Workflow Templates

Title: Gamify fitness tracking with AI multi-agents and Google Sheets Overview This template transforms fitness tracking into a gamified pirate adventure using AI multi-agents. It scores your health activities and assigns a dynamic "Bounty" reward. How it works Fetch Data: Retrieves your current "Bounty" from Google Sheets. AI Analysis: A central AI Scorer evaluates your report (meals, workouts, or injuries) and assigns a score from 0-100. Logic: JavaScript calculates the bounty increase based on the AI's score. Routing: The Switch node routes you to a specialized agent (Chef, Samurai, Doctor, or Navigator). Logging: Saves the conversation to Google Sheets for progress tracking. Setup steps Google Sheets: Create a sheet with two tabs: Profile (Columns: ID, Total_Bounty) Log (Columns: Date, Crew, Inquiry, Response) Spreadsheet ID: Replace YOUR_SPREADSHEET_ID in all 6 Google Sheets nodes. Credentials: Connect your Google Sheets and AI (OpenRouter/OpenAI) accounts.

✅ What problem does this workflow solve? Most e-commerce chatbots are transactional; they answer one question at a time and forget your context right after. This workflow changes that. It introduces a smart, memory-enabled shopping assistant that remembers user preferences, past orders, and previous queries to offer deeply personalized, natural conversations. ⚙️ What does this workflow do? Accepts real-time chat messages from users. Uses Zep Memory to store and recall personalized context. Integrates with: 🛒 Product Inventory 📦 Order History 📜 Return Policy Answers complex queries based on historical context. Provides: Personalized product recommendations Context-aware order lookups Seamless return processing Policy discussions with minimal user input 🧠 Why Context & Memory Matter Traditional bots: ❌ Forget what the user said 2 messages ago ❌ Ask repetitive questions (name, order ID, etc.) ❌ Can’t personalize beyond basic filters With Zep-powered memory, your bot: ✅ Remembers preferences (e.g., favorite categories, past questions) ✅ Builds persistent context across sessions ✅ Gives dynamic, user-specific replies (e.g., "You ordered this last week…") ✅ Offers a frictionless support experience 🔧 Setup Instructions 🧠 Zep Memory Setup Create a Zep instance and connect it via the Zep Memory node. It will automatically store user conversations and summarize facts. 💬 Chat Trigger Use the "When chat message received" trigger to initiate the conversation workflow. 🤖 AI Agent Configuration Connect: Chat Model → OpenAI GPT-4 or GPT-3.5 Memory → Zep Tools: Get_Orders – Fetch user order history from Google Sheets Get_Inventory – Recommend products based on stock and preferences Get_ReturnPolicy – Answer policy-related questions 📄 Google Sheets Store orders, inventory, and return policies in structured sheets. Use read access nodes to fetch data dynamically during conversations. 🧠 How it Works – Step-by-Step Chat Trigger – User sends a message. AI Agent (w/ Zep Memory): Reads past interactions to build context. Pulls memory facts (e.g., "User prefers men's sneakers"). Uses External Tools: Looks up orders, return policies, or available products. Generates Personalized Response using OpenAI. Reply Sent Back to the user through chat. 🧩 What the Bot Can Do 🛍 Suggest products based on past browsing or purchase behavior. 📦 Check order status and history without requiring the user to provide order IDs. 📃 Explain return policies in detail, adapting answers based on context. 🤖 Engage in more human-like conversations across multiple sessions. 👤 Who can use this? This is ideal for: 🛒 E-commerce store owners 🤖 Product-focused AI startups 📦 Customer service teams 🧠 Developers building intelligent commerce bots If you're building a chatbot that goes beyond canned responses, this memory-first shopping assistant is the upgrade you need. 🛠 Customization Ideas Connect with Shopify, WooCommerce, or Notion instead of Google Sheets. Add payment processing or shipping tracking integrations. Customize the memory expiration or fact-summarization rules in Zep. Integrate with voice AI to make it work as a phone-based shopping assistant. 🚀 Ready to Launch? Just connect: ✅ OpenAI Chat Model ✅ Zep Memory Engine ✅ Your Product/Order/Policy Sheets And you’re ready to deliver truly personalized shopping conversations.

