Workflow Templates

Overview This workflow automatically enriches Brazilian company data by fetching comprehensive CNPJ information from the MinhaReceita.org API and updating your Google Sheets spreadsheet. Perfect for data analysts, sales teams, and anyone working with Brazilian business databases who needs to enrich company information at scale. What it does Reads CNPJ numbers** from your Google Sheets spreadsheet Fetches complete company data** from Brazil's Federal Revenue database via MinhaReceita.org API Updates your spreadsheet** with comprehensive business information including address, tax status, partners, and more Sends Telegram notifications** when the process is complete Processes data in batches** to handle large datasets efficiently Key Features ✅ Free API - No authentication required, completely free to use ✅ Comprehensive Data - 47+ fields of official Brazilian company information ✅ Batch Processing - Handles up to 100 CNPJs per batch automatically ✅ Smart Filtering - Only processes CNPJs that don't already have data ✅ Real-time Updates - Updates your spreadsheet as data is retrieved ✅ Progress Notifications - Get notified via Telegram when complete Setup Requirements Google Sheets Structure Your spreadsheet must contain at minimum: cnpj** column with Brazilian CNPJ numbers (numbers only, no formatting) razao_social** column (used to identify records without data) Credentials Needed Google Sheets OAuth2** credentials configured in n8n Telegram Bot** credentials for notifications (optional but recommended) Available Data Fields The workflow can populate your spreadsheet with any or all of these official fields from Brazil's Federal Revenue: 🏢 Company Information cnpj, razao_social, nome_fantasia, capital_social porte, codigo_porte, natureza_juridica, codigo_natureza_juridica 📍 Address & Location uf, municipio, codigo_municipio, codigo_municipio_ibge bairro, logradouro, descricao_tipo_de_logradouro numero, complemento, cep pais, codigo_pais, nome_cidade_no_exterior 📞 Contact Information email, ddd_telefone_1, ddd_telefone_2, ddd_fax 💼 Business Classification cnae_fiscal, cnae_fiscal_descricao, cnaes_secundarios regime_tributario, qualificacao_do_responsavel 📋 Registration Status situacao_cadastral, descricao_situacao_cadastral motivo_situacao_cadastral, descricao_motivo_situacao_cadastral situacao_especial, identificador_matriz_filial, descricao_identificador_matriz_filial ente_federativo_responsavel 📅 Important Dates data_inicio_atividade, data_situacao_cadastral, data_situacao_especial 🏛️ Tax Regime Information opcao_pelo_mei, data_opcao_pelo_mei, data_exclusao_do_mei opcao_pelo_simples, data_opcao_pelo_simples, data_exclusao_do_simples 👥 Partners & Shareholders qsa (Complete structured data of company partners and shareholders) How to Use Prepare your spreadsheet with CNPJ numbers in the cnpj column Configure your Telegram ID in the Settings node for notifications Set up Google Sheets credentials in n8n Add the desired data columns to your spreadsheet (any combination from the list above) Run the workflow - it will automatically process all CNPJs without existing data Performance & Limitations API Limits**: None - completely free API from MinhaReceita.org Data Accuracy**: Official data from Brazil's Federal Revenue Service Batch Size**: Configurable (default: 100 records per batch) Use Cases Lead Enrichment**: Enhance prospect databases with complete company information Market Research**: Gather comprehensive data about Brazilian companies Compliance & Due Diligence**: Verify company registration status and details Sales Intelligence**: Access contact information and company classification data Data Cleaning**: Standardize and complete existing company databases Prerequisites N8N instance with Google Sheets integration Google Sheets document with CNPJ data Basic understanding of Brazilian CNPJ format (14-digit company registration number) Telegram bot token (optional, for notifications) Important Notes CNPJs must be active and registered with Brazil's Federal Revenue Service The workflow only processes CNPJs where razao_social is empty (avoiding duplicates) All data comes from official government sources via MinhaReceita.org No rate limiting needed - the API is designed for bulk requests Supports both matriz (headquarters) and filial (branch) identification

