by Robin Bonduelle
Template presentation This template generates a sales follow-up presentation in Google Slides after a sales call recorded in Claap. The workflow is simplified to showcase the main use case. You can customize and enrich this workflow by connecting to the CRM, researching data online or adding more files in the presentation. The presentation template used in this workflow is available here. Workflow configuration Create a webhook in Claap, by following this article. Edit the labels that trigger the workflow and route on the relevant presentation. Fill your Open AI credentials by creating an API Key in OpenAI Platform Edit the presentation personalization details (user set as editor, content, title) Fill your Slack credentials by following steps in this video.
by AppUnits AI
Generate Invoices and Send Reminders for Customers with Jotform and QuickBooks This workflow automates the entire process of receiving a product/service order, checking or creating a customer in QuickBooks Online (QBO), generating an invoice, emailing it — all triggered by a form submission (via Jotform), and sending invoice reminders. How It Works Receive Submission Triggered when a user submits a form. Collects data like customer details, selected product/service, etc. Check If Customer Exists Searches QBO to determine if the customer already exists. If Customer Exists:* *Update** customer details (e.g., billing address). If Customer Doesn’t Exist:* *Create** a new customer in QBO. Get The Item Retrieves the selected product or service from QBO. Create The Invoice Generates a new invoice for the customer using the item selected. Send The Invoice Automatically sends the invoice via email to the customer. Store The Invoice In DB Stores the needed invoice details in the DB. Send Reminders Every day at 8 AM, the automation checks each invoice to decide whether to: send a reminder email, skip and send it later, or delete the invoice from the DB (if it's paid or all reminders have been sent). Who Can Benefit from This Workflow? Freelancers** Service Providers** Consultants & Coaches** Small Businesses** E-commerce or Custom Product Sellers** Requirements Jotform webhook setup, more info here QuickBooks Online credentials, more info here Email setup, update email nodes (Send reminder email & Send reminders sent summary) Create data table with the following columns: invoiceId (string) remainingAmount (number) currency (string) remindersSent (number) lastSentAt (date time) Update Add reminders config node so update the data table id and intervals in days (default is after 2 days, then after 3 days and finally after 5 days ) LLM model credentials
by AppUnits AI
Generate Invoices and Send Reminders for Customers with Jotform and Xero This workflow automates the entire process of receiving a product/service order, checking or creating a customer in Xero, generating an invoice, emailing it — all triggered by a form submission (via Jotform), and sending invoice reminders. How It Works Receive Submission Triggered when a user submits a form. Collects data like customer details, selected product/service, etc. Create/Update The Customer Creates/Updates the customer. Create The Invoice Generates a new invoice for the customer using the item selected. Send The Invoice Automatically sends the invoice via email to the customer. Store The Invoice In DB Stores the needed invoice details in the DB. Send Reminders Every day at 8 AM, the automation checks each invoice to decide whether to: send a reminder email, skip and send it later, or delete the invoice from the DB (if it's paid or all reminders have been sent). Who Can Benefit from This Workflow? Freelancers** Service Providers** Consultants & Coaches** Small Businesses** E-commerce or Custom Product Sellers** Requirements Jotform webhook setup, more info here Xero credentials, more info here Make sure that products/services values in Jotform are exactly the same as your item Code in your Xero account Email setup, update email nodes (Send email & Send reminder email & Send reminders sent summary) Create data table with the following columns: invoiceId (string) remainingAmount (number) currency (string) remindersSent (number) lastSentAt (date time) Update Add reminders config node so update the data table id and intervals in days (default is after 2 days, then after 3 days and finally after 5 days ) LLM model credentials
by Robert Breen
