Workflow Templates

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This workflow automatically analyzes purchase trends and consumer behavior patterns to identify market opportunities and optimize business strategies. It saves you time by eliminating the need to manually analyze sales data and provides insights into buying patterns, seasonal trends, and customer preferences. Overview This workflow automatically scrapes e-commerce platforms, marketplace data, and sales analytics to extract purchase trends, product popularity, and consumer behavior insights. It uses Bright Data to access sales data and AI to intelligently analyze purchasing patterns, seasonal trends, and market opportunities. Tools Used n8n**: The automation platform that orchestrates the workflow Bright Data**: For scraping e-commerce and marketplace platforms without being blocked OpenAI**: AI agent for intelligent purchase trend analysis and forecasting Google Sheets**: For storing purchase trend data and analysis results How to Install Import the Workflow: Download the .json file and import it into your n8n instance Configure Bright Data: Add your Bright Data credentials to the MCP Client node Set Up OpenAI: Configure your OpenAI API credentials Configure Google Sheets: Connect your Google Sheets account and set up your trend analysis spreadsheet Customize: Define target marketplaces and trend analysis parameters Use Cases E-commerce Strategy**: Identify trending products and market opportunities Product Development**: Understand consumer preferences and demand patterns Marketing Planning**: Optimize campaigns based on seasonal purchase trends Business Intelligence**: Make data-driven decisions using market trend insights Connect with Me Website**: https://www.nofluff.online YouTube**: https://www.youtube.com/@YaronBeen/videos LinkedIn**: https://www.linkedin.com/in/yaronbeen/ Get Bright Data**: https://get.brightdata.com/1tndi4600b25 (Using this link supports my free workflows with a small commission) #n8n #automation #purchasetrends #marketanalysis #brightdata #webscraping #ecommerce #n8nworkflow #workflow #nocode #trendanalysis #consumerinsights #marketresearch #salesanalytics #businessintelligence #markettrends #customerinsights #ecommerceanalysis #salesdata #marketforecasting #consumerdata #purchaseanalysis #retailanalytics #marketinsights #demandforecasting #salestrends #consumertrends #marketintelligence #buyingpatterns #marketdemand

This workflow connects Telegram bots with LangChain nodes in n8n. The main AI Agent Node is configured as a Conversation Agent. It has a custom System Prompt which explains the reply formatting and provides some additional instructions. The AI Agent has several connections: OpenAI GPT-4 model is called to generate the replies Window Buffer Memory stores the history of conversation with each user separately There is an additional Custom n8n Workflow tool (Dall-E 3 Tool). AI Agent uses this tool when the user requests an image generation. In the lower part of the workflow, there is a series of nodes that call Dall-E 3 model with the user Telegram ID and a prompt for a new image. Once image is ready, it is sent back to the user. Finally, there is an extra Telegram node that masks HTML syntax for improved stability in case the AI Agent replies using the unsupported format.