This workflow takes a blog post (title + content) and automatically translates it into multiple languages of your choice using OpenAI inside n8n. The translated output is formatted in Markdown, making it ready for publishing or direct use in content management systems. It’s ideal for content creators, marketers, and businesses who want to instantly localize blogs into different languages without manual effort. 🔑 Key Features Multi-language support**: Translate your content into as many languages as you configure. Clean Markdown output**: Ensures translated blogs are properly formatted. Flexible input**: Works with any blog content passed into the workflow. Scalable**: Add or remove target languages with a single change in the Set node. ⚙️ Setup Instructions 1️⃣ Set Up OpenAI Connection Go to OpenAI Platform Navigate to OpenAI Billing Add funds to your billing account Copy your API key into the OpenAI credentials in n8n 2️⃣ Choose Your Target Languages Open the Set Node called Set Languages Edit the array of languages to include the ones you want to translate into, e.g.: [ "spanish", "french", "german" ]

Automated Personalized Email Icebreakers This workflow automates creating personalized email icebreakers. It reads leads from a Google Sheet, scrapes their company website, uses OpenAI to analyze the data and craft a unique opening line, and then saves that icebreaker back into the original sheet. How It Works Fetch Lead**: The workflow starts, loops through your leads, and pulls one from your Google Sheet. Scrape & Summarize**: It scrapes the lead's company website and uses a fast OpenAI model to summarize the key points about the company and the person. Generate Icebreaker**: This summary is then sent to a more powerful OpenAI model, which follows specific instructions to write a short, personalized icebreaker. Update Sheet**: The new icebreaker is saved back into the correct lead's row in your Google Sheet, using their email to match the record. Requirements An n8n instance. An OpenAI API key with available credits. A Google account with a Sheet for your leads. The Google Sheet must have columns for lead data (e.g., Email, Website, Company Name) and an empty column named icebreaker. The Email column must be unique for each lead. Setup Instructions Add Credentials: In n8n, add your OpenAI API key and connect your Google account via the Credentials menu. Configure Google Sheets Nodes: Select each of the two Google Sheets nodes (Client data and Add icebreaker to sheet). In each, choose your credential, select your spreadsheet and the specific sheet name, and ensure the column mapping is correct. Configure OpenAI Nodes: Select both OpenAI nodes (Summarising prospect data and Creating icebreaker) and choose your OpenAI credential from the dropdown. Verify Update Node: On the final Add icebreaker to sheet node, ensure the Operation is set to Append Or Update and the Matching Columns field is set to Email. Customization Options 💡 Trigger**: Change the manual start to an automatic trigger, like when a new row is added to the sheet or on a daily schedule (Cron). AI Prompt**: Modify the prompt in the "Creating icebreaker" node to change the tone, style, or length of the output. AI Model**: Experiment with different OpenAI models (like gpt-4o) for a different balance of cost, speed, and quality. Data Source**: Replace Google Sheets with a CRM like HubSpot or a database like Postgres.