Send VAPI voice requests into n8n with memory and OpenAI for conversational automation This template shows how to capture voice interactions from VAPI (Voice AI Platform), send them into n8n via a webhook, process them with OpenAI, and maintain context with memory. The result is a conversational AI agent that responds back to VAPI with short, business-focused answers. ✅ What this template does Listens for POST requests from VAPI containing the session ID and user query Extracts session ID and query for consistent conversation context Uses OpenAI (GPT-4.1-mini) to generate conversational replies Adds Memory Buffer Window so each VAPI session maintains history Returns results to VAPI in the correct JSON response format 👤 Who’s it for Developers and consultants building voice-driven assistants Businesses wanting to connect VAPI calls into automation workflows Anyone who needs a scalable voice → AI → automation pipeline ⚙️ How it works Webhook node catches incoming VAPI requests Set node extracts session_id and user_query from the request body OpenAI Agent generates short, conversational replies with your business context Memory node keeps conversation history across turns Respond to Webhook sends results back to VAPI in the required JSON schema 🔧 Setup instructions Step 1: Create Function Tool in VAPI In your VAPI dashboard, create a new Function Tool Name: send_to_n8n Description: Send user query and session data to n8n workflow Parameters: session_id (string, required) – Unique session identifier user_query (string, required) – The user’s question Server URL: https://your-n8n-instance.com/webhook/vapi-endpoint Step 2: Configure Webhook in n8n Add a Webhook node Set HTTP method to POST Path: /webhook/vapi-endpoint Save, activate, and copy the webhook URL Use this URL in your VAPI Function Tool configuration Step 3: Create VAPI Assistant In VAPI, create a new Assistant Add the send_to_n8n Function Tool Configure the assistant to call this tool on user requests Test by making a voice query — you should see n8n respond 📦 Requirements An OpenAI API key stored in n8n credentials A VAPI account with access to Function Tools A self-hosted or cloud n8n instance with webhook access 🎛 Customization Update the system prompt in the OpenAI Agent node to reflect your brand’s voice Swap GPT-4.1-mini for another OpenAI model if you need longer or cheaper responses Extend the workflow by connecting to CRMs, Slack, or databases 📬 Contact Need help customizing this (e.g., filtering by campaign, connecting to CRMs, or formatting reports)? 📧 rbreen@ynteractive.com 🔗 https://www.linkedin.com/in/robert-breen-29429625/ 🌐 https://ynteractive.com
by Easy8.ai
Automated Helpdesk Ticket Alerts to Microsoft Teams from Easy Redmine Intro/Overview This workflow automatically posts a Microsoft Teams message whenever a new helpdesk ticket is created in Easy Redmine. It’s perfect for IT teams who want real-time visibility into new issues without constantly checking ticket queues or inboxes. By integrating Easy Redmine with Teams, this setup ensures tickets are discussed and resolved faster, improving both response and resolution times. How it works Catch Easy Webhook – New Issue Created Triggers whenever Easy Redmine sends a webhook for a newly created ticket. Uses the webhook URL generated from Easy Redmine’s webhook settings. Get a new ticket by ID Fetches full ticket details (subject, priority, description) via the Easy Redmine API using the ticket ID from the webhook payload. Pick Description & Create URL to Issue Extracts the ticket description. Builds a direct link to the ticket in Easy Redmine for quick access. AI Agent – Description Processing Uses an AI model to summarize the ticket and suggest possible solutions based on the issue description. MS Teams Message to Support Channel Formats and sends the ticket details, priority, summary, and issue link into a designated Microsoft Teams channel. Uses the Teams message layout for clarity and quick scanning. How to Use Import the workflow into your n8n instance. Set up credentials: Easy Redmine API credentials with permission to read helpdesk tickets. Microsoft Teams credentials for posting messages to a channel. Configure Easy Redmine webhook To trigger on ticket creation events. Insert n8n webhook URL to your active Easy Redmine Webhook which can be created at https://easy-redmine-application.com/easy_web_hooks Adjust node settings: In the webhook node, use your Easy Redmine webhook URL. In the “Get a new ticket by ID” node, insert your API endpoint and authentication. In the Teams message node, select the correct Teams channel. Adjust timezone or scheduling if your team works across different time zones. Test the workflow by creating a sample ticket in Easy Redmine and confirming that it posts to Teams. Example Use Cases IT Helpdesk**: Notify the support team immediately when new issues are logged. Customer Support Teams**: Keep the entire team updated on urgent tickets in real time. Project Teams**: Ensure critical bug reports are shared instantly with the right stakeholders. Requirements Easy Redmine application Easy Redmine technical user for API calls with “read” permissions on tickets Microsoft Teams technical user for API calls with “post message” permissions Active n8n instance Customization Change the AI prompt to adjust how summaries and solutions are generated. Modify the Teams message format (e.g., bold priority, add emojis for urgency). Add filters so only high-priority or specific project tickets trigger notifications. Send alerts to multiple Teams channels based on ticket type or project. Workflow Improvement Suggestions: Rename nodes for clarity (e.g., “Fetch Ticket Details” instead of “get-one-issue”). Ensure no private ticket data is exposed beyond intended recipients. Add error handling for failed API calls to avoid missing ticket alerts.