Real-Time Uptime Alerts to Jira with Smart Slack On-Call Routing This workflow automatically converts uptime monitoring alerts received via webhook into Jira incident tasks and intelligently notifies an available on-call team member on Slack based on their real-time presence status. It ensures critical service outages never go unnoticed by selecting an active responder and sending a detailed direct message immediately. ⚡ Quick Implementation Steps Import the workflow JSON into n8n. Configure your Webhook, Slack, and Jira credentials. Update the IF node to filter for status = down (already configured). Set the Jira project and issue type as required. Connect your Slack on-call channel. Activate the workflow and send a test alert using Postman or your monitoring tool. What It Does This automation listens for incoming alerts from any uptime monitoring service. When a system or service goes down, the workflow instantly validates whether the alert is critical (status = down). Once validated, it automatically creates a detailed Jira Task containing all relevant service details such as timestamp, downtime duration, error code, customer impact and priority. After the Jira incident is created, the workflow retrieves a list of all members from a dedicated Slack on-call rotation channel. It checks each member’s Slack presence (active, away, offline) and uses smart selection logic to choose the best person to notify. The selected team member then receives a richly formatted direct Slack message containing all incident details and a link to the Jira ticket. This ensures the alert is not only logged properly but also reaches the right responder at the right time. Who’s It For This workflow is perfect for: DevOps teams managing uptime & system reliability. Support teams responsible for incident response. SRE teams using Jira and Slack. Organizations with an on-call rotation setup. Teams wanting automated escalation for downtime alerts. Requirements to Use This Workflow n8n installed** (self-hosted or cloud) Slack API credentials** with permission to read user presence and send direct messages Jira Software Cloud** credentials allowing issue creation A monitoring system** capable of sending webhook alerts (e.g., UptimeRobot, Uptime Kuma, StatusCake, custom system, etc.) Access to a Slack channel that includes your on-call rotation members How It Works & How to Set Up Step 1: Receive Alert from Uptime Monitoring Tool The workflow starts with the Webhook node (Receive Uptime Alert). Your monitoring tool must send a POST request with JSON payload including fields like: serviceName status timestamp customerImpact errorCode priority etc. Step 2: Filter for Critical Status The IF node (Filter for Critical Status) checks: Only when the service is down does the workflow continue to create a Jira incident. Step 3: Create Jira Incident Task The Create New Jira Incident node generates a Jira Task with: Summary: serviceName + timestamp Description: dynamic fields based on the alert payload Set your Jira Project and Issue Type as needed. Step 4: Fetch Slack On-Call Channel Members The workflow calls Slack API to retrieve all user IDs in a designated channel (e.g., #on-call-team). Step 5: Loop Through Each Member Split In Batches Node** loops each Slack member individually. For each user, their Slack presence is fetched using: Step 6: Build Final Data for Each User The Set node (Collect & Set Final Data) stores: presence member ID service details Jira ticket ID downtime info and more Step 7: Select the Best On-Call User A custom Code node uses presence-based logic: Selection Logic If one or more users are active → randomly pick one active user. If only one user is active → pick that user. If no users are active → default to the first member from the channel. This ensures you always get a responder. Step 8: Notify Selected User The Slack Notify Node sends a formatted direct message with: service status downtime duration error code customer impact Jira ticket link priority The selected on-call responder receives everything they need to act immediately. How to Customize Nodes Webhook Node Change the path to something meaningful (e.g., /uptime-alerts). Customize expected fields based on your monitoring tool's payload. IF Node Modify status condition for: "critical" "error" or multiple conditions Jira Node You can customize: Issue type (Incident, Bug, Task) Priority field mapping Project ID Custom fields or labels Slack Retrieval Node Change the channel to your team's actual on-call rotation channel. Slack Message Node Modify message formatting, tone, emojis, or add links. Add @mentions or tags. Include escalation instructions. Add-Ons (Optional Extensions) Enhance the workflow by adding: 1. Escalation Logic If the selected user doesn’t respond within X minutes, notify next user. 2. PagerDuty / OpsGenie Integration Trigger paging systems for SEV-1 incidents. 3. Status Page Updates Automatically update public status pages. 