Automate Drafts From Google Drive This workflow automates the end-to-end process of extracting and summarizing information from PDFs stored in a specific Google Drive folder. When a new PDF or any binary data is added, the workflow is triggered and begins by downloading and processing the PDF to extract all available text. If multiple PDFs are detected, their content is aggregated into a single, combined dataset. This automation eliminates the time consuming task of manually reading, taking notes, and drafting documents. By removing this burden, users can focus on more meaningful tasks while the workflow handles the repetitive, tedious work. The extracted content is then passed through an AI-powered information extractor that identifies key details such as names, dates, addresses, and any other structured data points the user wants to extract from the PDF. This step is highly customizable, allowing the user to define exactly what type of information should be extracted. While the workflow is designed to extract all available content from the PDF, specifying additional structured data points ensures that critical details are accurately captured. A second OpenAI Node uses the extracted information to draft a professional, formal summary suitable for documentation. This is the most important part of the workflow and can be fully customized to meet the user's specific needs. By editing the prompts, users can tailor the workflow to generate a wide variety of draft formats based on the extracted content. The workflow then generates a new Google Document containing the full draft and composes an email summarizing the key points in 3 to 5 bullet points. This email is automatically sent to the designated recipient along with a direct link to the Google Doc. This solution is ideal for insurance, legal, or administrative use cases where timely, accurate extraction and reporting from incoming PDFs is essential. How To Use The Workflow Step 1 - Place any binary data (e.g., PDF files) into the designated Google Drive folder. Step 2 - The workflow will automatically download each PDF, extract the text, and if multiple PDFs are present combine them into a single dataset for analysis. Step 3 - The OpenAI Draft Agent will analyze the extracted information, generate a formal draft, and create a Google Document. This document will be updated with the draft content and saved back into the same Google Drive folder. Step 4 - An email will be sent to the designated recipient(s), including a summary of the draft and key extracted information, along with a link to view the Google Document. Need Help? Have Questions? For consulting and support, or if you have questions, please feel free to connect with me on LinkedIn or email michael.gullo@outlook.com.

Who's it for This workflow is ideal for AI developers running multi-agent systems in n8n who need to quantitatively evaluate tool usage behavior. If you're building autonomous agents and want to verify their decisions against ground-truth expectations, this workflow gives you plug-and-play observability. What it does This template uses n8n's built-in Evaluation Trigger and Evaluation nodes to assess whether an AI agent correctly used all the expected tools. It supports: Dataset-driven testing of agent behavior Logging actual tools to compare them with the expected tools Assigning performance metrics (tool_called = true/false) Persisting output back to Google Sheets for further debugging The workflow can be triggered by either the chat input or the dataset row evaluation. It routes through a multi-tool agent node powered by the best LLMs. The agent has access to tools such as web search, calculator, vector search, and summarizer tools. The workflow then aims to validate tool use decisions by extracting the intermediate steps from the agent (i.e., action + observation) and comparing the tools that were called with the expected tools. If the tools that were called during the workflow execution match, then it's a pass; otherwise, it's documented as a fail. The evaluation nodes take care of that process.  How to set it up Connect your Google Sheets OAuth2 credential. Replace the document with your own test dataset. Set your desired models and configure the different agent tools, such as the summarizer and vector store. The default vector store used is Qdrant, so the user must create this vector store with a few samples of queries + web search results. Run from either the chat trigger or the evaluation trigger to test. Requirements Google Sheets OAuth2 credential OpenRouter / OpenAI credentials for AI agents and embeddings Firecrawl and Qdrant credentials for web + vector search How to customize Edit the Search Agent system message to define tool selection behavior Add more metric columns in the Evaluation node for complex scoring Add new tool nodes and link them to the agent block Swap in your own summarizer

