Automate client onboarding with GPT-4, Google Drive, ClickUp & Slack
Description This automation streamlines client onboarding by instantly processing a submitted form, extracting key details from an uploaded proposal, and using GPT-4 to generate a full onboarding task list. It then sets up the client workspace across Google Drive, ClickUp, and Slack, and sends a personalized welcome email completing in under a minute from submission. Setup Steps Connect your Google Drive, ClickUp, Slack, Gmail, and OpenAI accounts. Customize the form fields and system prompt to match your business. Test the workflow with a sample client submission to confirm all outputs. Estimated Setup Time: \~30–45 minutes for a first-time user familiar with n8n integrations.
By Muhammad BelloAutomate RSS to social media pipeline with AI, Airtable & GetLate for multiple platforms
Overview Automates your complete social media content pipeline: sources articles from Wallabag RSS, generates platform-specific posts with AI, creates contextual images, and publishes via GetLate API. Built with 63 nodes across two workflows to handle LinkedIn, Instagram, and Bluesky—with easy expansion to more platforms. Ideal for: Content marketers, solo creators, agencies, and community managers maintaining a consistent multi-platform presence with minimal manual effort. How It Works Two-Workflow Architecture: Content Aggregation Workflow Monitors Wallabag RSS feeds for tagged articles (to-share-linkedin, to-share-instagram, etc.) Extracts and converts content from HTML to Markdown Stores structured data in Airtable with platform assignment AI Generation & Publishing Workflow Scheduled trigger queries Airtable for unpublished content Routes to platform-specific sub-workflows (LinkedIn, Instagram, Bluesky) LLM generates optimized post text and image prompts based on custom brand parameters Optionally generates AI images and hosts them on Imgbb CDN Publishes via GetLate API (immediate or draft mode) Updates Airtable with publication status and metadata Key Features: Tag-based content routing using Wallabag's native system Swappable AI providers (Groq, OpenAI, Anthropic) Platform-specific optimization (tone, length, hashtags, CTAs) Modular design—duplicate sub-workflows to add new platforms in \~30 minutes Centralized Airtable tracking with 17 data points per post Set Up Steps Setup time: \~45-60 minutes for initial configuration Create accounts and get API keys (\~15 min) Wallabag (with RSS feeds enabled) GetLate (social media publishing) Airtable (create base with provided schema—see sticky notes) LLM provider (Groq, OpenAI, or Anthropic) Image service (Hugging Face, Fal.ai, or Stability AI) Imgbb (image hosting) Configure n8n credentials (\~10 min) Add all API keys in n8n's credential manager Detailed credential setup instructions in workflow sticky notes Set up Airtable database (\~10 min) Create "RSS Feed - Content Store" base Add 19 required fields (schema provided in workflow sticky notes) Get Airtable base ID and API key Customize brand prompts (\~15 min) Edit "Set Custom SMCG Prompt" node for each platform Define brand voice, tone, goals, audience, and image preferences Platform-specific examples provided in sticky notes Configure platform settings (\~10 min) Set GetLate account IDs for each platform Enable/disable image generation per platform Choose immediate publish vs. draft mode Adjust schedule trigger frequency Test and deploy Tag test articles in Wallabag Monitor the first few executions in draft mode Activate workflows when satisfied with the output Important: This is a proof-of-concept template. Test thoroughly with draft mode before production use. Detailed setup instructions, troubleshooting tips, and customization guidance are in the workflow's sticky notes. Technical Details 63 nodes: 9 Airtable operations, 8 HTTP requests, 7 code nodes, 3 LangChain LLM chains, 3 RSS triggers, 3 GetLate publishers Supports: Multiple LLM providers, multiple image generation services, unlimited platforms via modular architecture Tracking: 17 metadata fields per post, including publish status, applied parameters, character counts, hashtags, image URLs Prerequisites n8n instance (self-hosted or cloud) Accounts: Wallabag, GetLate, Airtable, LLM provider, image generation service, Imgbb Basic understanding of n8n workflows and credential configuration Time to customize prompts for your brand voice Detailed documentation, Airtable schema, prompt examples, and troubleshooting guides are in the workflow's sticky notes. Category Tags social-media-automation, ai-content-generation, rss-to-social, multi-platform-posting, getlate-api, airtable-database, langchain, workflow-automation, content-marketing
By Mikal Hayden-GatesZendesk pending ticket follow-up system with Gmail, Google Sheets & ClickUp