4. Auto-Resolution When service status returns to up, automatically: Update Jira ticket Notify the team Close the incident 5. Logging & Analytics Store incidents in Google Sheets, Notion, or a database. Use Case Examples This workflow can support multiple real-world scenarios: Website Uptime Monitoring If your main website goes down, instantly create a Jira incident and notify your on-call engineer. API Downtime Alerting When an API endpoint fails health checks, alert active developers only. Microservices Monitoring Each microservice alert triggers a consistent, automated incident creation and notification. Infrastructure Failure Detection When servers, containers, or VMs become unreachable, escalate to your infrastructure team. Database Performance Degradation If DB uptime drops or error rate spikes, create a Jira ticket and ping the database admin. And many more variations of outage, error, and performance monitoring events. Troubleshooting Guide | Issue | Possible Cause | Solution | |-------|----------------|----------| | Workflow not triggering | Webhook URL not updated in monitoring tool | Copy n8n webhook URL and update in monitoring source | | No Jira ticket created | Invalid Jira credentials or missing project permissions | Reauthorize Jira credentials and verify permissions | | Slack users not found | Wrong channel ID or bot not added to channel | Ensure bot is invited to the Slack channel | | Slack presence not returning | Slack app lacks presence permission (users:read.presence) | Update Slack API scopes and reinstall | | No user receives notification | Presence logic always returns empty list | Test Slack presence API and verify real-time presence | | Wrong user selected | Intended selection logic differs | Update the JS logic in the code node | | Jira fields not populated | Alert payload fields missing | Verify webhook payload structure and match expected fields | Need Help? If you need assistance setting up this workflow, customizing integrations, building escalations or extending the logic with add-ons — WeblineIndia is here to help. We can assist with: Custom Slack/Jira/Monitoring automation On-call rotation logic enhancements Cloud deployment & workflow optimization Any custom n8n automation Production-grade monitoring workflows 👉 Contact WeblineIndia for professional support, implementation and custom workflow development.

💰 Package Recommender with Sales Pipeline Tracking What It Does Automatically recommends the right service package based on budget, sends beautifully formatted proposal emails with case studies, logs everything to a sales pipeline tracker, and schedules your follow-up reminders. Converts inquiries into booked calls without manual proposal writing. How It Works Form Trigger → Lead submits budget and challenge details Log to Pipeline → All inquiry data saved to tracking sheet Budget Router → Directs to Basic ($0-3K), Standard ($3-6K), or Premium ($6K+) Set Package Variables → Loads appropriate features, pricing, case study Send Proposal Email → Gorgeous HTML email with personalized package details Update Pipeline → Marks "Package Sent" and sets follow-up date (+3 days) Calendar Reminder → Creates event in 3 days reminding you to follow up 🚀 SETUP INSTRUCTIONS Step 1: Create Sales Pipeline Sheet Create Google Sheet with tab "Package Inquiries" Add columns: Timestamp | Name | Email | Phone | Budget | Timeline | Challenge | Package Recommended | Package Price | Status | Date Sent | Follow-Up Date Update YOUR_GOOGLE_SHEET_ID in nodes 2, 7, and calendar description Step 2: Customize Package Details Edit nodes 4, 5, 6 (Set Package Details nodes) Update pricing, features, and case studies for your services Replace booking links with your actual Calendly/scheduling URLs Adjust package names if needed Step 3: Configure Email Template Edit node 7 email design/branding Update "Your Name" and signature Customize colors (currently: purple gradient, green CTA) Test email rendering across devices Step 4: Setup Calendar Integration Add Google Calendar OAuth2 credentials Verify follow-up timing (currently +3 days) Customize reminder description with your workflow Update Google Sheet link in calendar event

Product Ingredient Safety Analyzer with AI via WhatsApp What does this workflow do? This workflow creates an intelligent WhatsApp bot that analyzes product ingredients and provides instant safety assessments. Users can send either text queries (product names/brands) or images of product labels, and receive AI-powered analysis covering food, cosmetics, personal care, pharmaceuticals, and household products. Who's it for? Health-conscious consumers** wanting to make informed purchasing decisions Parents** checking product safety for their children People with allergies or sensitivities** screening for harmful ingredients Beauty and skincare enthusiasts** verifying cosmetic product safety Wellness coaches or nutritionists** helping clients evaluate products Small business owners** offering product safety consultation services Eco-conscious consumers** checking for environmental toxins Anyone** looking to understand what's in their everyday products What do you need to get started? Required Accounts & APIs: WhatsApp Business API** - For receiving and sending messages Google Cloud Account** - For Document AI (OCR) service Google Gemini API** - For AI-powered ingredient analysis Setup Steps: Configure WhatsApp Business