by Max aka Mosheh
How it works • Webhook triggers from content creation system in Airtable • Downloads media (images/videos) from Airtable URLs • Uploads media to Postiz cloud storage • Schedules or publishes content across multiple platforms via Postiz API • Tracks publishing status back to Airtable for reporting Set up steps • Sign up for Postiz account at https://postiz.com/?ref=max • Connect your social media channels in Postiz dashboard • Get channel IDs and API key from Postiz settings • Add Postiz API key to n8n credentials (Header Auth) • Update channel IDs in "Prepare for Publish" node • Connect Airtable with your content database • Customize scheduling times per platform as needed • Full setup details in workflow sticky notes
by Trung Tran
AI-Powered AWS S3 Manager with Audit Logging in n8n (Slack/ChatOps Workflow) > This n8n workflow empowers users to manage AWS S3 buckets and files using natural language via Slack or chat platforms. Equipped with an OpenAI-powered Agent and integrated audit logging to Google Sheets, it supports operations like listing buckets, copying/deleting files, managing folders, and automatically records every action for compliance and traceability. 👥 Who’s it for This workflow is built for: DevOps engineers who want to manage AWS S3 using natural chat commands. Technical support teams interacting with AWS via Slack, Telegram, etc. Automation engineers building ChatOps tools. Organizations that require audit logs for every cloud operation. Users don’t need AWS Console or CLI access — just send a message like “Copy file from dev to prod”. ⚙️ How it works / What it does This workflow turns natural chat input into automated AWS S3 actions using an OpenAI-powered AI Agent in n8n. 🔁 Workflow Overview: Trigger: A user sends a message in Slack, Telegram, etc. AI Agent: Interprets the message Calls one of 6 S3 tools: ListBuckets ListObjects CopyObject DeleteObject ListFolders CreateFolder S3 Action: Performs the requested AWS S3 operation. Audit Log: Logs the tool call to Google Sheets using AddAuditLog: Includes timestamp, tool used, parameters, prompt, reasoning, and user info. 🛠️ How to set up Step-by-step Setup: Webhook Trigger Slack, Telegram, or custom chat platform → connects to n8n. OpenAI Agent Model: gpt-4 or gpt-3.5-turbo Memory: Simple Memory Node Prompt: Instructs agent to always follow tool calls with an AddAuditLog call. AWS S3 Nodes Configure each tool with AWS credentials. Tools: getAll: bucket getAll: file copy: file delete: file getAll: folder create: folder Google Sheets Node Sheet: AWS S3 Audit Logs Operation: Append or Update Row Columns (must match input keys): timestamp, tool, status, chat_prompt, parameters, user_name, tool_call_reasoning Agent Tool Definitions Include AddAuditLog as a 7th tool. Agent calls it immediately after every S3 action (except when logging itself). ✅ Requirements [ ] n8n instance with AI Agent feature [ ] OpenAI API Key [ ] AWS IAM user with S3 access [ ] Google Sheet with required columns [ ] Chat integration (Slack, Telegram, etc.) 🧩 How to customize the workflow | Feature | Customization Tip | |----------------------|--------------------------------------------------------------| | 🌎 Multi-region S3 | Let users include region in the message or agent memory | | 🛡️ Restricted actions| Use memory/user ID to limit delete/copy actions | | 📁 Folder filtering | Extend ListObjects with prefix/suffix filters | | 📤 Upload file | Add PutObject with pre-signed URL support | | 🧾 Extra logging | Add IP, latency, error trace to audit logs | | 📊 Reporting | Link Google Sheet to Looker Studio for audit dashboards | | 🚨 Security alerts | Notify via Slack/Email when DeleteObject is triggered |
by Omer Fayyaz
This n8n template implements an AI-Powered Chatbot for Automated WHMCS Support Ticket Creation Who's it for This template is designed for web hosting companies, domain registrars, and IT service providers who want to automate their customer support ticket creation process. It's perfect for businesses looking to streamline support operations by automatically converting customer chat conversations into structured WHMCS support tickets while maintaining professional, empathetic customer interactions. How it works / What it does This workflow creates an AI-powered chatbot that automatically converts customer chat messages into structured support tickets within the WHMCS system. The AI agent automatically: Receives customer queries through a webhook endpoint Processes natural language requests using Google Gemini AI Extracts key information from customer conversations: Customer name and email Issue description and subject Appropriate support department Priority level (Low, Medium, High) Fetches valid support departments from WHMCS using the GetSupportDepartments API Creates structured support tickets via WHMCS OpenTicket API Maintains conversation context with session-based memory Provides professional