🎨 AI Image Generator with Flux AI Generate realistic, high-quality images from text prompts using the Flux AI Text-to-Image Generator API via RapidAPI, and seamlessly store the results in Google Drive and log them in Google Sheets — all automated using n8n. 🧠 What This Workflow Does This no-code automation enables you to: 🖋️ Enter a custom text prompt using a web form. 🖼️ Generate a photorealistic image using Flux AI’s Text-to-Image Generator via RapidAPI. ☁️ Upload the image to Google Drive. 📊 Log the prompt and result in a Google Sheet. ⚠️ Capture and log errors in a fallback sheet. 💡 Use Case Ideal for: Digital artists and marketers Social media managers Brand mockup creators Rapid concept prototyping All without writing a single line of code. ✅ Benefits No-code automation** for AI-generated images Cloud storage** and structured logging Error handling** built-in Fast content creation** for design, branding, or concept testing Powered by* the Flux AI Text-to-Image Generator API via *RapidAPI** 🧩 Node-by-Node Breakdown 1. 📝 On Form Submission Accepts user input for a creative text prompt. 🔍 Example: “A silver can with vapor and blue lightning background.” 💡 Benefit: No technical knowledge needed. 2. 🌐 HTTP Request — Flux AI API Sends the prompt to the Flux AI Text-to-Image Generator API via RapidAPI. 📦 Returns an image encoded in base64. 💡 Benefit: Seamless integration with cutting-edge image generation. 3. 🧪 Code Node — Base64 Decoder Converts the base64 image to a binary .jpg file. 💡 Benefit: Readies the image for upload/download/sharing. 4. 📁 Google Drive Uploads the generated image to your Google Drive folder. 💡 Benefit: Secure, sharable cloud storage. 5. 📊 Google Sheets — Success Log Appends a row with the original prompt, filename, and generation date. 💡 Benefit: Tracks history of all generated images. 6. ⚠️ IF Node — Error Detection Checks if the image generation failed. 💡 Benefit: Prevents workflow from halting and routes to error logging. 7. 📉 Google Sheets — Error Log Logs failed prompts and error messages. 💡 Benefit: Helps identify what went wrong (e.g. malformed prompt). 🛠️ Challenges Solved | Problem | How This Workflow Fixes It | |--------|-----------------------------| | Manual prompt-based image generation is slow | Fully automated with Flux AI | | No storage pipeline for generated images | Integrated with Google Drive | | No audit trail for prompts/images | Logged into Google Sheets | | Errors go unnoticed in image generation | Built-in error check and logging | | Users lack API access or dev experience | Friendly web form UI | 🔗 API Spotlight This workflow is powered by the Flux AI Text-to-Image Generator API — available exclusively on RapidAPI. Why use this API? Ultra-fast text-to-image rendering High-resolution results Developer-friendly and cost-effective Great for branding, mockups, and visuals We’ve integrated this API to make advanced image generation accessible with just a prompt — no AI or dev experience required.

How It Works This workflow automates property registration verification, fraud detection, and blockchain-based compliance tracking by systematically assessing fraud risk, validating transactions, ensuring data immutability through cryptographic hashing, and recording property records on the blockchain. It ingests property registration data, applies GPT-4–driven fraud analysis with risk scoring, and verifies transaction legitimacy against regulatory and contractual criteria. The system generates cryptographic hashes for property and lease records, validates compliance requirements using AI-based analysis, queries the blockchain for verification, logs transactions on-chain, stores audit records in structured sheets, and securely archives all supporting documentation. Designed for real estate firms, legal practices, and property management companies, it enables transparent verification, fraud mitigation, and tamper-resistant compliance tracking across the property lifecycle. Setup Steps Configure property data source and set up OpenAI GPT-4 for fraud detection and compliance. Connect blockchain network credentials and configure hash generation parameters. Set up Google Sheets for audit logging and configure blockchain verification queries. Define fraud risk thresholds, compliance criteria, and transaction validation rules. Prerequisites Property registration data source; OpenAI API key; blockchain network access Use Cases Real estate firms automating fraud checks on property transactions; Customization Adjust fraud detection criteria and risk thresholds, modify blockchain network selection. Benefits Eliminates manual fraud detection, prevents title fraud and forgery