API credentials Enable Google Document AI in your Google Cloud project Create a Document AI processor for OCR Set up Google Gemini API access Configure all credentials in N8N How does this workflow work? User Input Options: Text Messages**: Send product name/brand (e.g., "Dove soap", "Coca Cola") Images**: Upload photos of product ingredient labels Conversational**: Ask questions or request help Processing Flow: For Image Messages: WhatsApp receives image message Extracts and downloads the image Converts image to Base64 format Uses Google Document AI OCR to extract text AI analyzes extracted text + user caption Returns safety assessment via WhatsApp For Text Messages: WhatsApp receives text query AI directly analyzes product name/ingredients Returns safety assessment via WhatsApp AI Analysis Includes: Product type identification (food, cosmetic, pharmaceutical, etc.) Harmful ingredient detection (parabens, sulfates, trans fats, etc.) Beneficial ingredient highlights Clear safety verdict: ✅ SAFE / ⚠️ CAUTION / ❌ AVOID Practical recommendations and alternatives Response Format: The AI provides concise, WhatsApp-friendly messages with: Product category and type Key ingredients found Safety concerns with specific flags Clear recommendation Actionable advice Use Cases Health-conscious consumers** checking food product ingredients Beauty enthusiasts** verifying cosmetic safety Parents** ensuring child product safety People with allergies** screening for harmful ingredients Eco-conscious users** checking for environmental toxins General wellness** making informed purchase decisions Key Features Dual input support**: Text and image processing OCR technology**: Extracts text from product labels Multi-category analysis**: Food, cosmetics, pharmaceuticals, household items Conversational AI**: Handles greetings, help requests, unclear queries Mobile-optimized**: WhatsApp-friendly formatting Instant results**: Real-time safety assessments Educational**: Explains why ingredients are safe or harmful Technical Highlights Smart routing**: Automatically detects message type (text vs image) Structured output**: JSON-formatted AI responses for reliability Product-specific criteria**: Different analysis standards per category Error handling**: Requests clearer images if OCR fails Conversational fallback**: Guides users when information is insufficient Example Interactions User sends image of shampoo bottle: Response: "Hair Care Product Analysis - Contains sulfates and parabens. ⚠️ USE WITH CAUTION. Consider sulfate-free alternatives for healthier hair." User texts "Maggi noodles": Response: "Food Product Analysis - High sodium content, contains MSG and artificial colors. ❌ AVOID REGULAR CONSUMPTION. Occasional treat okay." User texts "Hi": Response: "Hi! I'm your Product Safety Analyzer. Send me a product name or photo of ingredients to check safety!" Benefits Empowers informed decisions**: Know what you're consuming/using Saves research time**: Instant analysis vs manual ingredient lookup Accessible**: Works via familiar WhatsApp interface Comprehensive**: Covers multiple product categories Educational**: Learn about ingredient safety over time Convenient**: Analyze products while shopping Notes OCR works best with clear, well-lit images AI provides general safety information, not medical advice Analysis based on commonly known ingredient safety standards Users should consult professionals for specific health concerns Supports conversational queries for better user experience

📝 Release Note Helper Triggered by a GitLab MR webhook, this workflow automatically assists your team in writing customer-facing release notes by combining Linear issue data with Claude AI. Apply the rn-release-n8n label to any release note MR in your docs repository to trigger it. How it works Version detection — reads your release RSS feed to find the last published version, then fetches all matching Linear version labels created since then to determine the version range automatically Issue collection — queries Linear for all completed issues in that version range that have Zendesk tickets, Slack links, or custom labels (Customer request, Release note public) attached Ticket summary — posts a structured list of all relevant issues to the MR as a comment AI draft — sends issue details to Claude, which generates customer-facing changelog entries grouped into ### Enhancements and ### Fixes, posted as a second MR comment Done label — adds rn-done to the MR when complete to prevent re-runs Setup Configure a GitLab webhook on your docs repo pointing to this workflow's URL (Merge Request events) Create two labels on your GitLab repo: rn-release-n8n (to trigger) and rn-done (auto-applied on completion) Update the RSS Read node URL to your release RSS feed Replace YOUR_PROJECT_ID in all GitLab API nodes with your docs project ID Replace YOUR_WORKSPACE in the Code nodes with your Linear workspace slug Connect Linear API, GitLab API, and Anthropic API credentials Notes Versioning assumes a vX.Y Linear label convention — adapt the Format labels node for your own scheme The AI prompt in Message a model is ready to use but can be customised to match your tone and changelog format Issues are filtered to those with Zendesk, Slack attachments, or your custom labels — adjust in Set Params

