by Angel Menendez
CallForge - AI Gong Sales Call Processor Streamline your sales call analysis with CallForge, an automated workflow that extracts, enriches, and refines Gong.io call data for AI-driven insights. Who is This For? This workflow is designed for: ✅ Sales teams looking to automate sales call insights. ✅ Revenue operations (RevOps) professionals optimizing call data processing. ✅ Businesses using Gong.io to analyze and enhance sales call transcripts. What Problem Does This Workflow Solve? Manually analyzing sales calls is time-consuming and prone to inconsistencies. While Gong provides raw call data, interpreting these conversations and improving AI-generated summaries can be challenging. With CallForge, you can: ✔️ Automate transcript extraction from Gong.io. ✔️ Enhance AI insights by adding product and competitor data. ✔️ Reduce errors from AI-generated summaries by correcting mispronunciations. ✔️ Eliminate duplicate calls to prevent redundant processing. What This Workflow Does 1. Extracts Gong Call Data Retrieves call recordings, metadata, meeting links, and duration from Gong. 2. Removes Duplicate Entries Queries Notion** to ensure that already processed calls are not duplicated. 3. Enriches Call Data Fetches integration details** from Google Sheets. Retrieves competitor insights** from Notion. Merges data** to provide AI with a more comprehensive context. 4. Prepares AI-Friendly Transcripts Cleans up transcripts** for structured AI processing. Reduces prompt complexity** for more accurate OpenAI outputs. 5. Sends Processed Data to an AI Call Processor Delivers the cleaned and enriched transcript** to an AI-powered workflow for generating structured call summaries. How to Set Up This Workflow 1. Connect Your APIs 🔹 Gong API Access – Set up your Gong API credentials in n8n. 🔹 Google Sheets Credentials – Provide API access for retrieving integration data. 🔹 Notion API Setup – Connect Notion to fetch competitor insights and store processed data. 🔹 AI Processing Workflow – Ensure an OpenAI-powered workflow is in place for structured summaries. CallForge - 01 - Filter Gong Calls Synced to Salesforce by Opportunity Stage CallForge - 02 - Prep Gong Calls with Sheets & Notion for AI Summarization CallForge - 03 - Gong Transcript Processor and Salesforce Enricher CallForge - 04 - AI Workflow for Gong.io Sales Calls CallForge - 05 - Gong.io Call Analysis with Azure AI & CRM Sync CallForge - 06 - Automate Sales Insights with Gong.io, Notion & AI CallForge - 07 - AI Marketing Data Processing with Gong & Notion CallForge - 08 - AI Product Insights from Sales Calls with Notion 2. Customize to Fit Your Needs 💡 Modify Data Sources – Update connections if using a different CRM, database, or analytics tool. 💡 Adjust AI Processing Logic – Optimize transcript formatting based on your preferred AI model. 💡 Expand Data Enrichment – Integrate CRM data, industry benchmarks, or other insights. Why Use CallForge? By automating Gong call processing, CallForge empowers sales teams to: 📈 Gain valuable AI-driven insights from calls. ⚡ Speed up decision-making with cleaner, structured data. 🛠 Improve sales strategies based on enriched, accurate transcripts. 🚀 Start automating your Gong call analysis today!
by Jimleuk
This n8n workflow assists property managers and surveyors by reducing the time and effort it takes to complete property inventory surveys. In such surveys, articles and goods within a property may need to be captured and reported as a matter of record. This can take a sizable amount of time if the property or number of items is big enough. Our solution is to delegate this task to a capable AI Agent who can identify and fill out the details of each item automatically. How it works An AirTable Base is used to capture just the image of an item within the property Our workflow monitoring this AirTable Base sends the photo to an AI image recognition model to describe the item for purpose of identification. Our AI agent uses this description and the help of Google's reverse image search in an attempt to find an online product page for the item. If found, the product page is scraped for the item's specifications which are then used to fill out the rest of the details of the item in our Airtable. Requirements Airtable for capturing photos and product information OpenAI account to for image recognition service and AI for agent SerpAPI account for google reverse image search. Firecrawl.dev account for webspacing. Customising this workflow Try building an internal inventory database to query and integrate into the workflow. This could save on costs by avoiding fetching new each time for common items.
