Box Two Powerful Workflows | Workflow | Function | Trigger | |----------|----------|---------| | 🔔 Automated Monitoring | Tracks specific routes, alerts on price drops | Schedule (every 7 days) | | 💬 AI Flight Assistant | Interactive search with natural language | Telegram messages | Key Capabilities: 🎯 Set price thresholds and get instant alerts 🤖 Ask questions in natural language (Vietnamese/English) 🧠 AI remembers conversation context 📊 Compares prices across airlines ⚡ Real-time search results from Google Flights 🎯 Key Features 📅 Scheduled Price Checks**: Automatic monitoring every 7 days (customizable) 💡 Smart AI Assistant**: Understands "find cheapest flight to Bangkok next weekend" 🔔 Instant Alerts**: Telegram notifications when prices drop 🧠 Context-Aware**: AI remembers your preferences and previous searches 🌐 Multi-Language**: Handles Vietnamese and English seamlessly 📱 Mobile-Ready**: Full control via Telegram chat interface Technical Highlights: SerpAPI integration for real-time prices, Google Gemini Flash for AI responses, session-based conversation memory, Telegram HTML formatting, automatic date calculations (+5 days for returns) 🏗️ How It Works Workflow 1: Automated Monitoring Schedule Trigger → Configure Route → Search Flights → Extract Best Price ↓ Price < Threshold? → Send Alert Workflow 2: AI Assistant Telegram Message → AI Agent → Flight Search Tools → Format Response ↓ ↓ ↓ Understand Round-trip/One-way Telegram HTML Context Auto +5 days return Send to user 🛠️ Setup Guide Step 1: API Credentials Get SerpAPI key (https://serpapi.com), Google Gemini API (https://aistudio.google.com/app/apikey), Telegram bot token (@BotFather) Step 2: Configure Monitoring Edit Fields node: Set departure/arrival codes, price threshold, Telegram ID Step 3: AI Assistant Setup Link Gemini model to AI Agent, connect flight search tools, activate memory Step 4: Activate & Test Enable workflow, send test message to bot, verify alerts 💡 Usage Examples Automated Alert: ✈️ CHEAPEST TICKET Price: 2,450,000 VND Airline: Vietjet Air Time: 06:00 → 08:00 AI Chat: "Find round-trip tickets Hanoi to Bangkok tomorrow" "What's the cheapest flight to Nha Trang next weekend?" "Search one-way Da Nang to Singapore on March 15" 👤 About the Author Nguyen Thieu Toan (Nguyễn Thiệu Toàn / Jay Nguyen) AI Automation Specialist | n8n Workflow Expert Contact: 🌐 nguyenthieutoan.com 📘 Facebook 💼 LinkedIn 📧 Email: me@nguyenthieutoan.com More Nguyen Thieu Toan's n8n Template GenStaff Company: genstaff.net 📄 License Free for commercial/personal use. Keep author attribution when sharing.** Ready to never miss a flight deal again? Import this workflow and start tracking prices today! 🚀
by Cheng Siong Chin
How It Works This workflow automates end-to-end audio translation with quality assurance for content creators, educators, and international teams managing multilingual content. It solves the challenge of translating audio into multiple languages while ensuring accuracy and maintaining organized delivery. The system receives audio files via webhook, splits them into target languages (Arabic, French, Spanish, Chinese, Hindi), and processes each through NVIDIA's Parakeet TDT translation model. OpenAI validates translation quality, and results are enhanced with comprehensive metadata. Successfully translated files are uploaded to Google Drive with organized naming, combined into a summary spreadsheet, and delivered via email notification. Failed translations trigger quality alerts, ensuring reliable output while minimizing manual oversight and reducing translation turnaround time from hours to minutes. Setup Steps Configure NVIDIA API credentials in the "Generate Audio with ElevenLabs" Add OpenAI API key for quality evaluation in the "OpenAI Chat Model" node Set up Google Drive OAuth connection and specify target folder ID for uploads Configure Gmail SMTP credentials for notification delivery Update webhook URL in source applications to trigger workflow Customize target languages in "Split Languages" node if needed Prerequisites Active accounts: NVIDIA (build.nvidia.com), OpenAI, Google Drive, Gmail. API credentials for all services. Use Cases International podcast distribution, e-learning course localization Customization Modify target languages in Split node, adjust quality thresholds in OpenAI evaluation Benefits Reduces translation time by 90%, eliminates manual quality checks through automated validation Here are clear, professional subheadings for each What / Why pair. They’re concise, action-oriented, and fit well in technical workflow documentation.