This workflow streamlines accounts receivable management by automatically monitoring invoices in Google Sheets and sending scheduled payment reminders. It is designed for businesses using Gmail and Google Sheets that need a scalable alternative to complex accounting software. How it works Watches for invoices: Triggers daily or via form submission to check for new entries. First Follow-up (Day 7): Checks payment status one week after the invoice date. If unpaid, it sends a friendly email (and optional SMS). Second Follow-up (Day 9): Re-checks status and sends a firmer reminder if funds are still not received. Final Notice (Day 12): Sends a final urgent reminder before closing the cycle. Smart Stopping: The workflow checks the 'Payment Status' column before every single message to ensure clients who have already paid are never disturbed. Setup time: About 20 minutes. Prerequisites: A Google Sheet with columns for Date, Email, and Payment Status.

Customer Feedback Automation Workflow with Webhook, OpenAI, Jira & Slack This workflow collects customer feedback from a webhook, validates the incoming data, analyzes the sentiment using OpenAI and creates Jira tasks for negative or feature-request feedback. It also generates an automated weekly summary using OpenAI and delivers it to Slack. It helps teams stay informed, skip manual reviews and act quickly on customer issues. Quick Start – Implementation Steps Set up the Webhook URL in your application to send customer feedback. Configure Slack, Jira and OpenAI credentials in n8n. Adjust sentiment rules or Jira fields if needed. Activate the workflow — you’re ready to collect and process feedback automatically. What It Does This workflow automates the entire lifecycle of customer feedback handling. When someone submits feedback, the system checks if the required information (feedback text and sentiment) is present. If the payload is invalid or incomplete, the team immediately receives a Slack notification to take action. If the feedback is valid, OpenAI analyzes the content and identifies the sentiment as positive, negative, neutral or a feature suggestion. Based on this result, the system automatically creates a Jira issue for negative feedback or feature requests, ensuring nothing important is missed. Alongside real-time processing, the workflow also compiles a weekly summary. Every week, it gathers all Jira issues created through feedback and sends them to OpenAI for summarization. The summary is then posted to Slack so the team gets a clean, easy-to-read review of customer sentiment trends. Who’s It For This workflow is ideal for: Customer support teams Product managers QA and development teams Companies collecting user feedback Businesses wanting automated sentiment analysis and reporting Requirements to Use This Workflow To fully use this workflow, you need: An n8n instance (self-hosted or cloud) A Webhook endpoint to receive customer feedback A Slack workspace with API access A Jira Software Cloud account An OpenAI API key with access to GPT-4.1 or similar Basic understanding of JSON payloads How It Works Collect Feedback – Receives customer data through an n8n webhook. Validate Payload – Checks required fields; bad input triggers Slack alerts. Determine Sentiment – Sends feedback text to OpenAI for sentiment classification. Conditional Routing – Negative or feature-request items move forward; others are ignored. Create Jira Task – Automatically logs an issue for follow-up. Weekly Summary – A scheduled trigger collects all Jira issues created during the week. Generate Report – Sends all issues to OpenAI for a clean weekly summary. Delivered to Slack – The summary is posted for the team to review. Setup Steps Import the workflow JSON file into n8n. Configure your credentials: Slack Jira OpenAI Update the webhook URL in your application. Edit Jira project ID or fields if required. Customize Slack channel IDs. Enable the schedule trigger (weekly summary). Activate the workflow. How To Customize Nodes Customize Sentiment Rules Modify the IF node that checks OpenAI output: Add new sentiment labels (e.g., “bug”, “urgent”) Adjust rules for what should create a Jira issue Customize Jira Task Fields In the Create Jira Task node, you can change: Project ID Issue type Summary and description templates Labels or assignees Customize Slack Messages Update Slack node text blocks to: Format alerts Add more details Send messages to different channels Add-Ons (Optional Enhancements) You can extend this