by Arthur Braghetto
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Your n8n Command Center in a Telegram Chat Remotely manage and operate your n8n instance from Telegram with powerful admin commands. This workflow connects your n8n instance with a Telegram Bot, giving you remote control over key admin operations through simple chat commands. 📱 You can List your workflows (workflows) Execute a workflow (execute [name]) Activate/deactivate workflows (activate [name], deactivate [name]) List past executions (executions [name]) Permanently delete archived workflows (cleanup) Create backups of all your workflows and credentials (backup) Get help (help) Get notified when a workflow fails and when n8n instance starts. This is especially useful for self-hosted instances when you want quick access to your automation environment from your mobile device. 📌 Notes backup** only works on self-hosted setups. execute, **activate, deactivate, and executions require the workflow name as argument. Workflows must contain the appropriate trigger nodes to be executed or activated. Commands and arguments are not case sensitive, there is no need to prefix with slash and spaces in the argument name are supported. ⚙️ Setup Create your credentials for Telegram API and n8n API. Edit all Telegram and n8n nodes. Select your credentials on them. On telegram nodes provide your chatid. Detailed step-by-step instructions are available in the workflow notes. In each workflow that fails and you want to receive a warning, configure this workflow as Error Workflow in its settings.
by Angel Menendez
Enhance Security Operations with the Venafi Slack CertBot! Venafi Presentation - Watch Video Our Venafi Slack CertBot is strategically designed to facilitate immediate security operations directly from Slack. This tool allows end users to request Certificate Signing Requests that are automatically approved or passed to the Secops team for manual approval depending on the Virustotal analysis of the requested domain. Not only does this help centralize requests, but it helps an organization maintain the security certifications by allowing automated processes to log and analyze requests in real time. Workflow Highlights: Interactive Modals**: Utilizes Slack modals to gather user inputs for scan configurations and report generation, providing a user-friendly interface for complex operations. Dynamic Workflow Execution**: Integrates seamlessly with Venafi to execute CSR generation and if any issues are found, AI can generate a custom report that is then passed to a slack teams channel for manual approval with the press of a single button. Operational Flow: Parse Webhook Data**: Captures and parses incoming data from Slack to understand user commands accurately. Execute Actions**: Depending on the user's selection, the workflow triggers other actions within the flow like automatic Virustotal Scanning. Respond to Slack**: Ensures that every interaction is acknowledged, maintaining a smooth user experience by managing modal popups and sending appropriate responses. Setup Instructions: Verify that Slack and Qualys API integrations are correctly configured for seamless interaction. Customize the modal interfaces to align with your organization's operational protocols and security policies. Test the workflow to ensure that it responds accurately to Slack commands and that the integration with Qualys is functioning as expected. Need Assistance? Explore Venafi's Documentation or get help from the n8n Community for more detailed guidance on setup and customization. Deploy this bot within your Slack environment to significantly enhance the efficiency and responsiveness of your security operations, enabling proactive management of CSR's.
by InfraNodus
The Ultimate Gmail Analysis and Visual Summarization Template This workflow showcases various useful Gmail search, filter, and AI categorization operations and generates a knowledge graph for your mail using the InfraNodus GraphRAG API, which you can use to reveal the main topics and blind spots in your correspondence. InfraNodus will then target those blind spots to generate interesting research questions for you and send the topical summary and insights via Telegram. You can also click the generated graph and explore the blind spots inside InfraNodus using the interactive visual interface: What is it useful for? Learn about advanced Gmail search, filtering, and AI categorization functions** that can be useful for your other workflows Analyze all your personal messages for the last week to get an overview of the main topics Analyze all your Sent messages to find recurrent topics and gaps and generate ideas based. on those gaps Generate ideas based on specific message filters (Personal, Promos, from a specific person, AI-defined criteria, e.g. urgency) Get an overview of an interaction with a specific person / company Get an overview of your notes Generate new ideas based on your correspondence on a certain topic (e.g. "business") Learn about various n8n nodes useful for email processing, filtering, and data conversion Never miss important topics, use AI filter to get notified of the urgent and important emails via Telegram How it works This template can be triggered in multiple ways: automatically in regular intervals (daily, weekly), manually in n8n, or via a private password-protected URL form where you can specify your search and filtering criteria When you start the workflow, you specify: your Gmail search filters (can be combined, e.g. after:2025/06/01 label:personal business to search for all emails received after 1 June 2025, filed in the Personal category containing the word "business". (optional, if empty, will retrieve all the