Overview: Automated Candidate Creation with AI Vacancy Matching This workflow automates the creation of new candidates in the Recrutei ATS directly from an n8n Form submission, ensuring a seamless "Apply Now" funnel. Its core feature is an AI Agent (OpenAI + Tool) that dynamically identifies the correct Recrutei vacancy_id based on the applicant's selection in the form. The workflow also automatically extracts the text content from the candidate's PDF curriculum and uploads it as an internal observation (note) to the profile. This template eliminates manual data entry, guarantees that candidates are associated with the correct vacancy, and makes the resume content easily searchable within your Recrutei ATS. Workflow Logic & Steps On Form Submission (Form Trigger): The workflow starts when a candidate submits the n8n Form, capturing Name, Email, Phone, the selected Vacancy Name (e.g., "Javascript Developer"), and the Resume (PDF file). Get Vacancy ID from AI (OpenAI): The text name of the vacancy is sent to an AI Agent. The AI, guided by a specific System Prompt, uses the Recrutei's MCP Tool to accurately find the official vacancy_id corresponding to that job title in your ATS. Set Vacancy ID (Set): Extracts the clean vacancy_id (a number) returned by the AI. Get Pipe Stages (HTTP Request): Fetches the pipeline stages associated with the identified vacancy ID. Create Prospect in Recrutei (HTTP Request): Creates the new candidate (Prospect) in the Recrutei ATS, associating them with the correct vacancy_id and the first available pipe stage. Merge Candidate Data (Merge): Merges the prospect creation output with the original form data to ensure all necessary details (like the resume file) are available for the next steps. Extract Text from PDF Resume (Extract from File): Reads and extracts all text content from the uploaded PDF resume file. Add Curriculum as Observation (HTTP Request): Adds the extracted CV text as an internal observation/note (talent_observation_type_id: 11) to the newly created candidate's profile in Recrutei. Setup Instructions To implement this workflow, you must configure the following: Recrutei API Credential: Create a Header Auth credential named Recrutei API (or similar) with: Header Name: Authorization Header Value: Bearer YOUR_API_KEY_HERE This credential must be selected in the nodes: Get Pipe Stages, Create Prospect in Recrutei, and Add Curriculum as Observation. AI Configuration: OpenAI: Configure your API Key in the Get Vacancy ID from AI node. Recrutei's MCP: Replace YOUR_MCP_ENDPOINT_URL_HERE in the Endpoint URL field of the Recrutei's MCP node with your actual Recrutei's MCP Server Endpoint URL. For more information about Recrutei API please refer to: https://developers.recrutei.com.br/docs/obtendo-token#

How it works This workflow starts whenever you add a new company name to a Google Sheet. It checks if the company name is filled in, then uses AI to find more details about the company like industry, size, location, and website. Next, it looks for the company in your HubSpot CRM. If the company is not there, it adds it automatically. Finally, it updates the Google Sheet with all the new company information so you have everything organized in one place. Step-by-step 1. Start with Google Sheets The workflow watches your Google Sheet for new company names. It ignores any empty or incomplete entries. 2. Get Company Details Uses AI (OpenAI GPT-4o-mini) to find more information about the company. Formats the AI results so they can be used easily. 3. Check and Update HubSpot Searches your HubSpot CRM to see if the company already exists. If the company is new, it creates a record in HubSpot with the AI details. 4. Save Everything in Google Sheets Prepares the enriched data for saving. Adds or updates the company information in the Google Sheet for easy tracking. Why use this? Automatically adds useful company info without manual work. Keeps your CRM clean by avoiding duplicates. Stores all updated company details in one place for easy access. Runs smoothly in the background without you needing to do anything after setup.

🤖 AI-Powered n8n Workflow Generator with n8nBuilder API Overview This workflow lets you generate complete n8n workflows from natural language descriptions using the n8nBuilder API. 🚀 Users submit a short description via a form, and the workflow returns a ready-to-import n8n workflow JSON. Why use it? ⚡ AI-generated workflows from natural language 🛠️ Production-ready patterns (triggers, error handling, best practices) 🎯 Perfect for beginners who don't know which nodes to pick 🔄 Two modes: Form-based and AI Chat Agent Prerequisites 🔑 n8nBuilder account + API token — Get your free token at n8nbuilder.dev 🏢 An n8n instance (Cloud or self-hosted) 🤖 OpenAI API Key (Optional - to use with AI Agents) ⚠️ Important: Never expose your API key in public workflows. Use n8n Credentials for production setups. Setup Instructions 1. Get your n8nBuilder API token Visit n8nbuilder.dev Sign up or log in to your account Navigate to Account → API to generate your token 2. Configure the Form The Form Trigger collects: api_token (required) — Your n8nBuilder API token email (required) — Your email address query (required) — Natural language description of the workflow (e.g., "Read RSS from https://n8nbuilder.dev/blog/feed.xml every hour and send Slack message if new post arrives") 3. Workflow Execution User fills the form and submits Workflow sends a POST request to https://api.n8nbuilder.dev/api/generate n8nBuilder API processes the request and generates a complete workflow Response is cleaned and formatted User receives the generated workflow JSON ready to import 4. Outputs The workflow returns: output — Complete n8n workflow JSON ready to import 💡 Tip: Copy the generated JSON and import it directly into your n8n instance via Settings → Workflows → Import from File. Customization Tips 📝 Write clear descriptions: The more specific your query, the better the generated workflow 🎨 Try different use cases: Data transformation, API integrations, scheduled tasks, webhooks, etc. 🔧 Edit after generation: Generated workflows are production-ready but you can always customize them further 🤖 Use AI Chat mode: Enable the AI Agent for conversational workflow generation Alternative: Use the n8nBuilder Community Node 🎁 Optional: Install the n8n-nodes-n8nbuilder community node if you prefer using a dedicated node instead of raw HTTP. See: GitHub Repository Troubleshooting 401/403 Unauthorized** → Check your API token in the form Invalid JSON** → Ensure your email and query are properly filled No output returned** → Verify your API token is valid and active Slow response** → Complex workflows may take a few seconds to generate Security Best Practices 🔒 Do not hardcode API tokens in public workflows 🔐 Use n8n Credentials for storing tokens securely 🛡️ Keep your API token private and regenerate if compromised Learn More 📚 n8nBuilder Documentation