workflow with: Email notifications for high-priority feedback Auto-reply emails to customers acknowledging their feedback Google Sheets logging for historical data Dashboard creation using Airtable or Notion Multi-language sentiment detection Auto-tagging Jira issues with sentiment categories Use Case Examples Customer Complaint Handling – Automatically detect negative feedback and create a Jira issue. Feature Request Collection – Route suggestions to the product backlog. Weekly Sentiment Reporting – Keep managers updated on trends. Slack Alerts for Bad Payloads – Notify the team when someone sends incomplete or incorrect feedback. Automated Feedback Triage – Assign tasks to specific Jira users based on sentiment or keywords. You can extend to many more such similar use cases. Troubleshooting Guide | Issue | Possible Cause | Solution | |-----------------------------|-----------------------------------------------|---------------------------------------------------| | Slack alert not sent | Wrong API credentials or channel ID | Check Slack credentials and update channel ID | | Jira issue not created | Incorrect project ID or issue type | Verify Jira configuration in n8n | | OpenAI sentiment not reading| Wrong JSON path in IF node | Re-check $json.output[0].content[0].text | | Weekly summary not generated| Schedule trigger disabled | Enable the Schedule Trigger node | | Webhook not receiving data | Application not pointing to correct URL | Verify webhook URL in your app | Need Any Help? If you need any help setting up this workflow, troubleshooting or adding custom features, our n8n experts at WeblineIndia is always here to support. We can help you automate more processes, integrate external systems or build complete workflow solutions tailored to your business.

What It Does Build your own AI Chatbot that listens, thinks, searches, and speaks — all inside n8n. This template combines Groq AI, LangChain Agent, SerpAPI, and StreamElements TTS to create a chatbot that: Understands natural language input Searches the web for real-time answers Remembers previous messages (context memory) Replies with a realistic AI voice How It Works Chat Trigger: The workflow activates whenever a new message is received. Groq AI Agent: Processes user input, performs reasoning, and integrates with SerpAPI for live web results. Memory Node: Keeps the chat context for a natural conversation flow. TTS Node: Converts AI responses into realistic voice replies using StreamElements API. Setup Steps Connect your Groq, SerpAPI, and StreamElements credentials (no coding required). Customize the chatbot behavior directly inside n8n. Deploy instantly and chat via webhook or UI widget. Use Cases Voice-enabled customer-support bots AI chat widgets for websites Personal assistants that talk and search the web

This n8n template turns raw call transcripts into clean HubSpot call logs and a single, actionable follow-up task—automatically. Paste a transcript and the contact’s email; the workflow finds the contact, summarizes the conversation in 120–160 words, proposes the next best action, and (optionally) updates missing contact fields. Perfect for reps and founders who want accurate CRM hygiene without the manual busywork. How it works A form trigger collects two inputs: Contact email Plain-text call transcript The workflow looks up the HubSpot contact by email to pull known properties. An AI agent reads the transcript (plus known fields) to: Extract participants, role, problem/opportunity, requirements, blockers, timeline, and metrics. Write a 120–160 word recap a teammate can skim. Generate one concrete follow-up task (title + body). Suggest updates for missing contact properties (city, country, job title, job function). The recap is logged to HubSpot as a completed Call engagement. The follow-up is created in HubSpot as a Task with subject and body. (Optional) The contact record is updated using AI-suggested values if the transcript clearly mentions them. How to use Connect HubSpot (OAuth2) on all HubSpot nodes. Connect OpenAI on the AI nodes. Open Form: Capture Transcript, submit the email + transcript. (Optional) In AI: Summarize Call & Draft Task, tweak prompt rules (word count, date normalization). (Optional) In Update Contact from Transcript, review the mapped fields before enabling in production. Activate the workflow and paste transcripts after each call. Requirements HubSpot** (OAuth2) for contact search, call logging, and tasks OpenAI** for summarization and task drafting Notes & customization ideas Swap the form for a Google Drive or S3 watcher to ingest saved transcripts. Add a speech-to-text step if you store audio recordings. Extend Update Contact to include additional fields (timezone, department, seniority). Post the summary to Slack or email the AE for quick handoffs. Gate updates with a confidence check, or route low-confidence changes for manual approval.