emails or limited to the number you set in the Gmail node) Additional Gmail labels (e.g. SENT or CATEGORY_PERSONAL or your custom categories). Use the search filter for faster processing (e.g. prefer label:person to CATEGORY_PERSONAL, but labels can be useful for additional filtering for your search queries) (optional, if empty, will retrieve all the emails) AI filtering criteria** — set an additional classification criteria used to filter out the emails, e.g. "Only the urgent, personal emails" — in that case, AI classification node working with Google's Gemini AI will be activated and will only pass through the email based on the criteria you specify. Whether you want to build a text graph or a social graph — see the workflow for detailed explanation of each Use snippets of emails (default) or full text (for thorough analysis). We prefer snippets as it's faster and your graph context doesn't get biased towards longer emails this way. Once you set up your search parameters in Steps 1 and 2, the template will follow the following steps: Step 3 — retrieve Google emails that satisfy your filter criteria. Filter them by additional labels provided if applicable. Step 4 - if the user chooses to analyze full text, use additional Gmail node that retrieves the full text of the email message Step 5 — if AI filter rule is provided, use the AI Classifier node with Google Gemini Pro 2.5 model to classify the email based on the rule provided. Bypass if empty. Step 6 - format the text or the email snippets to add the sender meta-data and category and to prepare to submit to InfraNodus Step 7 - submit the data to the InfraNodus HTTP graphAndEntries endpoint and generate a knowledge graph Step 8 - access this graph via the graphAndAdvice endpoint) and generate a topical summary based on the GraphRAG representation and insight questions bridging the gaps identified. Send the results via a Telegram bot. We use Telegram, because it takes only 30 seconds to set up a bot with an API, unlike Discord or Slack, which is long and cumbersome to set up. You can also attach a Gmail send node and generate an email instead. How to use You need an InfraNodus GraphRAG API account and key to use this workflow. Create an InfraNodus account Get the API key at https://infranodus.com/api-access and create a Bearer authorization key for the InfraNodus HTTP nodes. Add this Authorization code in Steps 7 and 8 of the workflow. Come up with the name of the graph and change it in the HTTP InfraNodus nodes in the steps 7 and 8 and also in the Telegram nodes that send a link to the graph. For additional settings you can use in the HTTP InfraNodus nodes, see the InfraNodus access points page. Authorize your Gmail account for Steps 2 and 3 Gmail nodes. The easiest way to set it up is to open a free Google Console API account and to create an OAuth access point for n8n. You can then reuse it with other Google services like Google Sheets, Drive, etc. So it's a useful thing to have in general. Set up the Gemini AI API key using the instructions in the Step 5 Gemini AI node. Set up the Telegram node bot for the Step 8. It takes only 30 seconds: just go to @botfather and type in /newbot and you'll have an API key ready. To get the conversation ID, follow the n8n / Telegram instructions in the node itself. Once everything is ready, try to run the default automated workflow to test if everything works well, then use the Form for playing around with specific filters that you may find useful. Requirements An InfraNodus account and API key An Google Cloud API OAuth client and key for Gmail access A Gemini AI API key A Telegram bot API key FAQ 1. What's the best search query to use? I personally like starting with analyzing the messages Gmail tags as "personal" from the last week (using the after:2025/05/28 label:personal search query) using the social graph settings. It helps me see who I interacted with, what it was about, and gives me a good bird's eye view into my last week's interactions, helping me see if I didn't miss anything. I also find it useful to analyze the sent messages (using the after:2025/05/28 label:sent search filter or SENT category filter) as it helps me see what I was writing about recently and understand some recurrent topics and gaps in my interactions. Finally, I also like to analyze notes (label:notes) or specific correspondence (from:your_friend@gmail.com) to get an overview and find gaps in the conversations. 2. Why use InfraNodus and not an AI summarization module? You probably get a lot of spam, so your AI will get overwhelmed with the content that's not really useful. The InfraNodus graph helps you see the important patterns and discover what's missing by focusing on the gaps. You can use the interactive graph to quickly remove the stuff you don't need and to focus on the most relevant topics and conversations. Customizing this workflow You can connect a Gmail node instead of the Telegram one if you prefer to receive notifications directly by email. I don't like using Slack and Discord because their bots are too difficult to set up and take too long. Check out the complete setup guide for this workflow at https://support.noduslabs.com/hc/en-us/articles/20394884531996-Build-a-Knowledge-Graph-and-Extract-Insights-from-Gmail-Emails-with-n8n-and-InfraNodus with a video tutorial coming soon and the links to other n8n workflows. Check our other n8n workflows at https://n8n.io/creators/infranodus/ for useful content gap analysis, expert panel, and marketing, and research workflows that utilize GraphRAG for better AI generation. Finally, check out https://infranodus.com to learn more about our network analysis technology used to build knowledge graphs from text.