by Cheng Siong Chin
How It Works Scheduled processes retrieve customer feedback from multiple channels. The system performs sentiment analysis to classify tone, then uses OpenAI models to extract themes, topics, and urgency indicators. All processed results are stored in a centralized database for trend tracking. Automated rules identify high-risk or negative sentiment items and trigger alerts to the relevant teams. Dashboards and workflow automation then visualize insights and support follow-up actions. Setup Instructions Data Sources: Connect social media APIs, survey tools, and customer support platforms. AI Analysis: Configure the OpenAI API with sentiment and theme-extraction prompts. Database: Set up a feedback storage schema in your utility database. Alerts: Configure email notifications and CRM triggers for priority issues. Dashboards: Link your analytics and reporting tools for real-time insights. Prerequisites Social media/survey API credentials; OpenAI API key; database access; CRM system credentials; email notification setup Use Cases Customer sentiment tracking; product feedback aggregation; support ticket prioritization; brand monitoring; trend identification Customization Adjust sentiment thresholds; add new feedback sources; modify categorization rules Benefits Reduces analysis time 85%; captures actionable insights; enables rapid response to issues
by DIGITAL BIZ TECH
AI-Powered Timesheet → Invoice Automation (Gmail + OCR + AI + Google Sheets + QuickBooks) > Note: This workflow uses sticky notes extensively to document each logical section of the automation. Sticky notes are mandatory and already included to explain OCR, AI parsing, folder logic, duplicate handling, and QuickBooks steps. This workflow automates the full lifecycle of timesheet-based invoicing — from emailed timesheets to structured Google Sheets records and finalized invoices in QuickBooks Online. It is designed for real-world billing scenarios, including split weeks across months, zero-hour months, duplicate prevention, and first-week-of-year edge cases. What This Workflow Does Listens to Gmail for timesheet emails with attachments Splits and processes each attachment independently Extracts text using OCR (no hardcoded API keys) Uses AI to parse month-wise billable hours Correctly splits weeks spanning multiple months Looks up Customer and PO details from Google Sheets Organizes files in Client → Employee → Year folders in Google Drive Reuses existing invoice sheets or creates new ones Prevents duplicate invoice rows Automatically finds or creates customers in QuickBooks Creates invoices in QuickBooks using validated data High-Level Workflow Stages Gmail Intake and Attachment Loop OCR Text Extraction AI-Based Timesheet Parsing Month Normalization and Validation Customer & PO Lookup Drive Folder Discovery and Creation Invoice Sheet Reuse or Creation Duplicate and Edge-Case Handling Append Invoice Rows to Google Sheets Create / Update Customers in QuickBooks Create Invoices in QuickBooks Each of these stages is clearly documented with sticky notes inside the workflow canvas. Quick Setup Instructions Import the workflow JSON into your n8n instance Configure credentials for: Gmail Google Drive Google Sheets OpenAI or Google Gemini QuickBooks Online Verify the OCR HTTP node: Default URL: https://universal-file-to-text-extractor.vercel.app/extract No hardcoded API keys are used Configure Get Customer Info From PO Sheet: Spreadsheet ID Sheet name and column mappings Ensure the Client Invoices root folder exists in Google Drive Send a test timesheet email Execute the workflow once manually Activate the workflow Who This Workflow Is For Agencies and consultancies billing from emailed timesheets Finance and operations teams using Google Workspace + QuickBooks Staffing firms with monthly or bi-weekly contractor billing Teams that want a fully auditable, zero-manual invoice process Requirements n8n instance Gmail account receiving timesheet emails Google Drive and Google Sheets OpenAI or Google Gemini API OCR API endpoint (configurable) QuickBooks Online account Customer PO Google Sheet containing: Email Customer Name Company Name Customer Account Number PO Number Item Folder Name Invoice range Due Date Calculation How It Works (Detailed) 1. Email Intake and Attachment Loop Gmail Trigger polls for timesheet emails Attachments are split so each file is processed independently Sticky notes explain the intake and loop logic 2. OCR Extraction Each attachment is sent to the OCR API PDFs and images are converted to plain text OCR logic is documented via sticky notes 3. AI Timesheet Parsing (Month-Wise) AI extracts data only from BILLABLE HOURS sections Outputs strict JSON: Employee Name Client Name Month Year Week Start Date Week End Date Total Billable Hours Special handling included: Split weeks across months Zero-hour months still included No guessed or inferred dates 4. Month Normalization and Validation AI output is normalized into a month array Each month is processed independently Invalid or zero-hour entries are skipped 5. Customer and PO Lookup Sender email is matched in the PO sheet Retrieved values drive: Folder structure Invoice logic Due date calculation 6. Google Drive Folder Structure The workflow enforces a strict hierarchy: Client Invoices └── Client └── Employee └── Year Missing folders are created automatically. 7. Invoice Sheet Naming and Search Sheet names are generated using: Employee Name Month Year Existing sheets are reused when found Supports monthly and 15-day billing cycles 8. Duplicate Prevention and Edge Cases Duplicate invoice rows are detected and skipped January first-week edge case is handled explicitly Safe re-runs are supported 9. Google Sheets Invoice Rows Each appended row includes: Customer Account Number Invoice Date Due Date PO Number Item Name Quantity (Total Hours) Period description 10. QuickBooks Integration Searches for existing customers in QuickBooks Creates customers automatically if missing Creates invoices using: Customer reference Item Quantity Invoice date Due date All QuickBooks logic is documented with sticky notes. How To Customize Swap AI model (OpenAI ↔ Gemini) Extend prompts to extract: Project Cost center Approval status Add tax codes, currency, or unit pricing Modify folder naming rules Insert approval steps before invoice creation Common Use Cases Monthly contractor invoicing Agency billing across multiple clients Finance automation with audit-ready records Eliminating manual timesheet-to-invoice work Troubleshooting | Issue | Likely Cause | |------|-------------| | No invoices created | Gmail filter mismatch or email already read | | OCR output empty | Unsupported file or OCR endpoint issue | | Wrong month split | Review AI prompt and month logic | | Duplicate rows | Duplicate detection conditions | | Invoice missing in QuickBooks | Customer or item configuration issue | Notes on Community Guidelines Sticky notes are used throughout the workflow No hardcoded API keys are present Markdown is used (no HTML tags) This workflow is original and not copied Need Help or Customization? Digital Biz Tech can help tailor this workflow to your business. We offer free setup support, including credential configuration and deployment. Contact: rajeet.nair@digitalbiz.tech Website: https://www.digitalbiz.tech LinkedIn: https://www.linkedin.com/company/digital-biz-tech/ You can also DM us on LinkedIn for any help. You can also DM us on LinkedIn.