How it works This workflow monitors a Discord channel on a schedule and processes recent messages automatically. Each message is checked against a data table to prevent duplicate processing. New messages are analyzed using an AI model to extract structured task details like assignee, priority, and deadlines. The workflow then formats this data and creates a corresponding ClickUp task with full context. Step-by-step Trigger and fetch messages** Schedule Trigger – Runs the workflow every minute. Get many messages – Retrieves the latest Discord messages from a selected channel. Process messages in batches** Loop Over Items – Iterates through each message one at a time for controlled execution. Check for duplicates** Get row(s) – Searches the data table for existing message IDs. If – Filters out messages that have already been processed. Store new messages** Insert row – Saves new message details (ID, author, content) to the data table. Generate task metadata with AI** Message a model – Uses OpenAI to extract structured task data like assignee, priority, estimate, and deadlines. Format task data** Format Task – Converts AI output into ClickUp-compatible fields and formats. Create ClickUp task** Create ClickUp Task – Creates a new task with assignees, dates, priority, and message context. Why use this? Eliminates manual ticket creation from Discord support messages Ensures no duplicate tasks with built-in tracking logic Automatically assigns tasks based on AI-driven classification Improves response time and team accountability Scales support operations without additional overhead

Use the n8n Data Tables feature to store, retrieve, and analyze survey results — then let OpenAI automatically recommend the most relevant course for each respondent. 🧠 What this workflow does This workflow demonstrates how to use n8n’s built-in Data Tables to create an internal recommendation system powered by AI. It: Collects survey responses through a Form Trigger Saves responses to a Data Table called Survey Responses Fetches a list of available courses from another Data Table called Courses Passes both Data Tables into an OpenAI Chat Agent, which selects the most relevant course Returns a structured recommendation with: course: the course title reasoning: why it was selected > Trigger: Form submission (manual or public link) 👥 Who it’s for Perfect for educators, training managers, or anyone wanting to use n8n Data Tables as a lightweight internal database — ideal for AI-driven recommendations, onboarding workflows, or content personalization. ⚙️ How to set it up 1️⃣ Create your n8n Data Tables This workflow uses two Data Tables — both created directly inside n8n. 🧾 Table 1: Survey Responses Columns: Name Q1 — Where did you learn about n8n? Q2 — What is your experience with n8n? Q3 — What kind of automations do you need help with? To create: Add a Data Table node to your workflow. From the list, click “Create New Data Table.” Name it Survey Responses and add the columns above. 📚 Table 2: Courses Columns: Course Description To create: Add another Data Table node. Click “Create New Data Table.” Name it Courses and create the columns above. Copy course data from this Google Sheet: 👉 https://docs.google.com/spreadsheets/d/1Y0Q0CnqN0w47c5nCpbA1O3sn0mQaKXPhql2Bc1UeiFY/edit?usp=sharing This Courses Data Table is where you’ll store all available learning paths or programs for the AI to compare against survey inputs. 2️⃣ Connect OpenAI Go to OpenAI Platform Create an API key In n8n, open Credentials → OpenAI API and paste your key The workflow uses the gpt-4.1-mini model via the LangChain integration 🧩 Key Nodes Used | Node | Purpose | n8n Feature | |------|----------|-------------| | Form Trigger | Collect survey responses | Forms | | Data Table (Upsert) | Stores results in Survey Responses | Data Tables | | Data Table (Get) | Retrieves Courses | Data Tables | | Aggregate + Set | Combines and formats table data | Core nodes | | OpenAI Chat Model (LangChain Agent) | Analyzes responses and courses | AI | | Structured Output Parser | Returns structured JSON output | LangChain | 💡 Tips for customization Add more Data Table columns (e.g., email, department, experience years) Use another Data Table to store AI recommendations or performance results Modify the Agent system message to customize how AI chooses courses Send recommendations via Email, Slack, or Google Sheets 🧾 Why Data Tables? This workflow shows how n8n’s Data Tables can act as your internal database: Create and manage tables directly inside n8n No external integrations needed Store structured data for AI prompts Share tables across multiple workflows All user data and course content are stored securely and natively in n8n Cloud or Self-Hosted environments. 📬 Contact Need help customizing this (e.g., expanding Data Tables, connecting multiple surveys, or automating follow-ups)? 📧 robert@ynteractive.com 🔗 Robert Breen 🌐 ynteractive.com