by Naser Emad
Create sophisticated shortened URLs with advanced targeting and tracking capabilities using the BioURL.link API Overview This n8n workflow provides a powerful webhook-based URL shortening service that integrates with BioURL.link's comprehensive link management platform. Transform any long URL into a smart, trackable short link with advanced targeting features through a simple HTTP POST request. Key Features Smart URL Shortening**: Create custom short URLs with optional passwords and expiry dates Geo-targeting**: Redirect users to different URLs based on their geographic location Device Targeting**: Serve different content to iPhone, Android, or other device users Language Targeting**: Customize redirects based on user language preferences Deep Linking**: Automatically redirect mobile users to app store or native apps Custom Meta Tags**: Set custom titles, descriptions, and images for social media sharing Analytics & Tracking**: Integrate tracking pixels and campaign parameters Splash Pages**: Create branded landing pages before redirects How It Works Webhook Trigger: Send a POST request to the /shorten-link endpoint API Integration: Workflow processes the request and calls BioURL.link's API Response: Returns the shortened URL with all configured features Setup Requirements BioURL.link account and API key Replace "Bearer YOURAPIKEY" in the HTTP Request node with your actual API key Customize the JSON body parameters as needed for your use case Use Cases Marketing campaigns with geo-specific landing pages Mobile app promotion with automatic app store redirects A/B testing with device or language-based targeting Social media sharing with custom preview metadata Time-sensitive promotions with expiry dates Password-protected internal links Technical Details Trigger**: Webhook (POST to /shorten-link) API Endpoint**: https://biourl.link/api/url/add Response**: Complete shortened URL data Authentication**: Bearer token required Perfect for marketers, developers, and businesses needing advanced URL management capabilities beyond basic shortening services.
by David Ashby
Complete MCP server exposing all LinkedIn Tool operations to AI agents. Zero configuration needed - all 1 operations pre-built. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community Import this workflow into your n8n instance Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works • MCP Trigger: Serves as your server endpoint for AI agent requests • Tool Nodes: Pre-configured for every LinkedIn Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n LinkedIn Tool tool with full error handling 📋 Available Operations (1 total) Every possible LinkedIn Tool operation is included: 🔧 Post (1 operations) • Create a post 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Resource IDs and identifiers • Search queries and filters • Content and data payloads • Configuration options Response Format: Native LinkedIn Tool API responses with full data structure Error Handling: Built-in n8n error management and retry logic 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • Other n8n Workflows: Call MCP tools from any workflow • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Complete Coverage: Every LinkedIn Tool operation available • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n error handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.
by David Ashby
Complete MCP server exposing all PagerDuty Tool operations to AI agents. Zero configuration needed - all 9 operations pre-built. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community Import this workflow into your n8n instance Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works • MCP Trigger: Serves as your server endpoint for AI agent requests • Tool Nodes: Pre-configured for every PagerDuty Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n PagerDuty Tool tool with full error handling 📋 Available Operations (9 total) Every possible PagerDuty Tool operation is included: 🔧 Incident (4 operations) • Create an incident • Get an incident • Get many incidents • Update an incident 🔧 Incidentnote (2 operations) • Create an incident note • Get many incident notes 🔧 Logentry (2 operations) • Get a log entry • Get many log entries 👤 User (1 operations) • Get a user 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Resource IDs and identifiers • Search queries and filters • Content and data payloads • Configuration options Response Format: Native PagerDuty Tool API responses with full data structure Error Handling: Built-in n8n error management and retry logic 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • Other n8n Workflows: Call MCP tools from any workflow • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Complete Coverage: Every PagerDuty Tool operation available • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n error handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.