responses while gathering necessary information The system ensures 100% accuracy by always mapping to valid WHMCS departments and never inventing ticket fields, maintaining data integrity and proper ticket routing. How to set up 1. Configure Google Gemini API Set up your Google Gemini API credentials in the Google Gemini Chat Model node Ensure you have sufficient API quota for your expected usage 2. Configure WHMCS API Update the WHMCS API credentials in both HTTP Request Tool nodes Replace https://WHMCS_URL.com/includes/api.php with your actual WHMCS API endpoint Ensure your WHMCS API has the necessary permissions for: GetSupportDepartments action OpenTicket action 3. Customize AI Agent Behavior Modify the system message in the AI Agent node to match your company's tone and policies Adjust the agent's response style and ticket creation workflow Customize department mapping and priority assignment logic 4. Set up the Webhook The workflow creates a unique webhook endpoint for receiving customer queries Use this endpoint URL in your customer-facing chat interface Ensure proper security measures for webhook access 5. Test Department Integration Verify that the GetSupportDepartments API call returns your actual support departments Test ticket creation with various customer scenarios Ensure proper error handling for API failures Requirements Google Gemini API account** with appropriate credentials n8n instance** (self-hosted or cloud) WHMCS installation** with API access enabled Support department structure** already configured in WHMCS Customer chat interface** or messaging system How to customize the workflow Modify AI Agent Behavior Edit the system message in the AI Agent node to change the bot's personality and response style Adjust ticket creation logic and required field validation Customize priority assignment algorithms based on keywords or urgency indicators Enhance Ticket Creation Add custom fields to the ticket creation process Implement ticket categorization based on conversation content Add automatic assignment to specific support staff members Improve Customer Experience Add ticket confirmation and tracking information Implement follow-up message scheduling Add customer satisfaction surveys after ticket resolution Security Enhancements Implement API key rotation and monitoring Add request validation and sanitization Set up usage analytics and abuse prevention Key Features Automatic ticket creation** from natural language conversations Intelligent department mapping** using WHMCS API Professional customer interaction** with empathetic responses Session-based memory** for contextual conversations Structured ticket data** with proper validation Priority assignment** based on conversation analysis Scalable webhook architecture** for high-volume usage Direct WHMCS integration** for seamless ticket management Use Cases 24/7 automated support ticket creation** for web hosting companies Customer service automation** with human-like interaction Support team efficiency** by reducing manual ticket entry Consistent ticket formatting** across all customer interactions Improved response times** through immediate ticket creation Customer self-service** with professional guidance Chat Session Management The workflow automatically manages chat sessions with the following features: Unique Session IDs** for each customer conversation Automatic information extraction** from customer messages Conversation history tracking** with chronological message storage Session persistence** across multiple interactions Contextual responses** based on conversation history Example Customer Interactions The AI agent can handle various customer scenarios: Technical Issues**: "My website is down" → Creates ticket in Technical Support department Billing Questions**: "I need help with my invoice" → Creates ticket in Billing department Domain Services**: "I want to transfer my domain" → Creates ticket in Domain Services department General Support**: "I have a question about my hosting plan" → Creates ticket in General Support department Ticket Creation Process The workflow follows a structured approach: Information Gathering: The AI agent identifies missing required information (email, name, etc.) Department Selection: Fetches available departments from WHMCS and maps customer needs appropriately Priority Assessment: Determines ticket priority based on urgency indicators in the conversation Ticket Creation: Generates a well-structured ticket with clear subject and detailed message Confirmation: Provides customer with ticket creation confirmation and next steps This template transforms your web hosting business by providing instant, automated support ticket creation while maintaining the personal touch that customers expect from professional service providers. The AI agent becomes an extension of your support team, handling routine inquiries and ensuring no customer request goes unaddressed.