Automated Instagram Carousel Post (Blotato + GPT-4.1) This workflow is an end-to-end solution for automating the creation and publishing of highly engaging Instagram Carousel content on a recurring schedule. It leverages the intelligence of an AI Agent (GPT-4.1) for idea generation and sharp copywriting, combined with the visual rendering capabilities of Blotato, all orchestrated by the n8n automation platform. The core objective is to drastically cut content production time, enabling creators and marketing teams to consistently generate high-impact, scroll-stopping educational or inspirational content without manual intervention. How It Works The workflow executes in five automated phases: 1. Trigger and Idea Generation The workflow starts with the Schedule Trigger node, running at your specified time interval (e.g., daily). It takes the initial subject from the Topic node and feeds it to the Topic1 AI Agent. This agent is specifically prompted to create a short, viral hook/title (max. 6 words) in the style of confident, tactical copywriters (like Alex Hormozi), maximizing the content's initial draw. 2. Content Creation and Output Structuring The viral hook is then passed to the AI Agent Carousel Maker. This agent uses the GPT-4.1 model, following strict system instructions, to generate all necessary content elements in a structured JSON format: Punchy, concise text for each Carousel slide. A long, detailed Instagram Caption with explanations and a CTA. A short final title for internal reference. 3. Visual Rendering (Blotato Tool) The slide text output is sent to the Simple tweet cards monocolor (Blotato Tool) node. Blotato acts as a graphic generation API, rendering the text onto a chosen template to create a series of Carousel images (using the 4:5 aspect ratio). This replaces the need for manual design work in tools like Canva. 4. Status Check and Retry Mechanism Visual rendering takes time, so the workflow pauses: The Wait node holds the execution for 3 minutes. The Get carousel node retrieves the image generation status using the ID provided by the previous Blotato node. The If carousel ready node checks if the status is done. If not, the flow is routed back to the Wait node, implementing a built-in simple retry mechanism until the visuals are complete. 5. Final Posting Once the status is confirmed as done, the workflow proceeds to the final step: The Instagram [BLOTATO] node uses the media URLs retrieved from Blotato and the long caption from the AI Agent to automatically publish the entire Carousel post (multiple images plus text) to your linked Instagram account. Set Up Steps To successfully activate and personalize this n8n workflow, follow these steps: Step 1: Import and Connect Credentials Import Workflow: Import the provided JSON file (Automated Instagram Carousel Post with Blotato + Gpt 4.1.json) into your n8n instance. OpenAI Credentials: Ensure you have valid OpenAI API credentials connected to the OpenAI Chat Model node. Blotato Credentials: Ensure your valid Blotato API credentials are connected to all three Blotato-related nodes (Simple tweet cards monocolor, Get carousel, and Instagram [BLOTATO]). Step 2: Configure Workflow Inputs Set Topic: Open the Topic node. Change the default initial topic expression =Top ai tools for finance to any general subject matter you want your Carousels to cover. Set Schedule: Open the Schedule Trigger node and configure the Rule to define how often you want the content to be created and posted (e.g., set it to run Every Day at a specific time). Step 3: Personalize Content and Visuals Customize AI Persona: Open the AI Agent Carousel Maker node. Review and modify the long System Message to refine the AI's output: Adjust the # ROLE and # STYLE sections to match your brand's voice (e.g., change the Alex Hormozi style to a more formal, academic tone if needed). Do not change the structure defined in # OUTPUT as this JSON format is essential for downstream nodes. Personalize Visuals: Open the Simple tweet cards monocolor (Blotato Tool) node. Under templateInputs, customize fields like authorName, handle, and profileImage URLs to ensure the generated visuals are consistent with your personal or brand identity. Step 4: Final Posting Setup Select Instagram Account: Open the Instagram [BLOTATO] node. In the accountId parameter, use the dropdown list to select the specific Instagram account that is connected via your Blotato service. Activate: Once all steps are complete, save the workflow and toggle the main switch to Active to allow the Schedule Trigger to begin running the automation.