by Ranjan Dailata
Who this is for? This workflow is designed for: Marketing analysts, **SEO specialists, and content strategists who want automated intelligence on their online competitors. Growth teams** that need quick insights from SERP (Search Engine Results Pages) without manual data scraping. Agencies** managing multiple clients’ SEO presence and tracking competitive positioning in real-time. What problem is this workflow solving? Manual competitor research is time-consuming, fragmented, and often lacks actionable insights. This workflow automates the entire process by: Fetching SERP results from multiple search engines (Google, Bing, Yandex, DuckDuckGo) using Thordata’s Scraper API. Using OpenAI GPT-4.1-mini to analyze, summarize, and extract keyword opportunities, topic clusters, and competitor weaknesses. Producing structured, JSON-based insights ready for dashboards or reports. Essentially, it transforms raw SERP data into strategic marketing intelligence — saving hours of research time. What this workflow does Here’s a step-by-step overview of how the workflow operates: Step 1: Manual Trigger Initiates the process on demand when you click “Execute Workflow.” Step 2: Set the Input Query The “Set Input Fields” node defines your search query, such as: > “Top SEO strategies for e-commerce in 2025” Step 3: Multi-Engine SERP Fetching Four HTTP request tools send the query to Thordata Scraper API to retrieve results from: Google Bing Yandex DuckDuckGo Each uses Bearer Authentication configured via “Thordata SERP Bearer Auth Account.” Step 4: AI Agent Processing The LangChain AI Agent orchestrates the data flow, combining inputs and preparing them for structured analysis. Step 5: SEO Analysis The SEO Analyst node (powered by GPT-4.1-mini) parses SERP results into a structured schema, extracting: Competitor domains Page titles & content types Ranking positions Keyword overlaps Traffic share estimations Strengths and weaknesses Step 6: Summarization The Summarize the content node distills complex data into a concise executive summary using GPT-4.1-mini. Step 7: Keyword & Topic Extraction The Keyword and Topic Analysis node extracts: Primary and secondary keywords Topic clusters and content gaps SEO strength scores Competitor insights Step 8: Output Formatting The Structured Output Parser ensures results are clean, validated JSON objects for further integration (e.g., Google Sheets, Notion, or dashboards). 4. Setup Prerequisites n8n Cloud or Self-Hosted instance** Thordata Scraper API Key** (for SERP data retrieval) OpenAI API Key** (for GPT-based reasoning) Setup Steps Add Credentials Go to Credentials → Add New → HTTP Bearer Auth → Paste your Thordata API token. Add OpenAI API Credentials for the GPT model. Import the Workflow Copy the provided JSON or upload it into your n8n instance. Set Input In the “Set the Input Fields” node, replace the example query with your desired topic, e.g.: “Google Search for Top SEO strategies for e-commerce in 2025” Execute Click “Execute Workflow” to run the analysis. How to customize this workflow to your needs Modify Search Query Change the search_query variable in the Set Node to any target keyword or topic. Change AI Model In the OpenAI Chat Model nodes, you can switch from gpt-4.1-mini to another model for better quality or lower cost. Extend Analysis Edit the JSON schema in the “Information Extractor” nodes to include: Sentiment analysis of top pages SERP volatility metrics Content freshness indicators Export Results Connect the output to: Google Sheets / Airtable** for analytics Notion / Slack** for team reporting Webhook / Database** for automated storage Summary This workflow creates an AI-powered Competitor Intelligence System inside n8n by blending: Real-time SERP scraping (Thordata) Automated AI reasoning (OpenAI GPT-4.1-mini) Structured data extraction (LangChain Information Extractors)
by Gregor
This workflow offers several additional features for time tracking with Awork: Check whether time has been tracked when closing a task. If not, the task is reopened and the user is notified. This can be restricted to specific tasks using tags. Enforce a minimum time entry for tasks to comply with "at least 15-minute intervals are billed" policies. This can also be limited to specific tasks by using tags. Clean up time entries to match billing intervals. Add a start time to time entries if it is missing. This workflow does not use the Awork community nodes package, as the package does not support all required API calls and is therefore not used here. If you prefer to use that package, you can find more information at awork integration guide and replace the HTTP nodes with the corresponding community nodes where applicable. How it works Triggered via Awork Webhook call on status change of tasks and new time entries Set up steps Add webhook call to Awork (please see in-workflow notes regarding webhook configuration) Configure Awork API credentials Set up workflow configuration via setup node, e.g. user notification text, tags, enabled features etc.