by Omer Fayyaz
This n8n template implements a Customer Support Chat Agent for Web Hosting Companies with Google Gemini, Google Sheets Knowledge base and WHMCS API to Check Domain Name Availability Who's it for This template is designed for web hosting companies, domain registrars, and IT service providers who want to automate their customer support with an AI-powered chatbot. It's perfect for businesses looking to provide 24/7 customer assistance for hosting plans, domain services, and technical support while maintaining a professional, human-like interaction experience. How it works / What it does This workflow creates an AI-powered customer support chatbot that provides comprehensive assistance for web hosting and domain services. The AI agent (named Matt) automatically: Receives customer queries through a webhook endpoint Captures customer information (name and email) at the start of each session Processes natural language requests using Google Gemini AI Accesses real-time information from multiple Google Sheets knowledge bases: Shared Hosting Plans (pricing, features, specifications) Domain Prices (registration, transfer, renewal costs) Hosting Features (technical capabilities and specifications) FAQs (common questions and answers) Payment Method Details (accepted payment options) Company Offerings (available products and services) Checks domain availability via WHMCS API integration Provides accurate, contextual responses based on the knowledge base Maintains conversation history with session-based memory Stores complete chat sessions in Google Sheets for analysis and follow-up The system ensures 100% accuracy by only providing information that exists in the knowledge base, eliminating guesswork and maintaining brand consistency. How to set up 1. Configure Google Sheets Knowledge Base Set up a Google Sheets document with the following sheets: Shared_Hosting_Plans: Hosting plan details, pricing, and specifications Domain_Prices: Domain registration and renewal pricing Hosting_Features: Technical features and capabilities FAQs: Frequently asked questions and answers Payment_Method_Details: Payment options and instructions Offerings: Available products and services Update the Google Sheets credentials in each tool node 2. Set up Google Gemini API Configure your Google Gemini API credentials in the Google Gemini Chat Model node Ensure you have sufficient API quota for your expected usage 3. Configure WHMCS API (Optional) Replace Your_WHMCS_Identifier with your actual WHMCS API identifier Replace Your_WHMCS_Secret with your actual WHMCS API secret Update https://your_whmcs_url.com/includes/api.php with your WHMCS domain This enables domain availability checking for customers 4. Set up Chat Storage Create a Google Sheet for storing chat inquiries Update the document ID and credentials in the Chat_Inquiries node This will automatically store all customer conversations for analysis 5. Deploy the Webhook The workflow creates a unique webhook endpoint for receiving customer queries Use this endpoint URL in your customer-facing application or chat interface Requirements Google Sheets account** with the knowledge base set up Google Gemini API account** with appropriate credentials n8n instance** (self-hosted or cloud) WHMCS installation** (optional, for domain availability checking) Web hosting or domain services business** How to customize the workflow Modify AI Agent Behavior Edit the system message in the AI Agent node to change the bot's personality and response style Adjust response length and tone to match your brand voice Customize the agent's name (currently "Matt") Enhance Knowledge Base Add more Google Sheets tools for additional information sources Include product catalogs, pricing tables, or technical documentation Add multi-language support for international customers Improve Customer Experience Add domain suggestion algorithms based on customer input Integrate with your existing customer database for personalized recommendations Add notification systems (email, Slack, SMS) for high-value inquiries Security Enhancements Implement API key rotation and monitoring Add request validation and sanitization Set up usage analytics and abuse prevention Key Features Real-time information access** from Google Sheets knowledge base AI-powered natural language processing** for customer queries Session-based memory** for contextual conversations Automatic domain availability checking** via WHMCS API Professional, customer-focused responses** that maintain brand standards Complete chat history storage** for analysis and follow-up Scalable webhook architecture** for high-volume usage Multi-tool integration** for comprehensive customer support Use Cases 24/7 customer support automation** for web hosting companies Sales team assistance** with real-time product information Customer self-service portals** with intelligent assistance Lead generation** through proactive service recommendations Customer retention** via improved support experience Support ticket reduction** by handling common queries automatically Chat Session Management The workflow automatically manages chat sessions with the following features: Unique Session IDs** for each customer conversation Automatic customer information capture** (name and email) Conversation history tracking** with chronological message storage Session persistence** across multiple interactions Data export** to Google Sheets for analysis and follow-up Example Customer Interactions The AI agent can handle various customer scenarios: Hosting Plan Inquiries**: Detailed information about shared hosting plans, features, and pricing Domain Services**: Domain availability checking, pricing, and registration guidance Technical Support**: Feature explanations, setup guidance, and troubleshooting Payment Information**: Accepted payment methods and transaction processes General Support**: Company information, service offerings, and FAQ responses This template transforms your web hosting business by providing instant, accurate customer support while maintaining the personal touch that customers expect from professional service providers. The AI agent becomes an extension of your support team, handling routine inquiries and allowing human agents to focus on complex technical issues.