N8N Workflow: Send and Check TTS (Text-to-speech) Voice Calls with Email Verification This workflow automates a two-factor verification process using a voice call and an email. It is designed to send a text-to-speech (TTS) voice call with a verification code and, upon successful voice verification, to send an email with a second verification code. How it Works This workflow automates the process of sending voice calls for verification and combines it with email verification. It uses the ClickSend API for the voice call and an SMTP integration for sending the email. Use Cases Two-factor authentication (2FA) for user registration or login. Automated verification for phone numbers and email addresses. Building a custom verification system for web applications. Setup Instructions ClickSend API: Register on ClickSend and obtain your API Key. In the Send Voice node, create a Basic Auth credential using your ClickSend username and API Key as the password. SMTP Credentials: In the Send Email node, you must set up your SMTP credentials for the sender's email. Workflow Logic Trigger: The workflow is started by submitting a form. Set Voice Code: The workflow sets a predefined voice verification code. Send Voice Call: A voice call is made to the provided phone number using the ClickSend API, where a synthesized voice reads the code. Verify Voice Code: A form appears to prompt the user to enter the voice code they received. Conditional Check: An If node checks if the entered voice code is correct. Set Email Code & Send Email: If the voice code is correct, a second code is set, and an email is sent to the user with that code. Verify Email Code: The user is then prompted to enter the code from the email. Final Check: A final If node verifies the email code. The workflow either leads to a Success message or a Fail email code message. Node Descriptions | Node Name | Description | |-----------|-------------| | On form submission | This trigger node presents a form to the user to collect their phone number, desired voice, language, email, and name. | | Set voice code | A Set node that defines the verification code for the voice call. | | Code for voice | A Code node that adds spaces between the digits of the voice code to make it sound clearer during the call. | | Send Voice | This httpRequest node sends a POST request to the ClickSend API to initiate the TTS voice call. | | Verify voice code | A form node that prompts the user to enter the code they received via the voice call. | | Is voice code correct? | An If node that checks if the code entered by the user matches the predefined voice code. | | Set email code | A Set node that defines the verification code for the email. | | Send Email | This node uses an SMTP credential to send an email to the user with their verification code. | | Verify email code | A form node that prompts the user to enter the code they received via email. | | Is email code correct? | An If node that checks if the code entered by the user matches the predefined email code. | | Success | A form node that displays a success message upon completion of both verifications. | | Fail voice code | A form node that displays a failure message if the voice code is incorrect. | | Fail email code | A form node that displays a failure message if the email code is incorrect. | Customization Tips You can change the verification codes by modifying the values in the Set voice code and Set email code nodes. The form can be customized to change the fields, labels, and dropdown options for voice and language. The email content and subject can be customized in the Send Email node. Suggested Sticky Notes for Workflow STEP 1**: "Register here to ClickSend and obtain your API Key... In the node 'Send Voice' create a 'Basic Auth' with the username you registered and the API Key provided as your password". STEP 2**: "Set the verification code for this explanatory flow... In the node 'Send Email' set the sender". STEP 3**: "Submit the form and you will receive a call to the phone number you entered where the selected voice will tell you the content of the text you wrote". Set voice code**: "Set the code that will be spoken in the verification phone call". Set email code**: "Set the code that will be sent in the verification email". Required Files 1g8EAij2RwhNN70t_xSend_and_check_TTS_(Text-to-speech)_voice_calls_end_email_verification.json: The n8n workflow export file for this automation. Testing Tips Run the workflow and submit the form with your phone number and email. Check your phone for the voice call and listen for the code. Enter the correct voice code in the next form and submit. Check your email for the second verification code. Enter the correct email code to test the success path, or an incorrect one to test the failure path. Suggested Tags & Categories #Verification #Voice #Email #API #Authentication

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Monetize Your Private LLM Models with x402 and Ollama Self-hosting custom LLMs is becoming more popular and easier with turn-key inferencing tools like Ollama. With Ollama you can host your own proprietary models for customers in a private cloud or on your own hardware. But monetizing custom-trained, propietary models is still a challenge, requiring integrations with payment processors like Stripe, which don't support micropayments for on-demand API consumption. With this free workflow you can quickly monetize your proprietary LLM models with the x402 payment scheme in n8n with 1Shot API. Setup Steps: Authenticate the 1Shot API node against your 1Shot API business account. Point the 1Shot API simulate and execute nodes at the x402-compatible payment token you'd like to receive as payment. Configure the Ollama n8n node in the workflow (with optional authentication) to forward to your Ollama API endpoint and let users query it through an n8n webhook endpoint while paying you directly in your preferred stablecoin (like USDC). Through x402, users and AI agents can pay per-inference, whith no overhead wasted on centralized payment processors. Walkthrough Tutorial Check out the YouTube tutorial for this workflow so see the full end-to-end process.