by Trung Tran
Multi-Agent Book Creation Workflow with AI Tool Node and GPT-4, DALL-E Who’s it for This workflow is designed for: Content creators** who want to generate books or structured documents automatically. Educators and trainers** who need quick course materials, eBooks, or study guides. Automation enthusiasts* exploring *multi-agent systems* using the newly released *AI Tool Node** in n8n. Developers* looking for a reference template to understand *orchestration of multiple AI agents** with structured output. How it works / What it does This template demonstrates a multi-agent orchestration system powered by AI Tool Nodes: Trigger: Workflow starts when a chat message is received. Book Brief Agent: Generates the initial book concept (title, subtitle, and outline). Book Writer Agent: Expands the outline into full content by collaborating with two sub-agents: Designer Agent → Provides layout/design suggestions. Content Writer Agent → Drafts and refines chapters. Generate Cover Image: AI generates a custom book cover image. Upload to AWS S3: Stores the cover image securely. Configure Metadata: Adds metadata for title, author, and description. Build Book HTML: Converts markdown-based content into HTML format. Upload to Google Drive: Saves the HTML content for processing. Convert to PDF: Transforms the book into a professional PDF. Archive to Google Drive: Final version is archived for safe storage. This workflow showcases multi-agent coordination, structured parsing, and seamless integration with cloud storage services. How to set up Import the workflow into n8n. Configure the following connections: OpenAI (for Book Brief, Book Writer, Designer, and Content Writer Agents). AWS S3 (for image storage). Google Drive (for document storage & archiving). Add your API keys and credentials in n8n credentials manager. Test the workflow by sending a sample chat message (e.g., “Write a book about AI in education”). Verify outputs in Google Drive (HTML + PDF) and AWS S3 (cover image). Requirements n8n* (latest version with *AI Tool Node** support). OpenAI API key** (to power multi-agent models). AWS account** (with S3 bucket for storing images). Google Drive integration** (for document storage and archiving). Basic familiarity with workflow setup in n8n. How to customize the workflow Switch Models**: Replace gpt-4.1-mini with other models (faster, cheaper, or more powerful). Add More Agents: Introduce agents for **editing, fact-checking, or translation. Change Output Format: Export to **EPUB, DOCX, or Markdown instead of PDF. Branding Options: Modify the **cover generation prompt to include company logos or specific style. Extend Storage: Add **Dropbox, OneDrive, or Notion integration for additional archiving. Trigger Alternatives: Replace chat trigger with **form submission, webhook, or schedule-based runs. ✅ This workflow acts as a free, plug-and-play template to showcase how multi-agents + AI Tool Node can work together to automate complex content creation pipelines.
by Robert Breen
This workflow is designed for creators, marketers, and agencies who want to automate content publishing while keeping quality control through human review. It integrates four powerful tools — Google Sheets, OpenAI, GoToHuman, and Blotato — to deliver a seamless AI-assisted, human-approved, auto-publishing system for LinkedIn. ⚙️ What This Workflow Does 📅 Pulls Today’s Topic from Google Sheets You store ideas in a spreadsheet with a date column. The workflow runs daily (or manually) and selects the row matching today’s date. 🧠 Generates a Caption with OpenAI The selected idea is passed to GPT-4 via an AI Agent node. OpenAI returns a short, emoji-rich LinkedIn caption (1–2 sentences). The result is saved back to the sheet. 👤 Sends the Caption for Human Review via GoToHuman A human reviewer sees the AI-generated caption. They approve or reject it using a GoToHuman review template. Only approved captions move forward. 🚀 Publishes the Approved Caption to LinkedIn via Blotato The caption is posted to a LinkedIn account via Blotato's API. No additional input is required — it's fully automated after approval. 🔧 Setup Requirements ✅ Google Sheets Create or copy the provided sample sheet. Connect your Google Sheets account in n8n using OAuth2. ✅ OpenAI Create an API key at platform.openai.com. Add it to n8n as an OpenAI credential. ✅ GoToHuman Create an account and a Review Template at gotohuman.com. Add your API credential in n8n and use your reviewTemplateId in the node. ✅ Blotato Create an account at blotato.com. Get your API key and Account ID. Insert them into the HTTP Request node that publishes the LinkedIn post. 🧪 Testing the Workflow Use the Manual Trigger node for step-by-step debugging. Review nodes like AI Agent, Ask Human for Approval, and Post to LinkedIn to verify output. Once confirmed, activate the schedule for fully hands-free publishing. 👋 Built By Robert Breen Founder of Ynteractive — Automation, AI, and Data Strategy 🌐 Website: https://ynteractive.com 📧 Email: robert@ynteractive.com 🔗 LinkedIn: https://www.linkedin.com/in/robert-breen-29429625/ 📺 YouTube: YnteractiveTraining 🏷 Tags linkedin openai gotohuman social automation ai content approval workflow google sheets blotato marketing automation