Description Automate Zendesk ticket follow-up management by fetching pending tickets daily, enriching and logging them into Google Sheets, creating ClickUp tasks for team reminders, and sending professional follow-up emails to customers. Keeps your support pipeline clean and ensures no pending tickets fall through the cracks. 🎫📊📧✅ What This Template Does Triggers daily (Mon–Fri at 8 PM) to check Zendesk for pending tickets. ⏰ Filters only "pending" status tickets to reduce noise. 🔍 Formats ticket data with priority, age, and attention flags. 🧠 Logs all tickets into Google Sheets for reporting and analytics. 📊 Creates ClickUp tasks for team follow-up and accountability. 📋 Generates professional HTML follow-up emails grouped by customer. 🎨 Sends emails via Gmail with ticket details and next steps. 📧 Key Benefits Ensures no pending Zendesk tickets are forgotten. ⏱️ Builds a historical log for analytics and audit trails. 🧾 Keeps your support team accountable with ClickUp tasks. ✅ Delivers personalized, branded follow-up emails to customers. 💡 Reduces manual effort in tracking and responding to tickets. 🔄 Features Schedule Trigger – Runs Mon–Fri at 8:00 PM. 🗓️ Zendesk Integration – Fetches pending tickets automatically. 🎫 Smart Data Processing – Cleans descriptions, calculates age, flags urgent tickets. ⚡ Google Sheets Logging – Maintains a structured log with Ticket ID, URL, tags, status, etc. 📈 ClickUp Tasks – Automatically creates tasks per pending ticket. 📋 Email Generation – Groups tickets per customer, builds professional HTML follow-ups. 🎨 Gmail Delivery – Sends personalized follow-ups directly to customers. 📧 Requirements n8n instance (cloud or self-hosted). Zendesk API credentials with read access. Google Sheets OAuth2 credentials with write access. ClickUp API credentials for task creation. Gmail OAuth2 credentials for sending emails. Pre-configured Google Sheet for pending ticket tracking. Target Audience Customer support teams managing Zendesk tickets. 🎧 SaaS companies wanting automated follow-ups. 🚀 CS managers ensuring accountability in ticket handling. 🛠️ SMBs reducing customer wait time with proactive follow-ups. 🏢 Remote support teams needing automated reminders and logs. 🌐 Step-by-Step Setup Instructions Connect Zendesk, Google Sheets, ClickUp, and Gmail credentials in n8n. 🔑 Update the schedule trigger (default: Mon–Fri at 8:00 PM). ⏰ Replace the Google Sheet ID with your pending ticket log sheet. 📊 Configure your ClickUp space/list IDs for task creation. 📋 Update email branding and sender address in the email generator. 🎨 Test with sample tickets to validate Sheets logging, ClickUp tasks, and Gmail delivery. ✅
By Rahul JoshiAutomate invoice processing & weekly spending reports with GPT-4 and Airtable
Invoice Automation Kit: AI-Powered Invoice Processing and Weekly Reports This n8n workflow is designed to automate invoice processing and streamline financial management. It leverages AI to extract key invoice data, validate it, and store it in Airtable. Additionally, it generates and emails weekly spending reports. Who is it for? This template is for small businesses, freelancers, or individuals looking to save time on manual invoice processing. It's ideal for anyone who wants to improve the accuracy of their financial data and maintain a clear overview of their spending. How it Works / What it Does This workflow consists of two main parts: Invoice Data Extraction and Storage: Invoice Upload Form: Upload your invoices (PDF, PNG, JPG) via an n8n form. AI-Powered Data Extraction: AI extracts key information such as vendor name, invoice date, total amount, currency, and line items (description, quantity, unit price, total) from the uploaded invoice. Data Validation: The extracted data is validated to ensure it is complete and accurate. Store in Airtable: Validated invoice data is saved in a structured format to your specified Airtable base and table. Weekly Spending Report Generation and Email: Weekly Report Schedule: Automatically triggers every Sunday at 6 PM. Fetch Weekly Invoices: Retrieves all invoices stored in Airtable within the last 7 days. AI-Powered Spending Report Generation: Based on the retrieved invoice data, AI generates a comprehensive spending report, including total spending for the week, breakdown by vendor, top 5 expenses, spending trends, and any notable observations. Send Weekly Report Email: The generated report is sent in a professional format to the configured recipient email address. How to Set Up Update Workflow Configuration Node: Replace airtableBaseId with your Airtable Base ID. Replace airtableTableId with your Airtable Table ID. Replace reportRecipientEmail with the email address that should receive the weekly reports. Airtable Credentials: Set up your Airtable Personal Access Token credentials in the Airtable nodes. OpenAI Credentials: Set up your OpenAI API key credentials in the OpenAI Chat Model nodes. Email Credentials: Configure your email sending service (e.g., SMTP) credentials in the "Send Weekly Report Email" node and update the fromEmail. Airtable Table Setup: Ensure your Airtable has a table set up with appropriate columns to store invoice data, such as "Vendor", "Invoice Date", "Total Amount", "Currency", and "Line Items". Requirements An n8n instance An OpenAI account and API key An Airtable account and Personal Access Token An email sending service (e.g., SMTP server) How to Customize the Workflow Adjust Information Extraction: Edit the prompt in the "Extract Invoice Data" node to include additional information you wish to extract. Customize Report: Adjust the prompt in the "Generate Spending Report" node to change specific analyses or formatting included in the report. Add Notifications: Incorporate notification nodes to other services like Slack or Microsoft Teams to be alerted when an invoice is uploaded or a report is ready. Modify Validation Rules: Edit the conditions in the "Validate Invoice Data" node to implement additional validation rules. Here's a visual representation of the workflow.