🧠 FB Group Problem Solver - Auto - Generate Helpful Posts For: Business Owners, Community managers, coaches, consultants, and business owners who want to build authentic relationships in Facebook groups without spending hours scrolling and crafting responses. Pain Point Solved: Tired of manually browsing Facebook groups to find engagement opportunities? This workflow automatically discovers what your community is struggling with and writes genuine, helpful posts that position you as a trusted problem-solver. How It Works This workflow runs on autopilot to: Scan your target Facebook groups for recent posts Identify the most common problems and pain points Analyze the community's language and communication style Generate authentic, value-packed posts that solve real problems Save ready-to-publish content to your Google Sheet What You'll Need Google Sheets account (for group URLs and post storage) PAID Apify account with Facebook Groups Scraper actor OpenAI API key (GPT-4 recommended) n8n instance (self-hosted or cloud) Quick Setup Import workflow and connect your Google Sheets Add your Apify API key and configure the Facebook scraper Insert OpenAI API keys in the three AI nodes List your FB groups in the input sheet (URL, Name, Niche) Test manually, then schedule to run daily/weekly Results Get 2 post variations for each identified problem, written in the group's natural tone and style. Posts are non-promotional, genuinely helpful, and designed to spark engagement while building trust. Time saved: 3-5 hours per week of manual group monitoring and content creation

Video Introduction Want to automate your inbox or need a custom workflow? 📞 Book a Call | 💬 DM me on Linkedin What This Workflow Does This workflow creates an intelligent AI assistant that manages your HubSpot contacts through natural conversation. Instead of manually navigating the HubSpot interface, you can simply chat with the agent to search for contacts by email or company name, add new leads, or update existing records. The AI automatically determines which action to take based on your chat input and can handle multiple operations in a single conversation. Key Features Natural language contact search**: Find contacts by email address or company name using conversational commands Smart contact creation**: Add new contacts by providing details in natural language—the AI extracts email, name, and company information automatically Duplicate prevention**: Uses HubSpot's ""create or update"" functionality to prevent duplicate entries Conversation memory**: Remembers context from previous messages in the same chat session Multi-tool intelligence**: The AI agent automatically selects the appropriate tool based on your request Common Use Cases Quickly add leads captured from conversations, emails, or meetings without opening HubSpot Search for contact information during calls or meetings Update contact details through simple chat commands Bulk contact lookups by company for account research Enable non-technical team members to manage CRM data through conversation Setup Instructions HubSpot Configuration: Create a developer account at developers.hubspot.com using your existing HubSpot login Navigate to Legacy Apps in the left-hand menu and create a new private app Give your app a name and move to the Scopes tab Add the following permissions: crm.objects.contacts.read crm.objects.contacts.write Click Create app In the Auth tab, reveal and copy your Access token In n8n, create a new HubSpot credential using APP Token as the connection method and paste your token OpenAI Configuration: Ensure you have an OpenAI API account with valid credentials configured in n8n The workflow uses GPT-5.2 by default, but you can select any compatible OpenAI model based on your needs and budget Configuration Notes The workflow includes three HubSpot tools that the AI can use: Search contacts by email address Search contacts by company name Create or update a contact All contact properties (email, first name, last name, company name) are set to be automatically defined by the AI model based on your chat input. The agent intelligently chooses which tool to use based on your request—no need to specify which action you want.