by Milo Bravo
Event Registration + Auto-Enrichment Intelligence Who is this for? Event organizers, conference planners, and marketing teams fighting registration drop-off who want 4-field forms with LinkedIn-level attendee intelligence. What problem is this workflow solving? Multi-page forms kill conversions: 80-90% drop-off on page 2 No attendee insights post-reg Manual enrichment wastes hours Abandoned carts = lost revenue This captures 4 fields but enriches 15+ data points automatically. What this workflow does 3 Webhook Intelligence Suite: POST /event-registration**: 4-field form → enrichment → HubSpot POST /reg-beacon**: Abandoned cart tracking pixel POST /validate-promo**: AJAX promo code validation Requires 2 sub-workflows: 1) Abandoned Cart Recovery 2) Participant Re-engager Enrichment Waterfall: Clearbit → LinkedIn (Proxycurl) → Google+AI → Full profile Outputs: HubSpot contacts with company/role/title Data Tables: enriched_profiles / reg_analytics Slack alerts + email confirmations Setup (12 minutes) Data Tables**: enriched_profiles, reg_analytics, promo_codes HubSpot**: API key + custom properties APIs**: Clearbit, Proxycurl, SerpAPI, Gemini Host**: reg-page/index.html (update webhook URLs) SMTP/Slack**: Notifications Fully configurable, no code changes needed. How to customize to your needs Forms**: Swap HTML for Typeform/Webflow Enrichment**: Add Apollo/Hunter for emails CRM**: HubSpot → Salesforce → Airtable Promos**: Tiered discounts / early-bird Companion**: Abandoned Cart + Re-engager templates ROI: 3x registration completion** (4 fields vs 12+) 65% enriched profiles** (company/role/title) 20% revenue recovery** (abandoned carts) Need help customizing?: Contact me for consulting and support: LinkedIn / Message Keywords: event registration, attendee enrichment, abandoned cart recovery, conference automation, HubSpot
by Cheng Siong Chin
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
by Cheng Siong Chin
How It Works This workflow automates comprehensive risk signal detection and regulatory compliance management across financial and claims data sources. Designed for risk management teams, compliance officers, and financial auditors, it solves the critical challenge of identifying potential risks while ensuring timely regulatory reporting and stakeholder notifications. The system operates on scheduled intervals, fetching data from multiple sources including financial APIs and claims databases, then merging these streams for unified analysis. It employs an AI-powered risk signal agent to detect anomalies, regulatory violations, and compliance issues. The workflow intelligently routes findings based on risk severity, orchestrating parallel processes for critical risks requiring immediate escalation and standard risks needing documentation. It manages multi-channel notifications through Slack and email, generates comprehensive compliance documentation, and maintains detailed audit trails. By coordinating regulatory analysis, exception handling, and evidence collection, it ensures complete risk visibility while automating compliance workflows. Setup Steps Configure Schedule Trigger with risk monitoring frequency Connect Workflow Configuration node with data source parameters Set up Fetch B2B Data and Fetch Claims Data nodes with respective API credentials Configure Merge Financial Data node for data consolidation Connect Calculate Risk Metrics node with risk scoring algorithms Set up Risk Signal Agent with OpenAI/Nvidia API credentials for anomaly detection Configure parallel output parsers Connect Check Critical Risk node with severity routing logic Set up Route by Risk Level node for workflow branching Prerequisites OpenAI or Nvidia API credentials for AI-powered risk analysis, financial data API access Use Cases Insurance companies monitoring claims fraud patterns, financial institutions detecting transaction anomalies Customization Adjust risk scoring algorithms for industry-specific thresholds Benefits Reduces risk detection time by 80%, eliminates manual compliance monitoring