By 對馬 瑠斗Scrape Trustpilot reviews 📊 with ScrapegraphAI and OpenAI Reputation analysis
This workflow automates the collection, analysis, and reporting of Trustpilot reviews for a specific company using ScrapeGraphAI, transforming unstructured customer feedback into structured insights and actionable intelligence. --- Key Advantages ✅ End-to-End Automation The entire process—from scraping reviews to delivering a polished management report—is fully automated, eliminating manual data collection and analysis . ✅ Structured Insights from Unstructured Data The workflow transforms raw, unstructured review text into structured fields and standardized sentiment categories, making analysis reliable and repeatable. ✅ Company-Level Reputation Intelligence Instead of focusing on individual products, the analysis evaluates the overall brand, service quality, customer experience, and operational performance, which is critical for leadership and strategic teams. ✅ Action-Oriented Outputs The AI-generated report goes beyond summaries by: Identifying reputational risks Highlighting improvement opportunities Proposing concrete actions with priorities, effort estimates, and KPIs ✅ Visual & Executive-Friendly Reporting Automatic sentiment charts and structured executive summaries make insights immediately understandable for non-technical stakeholders. ✅ Scalable and Configurable Easily adaptable to different companies or review volumes Page limits and batching protect against rate limits and excessive API usage ✅ Cross-Team Value The output is tailored for multiple internal teams: Management Marketing Customer Support Operations Product & UX --- Ideal Use Cases Brand reputation monitoring Voice-of-the-customer programs Executive reporting Customer experience optimization Competitive benchmarking (by reusing the workflow across brands) --- How It Works This workflow automates the complete process of scraping Trustpilot reviews, extracting structured data, analyzing sentiment, and generating comprehensive reports. The workflow follows this sequence: Trigger & Configuration: The workflow starts with a manual trigger, allowing users to set the target company URL and the number of review pages to scrape. Review Scraping: An HTTP request node fetches review pages from Trustpilot with pagination support, extracting review links from the HTML content. Review Processing: The workflow processes individual review pages in batches (limited to 5 reviews per execution for efficiency). Each review page is converted to clean markdown using ScrapegraphAI. Data Extraction: An information extractor using OpenAI's GPT-4.1-mini model parses the markdown to extract structured review data including author, rating, date, title, text, review count, and country. Sentiment Analysis: Another OpenAI model performs sentiment classification on each review text, categorizing it as Positive, Neutral, or Negative. Data Aggregation: Processed reviews are collected and compiled into a structured dataset. Analytics & Visualization: A pie chart is generated showing sentiment distribution A comprehensive reputation analysis report is created using an AI agent that evaluates company-level insights, recurring themes, and provides actionable recommendations Reporting & Delivery: The analysis is converted to HTML format and sent via email, providing stakeholders with immediate insights into customer feedback and company reputation. Set Up Steps To configure and run this workflow: Credential Setup: Configure OpenAI API credentials for the chat models and information extraction Set up ScrapeGraphAI credentials for webpage-to-markdown conversion Configure Gmail OAuth2 credentials for email notifications Company Configuration: In the "Set Parameters" node, update company_id to the target Trustpilot company URL Adjust max_page to control how many review pages to scrape Review Processing Limits: The "Limit" node restricts processing to 5 reviews per execution to manage API costs and processing time Adjust this value based on your needs and OpenAI usage limits Email Configuration: Update the "Send a message" node with the recipient email address Customize the email subject and content as needed Analysis Customization: Modify the prompt in the "Company Reputation Analyst" node to tailor the report format Adjust sentiment analysis categories if different classification is needed Execution: Click "Test workflow" to execute the manual trigger Monitor execution in the n8n editor to ensure all API calls succeed Check the configured email inbox for the generated report Note: Be mindful of API rate limits and costs associated with OpenAI and ScrapegraphAI services when processing large numbers of reviews. The workflow includes a 5-second delay between paginated requests to comply with Trustpilot's terms of service. --- 👉 Subscribe to my new YouTube channel. Here I’ll share videos and Shorts with practical tutorials and FREE templates for n8n. [](https://youtube.com/@n3witalia) --- Need help customizing? Contact me for consulting and support or add me on Linkedin.
By Davide