Workflow Templates

🚀 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

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.

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

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

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

Monitor Clutch categories for new agencies to Slack With BrowserAct and Gemini Introduction This workflow automates the discovery of new B2B service providers entering the market. It scrapes a specific category on Clutch.co weekly, standardizes the data using AI, and compares it against a historical database to identify only the fresh "new entrants." These leads are then sent to Slack as a "Hot Alert." Target Audience Sales Development Representatives (SDRs), partnership managers, and lead generation agencies looking for new agencies or service providers before their competitors find them. How it works Scheduling: A Weekly Trigger initiates the scan to ensure regular monitoring of the market. Targeting: A Set node defines the specific Clutch category URL to monitor (e.g., https://clutch.co/developers). Data Extraction: The BrowserAct node runs the "The New Entrant Asset Finder" template. It navigates to the target category and scrapes the current list of companies. Data Cleaning: An AI Agent (using OpenRouter/Gemini) processes the raw scraped data. It fixes formatting issues, such as converting "$10,000+" to integers and splitting "City, Country" strings into separate fields. Staging: The cleaned data is written to a temporary "Second Extraction" sheet in Google Sheets. Change Detection: The workflow retrieves the previous week's data ("Database") and the current week's data. A second AI Agent compares the two lists to identify companies that exist in the new scan but not the old one. Notification: If new companies are found, a Slack node posts a formatted alert with details like "Company Name," "Rate," and "Website." Database Update: The workflow clears the old database and replaces it with the latest scan, establishing a new baseline for the next week's comparison. How to set up Configure Credentials: Connect your BrowserAct, OpenRouter, Google Sheets, and Slack accounts in n8n. Prepare BrowserAct: Ensure the The New Entrant Asset Finder template is active in your BrowserAct library. Prepare Google Sheet: Create a Google Sheet with two tabs: Database (First Extarction) Second Extraction Define Target: Open the Clutch Category Link node and paste the URL of the Clutch category you want to track. Configure IDs: Update the Google Sheets nodes to point to your specific spreadsheet file and the respective tabs mentioned above. Google Sheet Headers To use this workflow, ensure your Google Sheet tabs use the following headers: company_name website_url min_project_value_usd hourly_rate_low hourly_rate_high employees_range city country short_description Requirements BrowserAct Account:* Required for scraping. Template: *The New Entrant Asset Finder**. OpenRouter Account:** Required for cleaning data and detecting changes. Google Sheets:** Acts as the historical database. Slack Account:** Used for receiving lead alerts. How to customize the workflow Change the Source: Modify the Clutch Category Link and the BrowserAct template to scrape a different directory, such as G2, Capterra, or Upwork. Filter Logic: Update the system prompt in the Detect data changes AI node to only alert on companies with a specific hourly rate (e.g., >$100/hr) or employee count. Enrichment: Add a Clearbit or Apollo node after the change detection step to find email addresses for the new companies before sending them to Slack. Need Help? How to Find Your BrowserAct API Key & Workflow ID How to Connect n8n to BrowserAct How to Use & Customize BrowserAct Templates Workflow Guidance and Showcase Video AI-Powered Lead Finder: Target New & Growing Companies (n8n + AI Tutorial)

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.

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.

Who is this for? This workflow is built for founders, sales teams, solopreneurs, and agencies who want to automate outbound sales without expensive tools. Perfect for anyone doing cold email outreach who wants AI-powered personalization at scale. What it does The workflow runs three automated flows: Flow 1 — New Lead Processing (8 AM weekdays): Reads new leads from Google Sheets Scrapes the lead's website to build a research dossier AI scores each lead (0–100) on company fit, role fit, timing signals, and engagement potential For leads scoring 40+, AI generates 3 personalized cold emails with different angles Sends Email 1 immediately and saves all 3 emails to the sheet Low-fit leads are marked as skipped Flow 2 — Follow-up Engine (every 2 hours weekdays): Checks for leads that need follow-ups Sends Email 2 after 3 days, Email 3 after 7 days Automatically marks sequence as complete after Email 3 Skips leads that have already replied Flow 3 — Reply Detection (every 2 hours weekdays): Searches Gmail for replies from active leads Filters out your own sent emails to avoid false positives When a reply is found, marks the lead as "replied" and stops the sequence Sends a Telegram alert with the reply preview Setup steps Google Sheets — Create a spreadsheet with columns: Lead Name, Email, Company, Website, Role/Title, Status, Reply Date, Reply Subject, Reply Snippet, and email tracking columns (see sticky notes in the workflow for full list) Gmail OAuth2 — Connect your Gmail account for sending emails and searching replies Ollama — Install locally and pull your preferred model (e.g., ollama pull mistral). You can also swap for OpenAI or Anthropic Telegram Bot — Create via @BotFather, get your bot token and chat ID AI Lead Scorer prompt — Edit the system prompt with your product, ICP, and scoring criteria AI Email Writer prompt — Edit with your name, company, value prop, and one specific result Sender name — Update the sender name in the Extract Emails code node (line 12) and Find Follow-ups code node (line 9) Gmail address — Set your sending Gmail address in the Filter Active Leads code node (line 10) and Check Reply Results code node (line 10) Test — Add a test lead with status "new", run the research flow manually, verify emails generate correctly, then enable all schedules Requirements Self-hosted n8n (uses Ollama nodes) Ollama running locally with at least one model installed Google Sheets OAuth2 credentials Gmail OAuth2 credentials Telegram Bot credentials How to customize Adjust the scoring threshold (default 40) in the Extract Score node to be more or less selective Change follow-up timing (default 3 and 7 days) in the Find Follow-ups code node Modify cron schedules on any trigger to match your timezone and preferences Swap Ollama for OpenAI or Anthropic by replacing the LLM nodes Add a LinkedIn enrichment step before the dossier builder for richer research Customize email tone and sign-off in the AI Email Writer system prompt