Summarize Gmail Support Emails with Gemini and Post to Slack This workflow automatically checks your Gmail inbox for new support emails, summarizes them using Google Gemini and posts concise summaries directly into Slack. Instead of manually reading long support emails, your team can stay updated with short, actionable insights in real-time. Who’s it for Customer Support Teams** – to stay on top of support tickets without reading lengthy emails. Operations Managers** – who need quick insights on issues raised by customers. Engineering Teams** – who want alerts and summaries of support escalations in Slack. Founders/Execs** – who prefer high-level summaries rather than full email threads. How it works Gmail Trigger – Check Support Emails The workflow runs every minute to detect new incoming emails in your support inbox. Forward Email to Gemini for Summarization Extracts the email body and prepares it for the LLM model. Gemini – Summarize Support Email Google Gemini condenses the email into a short, clear summary. Slack – Post Summary to Channel The summarized text is sent to your chosen Slack channel for instant visibility. How to set up Connect your Gmail account in n8n. Configure the Gmail Trigger to check emails from your support inbox (or apply filters like subject = “Support” or label = “Support”). Add your Google Gemini API credentials in n8n. Configure Gemini with a summarization prompt (e.g., “Summarize this email in 3 bullet points”). Connect your Slack account and select the target channel. Save and activate the workflow. Requirements n8n instance** (self-hosted or cloud). Google Account** with Gmail API enabled. Google Gemini API access** (API key). Slack workspace** with a bot token and permission to post messages. How to customize Change the email filters in the Gmail Trigger (e.g., only unread emails, only with label Support). Modify the summarization style in Gemini (bullet points, short paragraph, etc.). Choose a different Slack channel for posting (e.g., #support, #alerts, #dev-team). Add additional nodes for logging into Google Sheets or creating Jira tickets. Add-ons Save original emails + summaries into Google Sheets for tracking. Create Jira or Trello tasks automatically for high-priority issues. Add a translation step if support emails arrive in multiple languages. Integrate with Zendesk or Freshdesk if you also use those tools. Integrate OpenAI LLM models. Use Case Examples Customer sends a bug report → Gemini summarizes key points → Slack post alerts dev team instantly. Support email with long back-and-forth conversation → condensed into a 3-line summary in Slack. Team lead checks Slack daily instead of logging into Gmail to stay informed. Common Troubleshooting | Issue | Possible Cause | Solution | | -------------------------------- | ------------------------------------- | ---------------------------------------------------------------- | | No emails detected | Gmail Trigger not configured properly | Check Gmail Trigger settings and labels/filters. | | Gemini not summarizing | API key missing or invalid | Re-add Gemini API credentials in n8n. | | Slack not receiving messages | Slack auth expired or wrong channel | Reconnect Slack account and verify channel ID. | | Workflow runs but nothing posted | Summarization output empty | Adjust Gemini prompt or check email format (HTML vs plain text). | 👨‍💻Need help? If you need assistance setting up or customizing this workflow, feel free to reach out WeblineIndia. We can help you: Configure Gmail filters. Optimize Gemini prompts for better summaries. Connect Slack and set up advanced alerts. Extend the workflow with Sheets, Jira or other integrations.