by Asfandyar Malik
Short Description Automatically scrape new Upwork job listings, save them to Google Sheets, and get real-time WhatsApp alerts when new matching jobs appear. This workflow helps freelancers and agencies track new opportunities instantly — without checking Upwork manually. Who’s it for For freelancers, agencies, and automation enthusiasts who want to monitor Upwork jobs automatically and receive instant notifications for relevant projects. How it works This workflow connects with RapidAPI to fetch new Upwork job listings, filters relevant ones, stores them in a Google Sheet, and sends WhatsApp alerts for matching results. It includes: Trigger node** for scheduled or webhook-based execution HTTP Request node** connected to RapidAPI for scraping Google Sheets node** to store job data Filter (IF) node** to select relevant jobs WhatsApp API node** to send alerts automatically How to set up Get an API key from RapidAPI and subscribe to an Upwork scraper API. Create a Google Sheet with columns like Title, Budget, Category, Link, and Description. Connect your Google account to n8n using Google Sheets credentials. Set up your WhatsApp API endpoint (e.g., via Waha API or WhatsApp Cloud API). Paste your API keys into the HTTP Request nodes and test the workflow. Schedule the workflow to run automatically (e.g., every hour or once daily). Requirements RapidAPI account (for Upwork scraper API) Google Sheets account WhatsApp API access (Waha / Cloud API) n8n cloud or self-hosted instance How to customize You can modify this workflow to: Track specific job categories or keywords (e.g., “automation”, “AI”, “n8n”) Send alerts to Telegram, Discord, or Slack instead of WhatsApp Add budget or client rating filters for higher-quality job leads Connect it with Airtable or Notion for advanced job tracking
by Roni Bandini
How it works This template waits for an external button to be pressed via webhook, then reads a Google Sheet with pending shipments. The sheet contains the columns: idEnvio, fechaOrden, nombre, direccion, detalle, and enviado. It determines the next shipment using Google Gemini Flash 2.5, considering not only the date but also the customer’s comments. Once the next shipment is selected, the column “enviado” is updated with an X, and the shipping information is forwarded to Unihiker’s n8n Terminal. Setup Create a new Google Sheet and name it "Shipping". Add the following column headers in the first row: idEnvio, fechaOrden, nombre, direccion, detalle, and enviado. Connect your Google Sheets and Google Gemini credentials. In your n8n workflow, select the Shipping sheet in the Google Sheets node. Copy the webhook URL and paste it into the .ino code for your Unihiker n8n Terminal. 🚀
by Open Paws
📌 Who’s it for This template is designed for campaigners, researchers, and organizers who need to enrich spreadsheets of contacts with publicly available social media profiles. Ideal for advocacy campaigns, outreach, or digital organizing where fast, scalable people lookup is needed. ⚙️ What it does This workflow scans a Google Sheet for rows marked as unanalysed ("Analysed?" = false), sends each contact to a dedicated AI-powered research agent, and returns structured public profile links across major platforms like: Twitter/X LinkedIn Facebook Instagram GitHub TikTok YouTube Reddit Threads Medium Substack And more (18+ total) It processes one contact per run for clarity and stability, appending the results back to the original Google Sheet. 🛠️ How to set it up Copy the Google Sheet template → This sheet includes sample columns and headers for contacts and social profile fields. Paste your contact list at the end of the sheet. For each new contact, make sure the "Analysed?" column is set to false. Clone this workflow and the AI Research Agent subworkflow. Connect your Google Sheets account in n8n. Update the workflow with your sheet ID and sheet name (Sheet1 by default). Trigger the workflow on a schedule (e.g. every 15 minutes) or run it manually. ✅ Requirements Google Sheets integration** set up in n8n Access to this AI research subworkflow OpenRouter API key n8n (self-hosted or cloud) 🧩 How to customize the workflow Modify the research agent to prioritize specific platforms or return only verified profiles. Add more profile columns to the Google Sheet and schema to match your custom fields. Add logic to send alerts (email, Slack, etc.) for specific contacts. Use an n8n webhook instead of a schedule to run the process on demand. Use a loop over all items to process all rows sequentially (only recommended for small datasets due to memory constraints)