Automatically converts your daily WhatsApp messages and photos from travels into beautifully structured travel stories, saved as documents in Google Drive. How it works Receive WhatsApp Updates - Webhook captures messages, photos, and locations from your travel day Validate & Aggregate Content - JavaScript organizes messages by day, extracts metadata, validates media Fetch Previous Entries - Retrieves existing journal from Google Drive for context and continuity Prepare AI Context - JavaScript builds comprehensive prompt with photos, messages, locations, and timeline Claude AI Story Generation - Transforms raw messages into narrative travel journal with insights Parse & Format Story - JavaScript structures the output into readable document format Wait for Finalization - Brief pause to ensure all processing completes Save to Google Drive - Creates or updates your travel journal document Send Confirmation - WhatsApp notification with preview of generated story Respond to Webhook - Returns success confirmation Setup Steps Import workflow into n8n Configure credentials: Anthropic API - Claude AI for story generation Google Drive - Document storage and retrieval WhatsApp Business API or Twilio WhatsApp - Message integration Create a Google Drive folder for your travel journals Set up WhatsApp webhook integration: Point WhatsApp webhook to: https://your-n8n-instance.com/webhook/travel-journal Configure to send: messages, media, locations Update the "Fetch Previous Journal" node with your Drive folder ID Activate the workflow Sample WhatsApp Input Messages throughout the day: 09:30 AM: "Just arrived in Kyoto! The train station architecture is stunning 🚄" 11:45 AM: "Fushimi Inari shrine - thousands of orange torii gates going up the mountain" 📸 Photo: Torii gates pathway 02:15 PM: "Tried okonomiyaki for lunch. Amazing! The chef made it right in front of us" 📸 Photo: Okonomiyaki cooking 05:30 PM: "Gion district at sunset. Spotted two geishas!" 📍 Location: Gion, Kyoto, Japan 08:45 PM: "Dinner at an izakaya. Made friends with locals who taught us drinking games 😄" Generated Journal Output Day 3: Kyoto - Ancient Temples and Modern Connections The day began with anticipation as the shinkansen pulled into Kyoto Station at 9:30 AM. The station itself was an architectural marvel—a blend of traditional Japanese aesthetics and contemporary design that set the tone for what would be an unforgettable day. By mid-morning, I found myself at Fushimi Inari Taisha, one of Kyoto's most iconic sites. The seemingly endless tunnel of vermillion torii gates created a mesmerizing pathway up Mount Inari. Each gate, donated by individuals and businesses, bore inscriptions in black kanji. The experience was both spiritual and surreal—the way light filtered through the gates, creating dancing shadows on the stone path... [Full narrative continues with integrated photos, locations, and emotional insights] Features Smart Aggregation** - Groups messages by day, even across time zones Photo Integration** - Embeds images inline with contextual descriptions Location Awareness** - Maps locations and adds geographical context Narrative Style** - Converts casual messages into polished travel prose Emotional Intelligence** - Captures mood and significance beyond literal text Timeline Coherence** - Maintains chronological flow and story arc Automatic Continuity** - Links to previous days for multi-day trip journals Format Flexibility** - Outputs as Google Docs with proper formatting Privacy & Data Messages are processed in real-time and not stored long-term Photos are referenced but can be embedded or linked based on preference Journal documents are private in your Google Drive No message content is retained after journal generation

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.

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