Automated Invoice Archiving Automatically fetch, store, and extract key information from invoices received via email from your ISP or utility provider (electricity, gas, telecom, water, etc.).The workflow saves the invoices to Google Drive (or optionally to your personal FTP/SFTP server) and logs all invoice details into Google Sheets via AI-powered extraction. Read: Full setup Guide How it works Scheduled TriggerRuns the workflow at a selected interval (e.g., every hour). You can freely adjust the timing. Gmail – Fetch MessagesReads your Gmail inbox and retrieves only messages coming from your ISP/utility provider’s email address, filtering for messages with PDF attachments. Gmail – Download Invoice Fetches the full email content and downloads the attached invoice (PDF). Google Drive – Upload File Uploads the invoice into a specific Google Drive folder of your choice. (Optional) Upload to FTP/SFTP Sends a copy of the invoice to your personal server via secure FTP/SFTP. AI Extraction Pipeline Extract PDF Text – converts the PDF into text (OCR not required if text-based). AI Agent (OpenRouter) – understands the invoice content and extracts structured fields (invoice number, date, provider name, total amount, tax info, line items, etc.) Code Node – sanitizes and parses the JSON from the AI model. Google Sheets – Append Invoice DataAdds a new row to your Google Sheet with all parsed invoice fields. (Optional) CleanupAutomatically deletes:– the Gmail message– the temporary file in Google Drive(Useful when you only want your FTP or Sheets copy.) Parameters to configure | Parameter | Description | Recommended configuration | | --- | --- | --- | | Gmail Credentials | OAuth2 credentials needed to read and delete emails. | Create OAuth credentials on Google Cloud → enable Gmail API → paste Client ID & Secret into n8n → “Connect OAuth2”. | | Sender Email Filter | Email address your provider uses to send invoices. | Example: billing@your-isp.com, invoices@utility.it, ciao@octopusenergy.it | | Google Drive Folder | Destination folder for saving invoices. | Copy the folder ID from the Drive URL and paste it into folderId. | | Google Drive Credentials | OAuth2 connection for file uploads/deletions. | Same Google Cloud project → enable Drive API → OAuth connect in n8n. | | FTP/SFTP Server (optional) | Upload invoices to your private server. | Host / IP · Port · Username · Password or SSH Key · Destination path (e.g. /home/user/invoices/). | | AI Model (OpenRouter) | Large-language model used to parse invoice text. | Example: gpt-4.1, llama-3.1, or any preferred OpenRouter model. | | Google Sheets Document | Destination spreadsheet for structured data. | Create a Sheet → add columns (Vendor, Invoice Number, Date, Amount, Service Type, etc.) → insert documentId & sheet name. | | Sheets Credentials (Service Account) | Used for writing into Google Sheets. | Create Service Account → download JSON → add to n8n → share the Sheet with the Service Account email. | | Trigger Interval | How often the workflow checks for new invoices. | Every hour · every 30 minutes · daily at set ti | Node-by-node breakdown 1. Schedule Trigger Runs at the interval you choose (default: hourly).Start → triggers entire workflow. 2. Gmail – Get Many Messages Filters inbox items using: Sender email** (your ISP/utility address) Has attachment** Unread or recent messages** Downloads metadata + attachment references. 3. Filter – Contains Attachment Ensures only messages with binary attachments continue. 4. Gmail – Get Invoice Downloads: Full email JSON The invoice PDF (binary data) 5. Google Drive – Upload File Uploads invoice PDF with a dynamic filename: {{ $json.from.value[0].name }}-{{ $json.date }}.pdf Requires: Google Drive OAuth2 credentials Folder ID (destination directory) 6. HTTP Request – Download File Retrieves the raw PDF file from Google Drive for further processing. 7. (Optional) FTP/SFTP Upload Uploads the PDF to your server using: Host / IP Port (default 22) Username Password or private key Destination path Filename is sanitized to ensure Unix compatibility. 8. (Optional) Delete Temporary File Deletes the Google Drive file if you don’t want duplicates. 9. (Optional) Delete Gmail Message Removes the original email once processed (optional inbox cleanup). 10. Extract from File (PDF → Text) Reads the PDF and extracts raw text for AI processing. 11. OpenRouter Chat Model LLM backend for the AI agent. Provides: invoice parsing field extraction structured reasoning 12. AI Agent – Extract Invoice Fields The agent is instructed to return strict JSON only, containing keys such as: vendor_name invoice_number invoice_date total_amount tax_details line_items[] po_number po_date Works for most standard PDF invoices. 13. Code – Clean & Parse JSON Sanitizes the AI output: Removes markdown fences Extracts valid JSON Parses into a clean JS object If the AI output is malformed, debugging info is returned. 14. Google Sheets – Append Data Appends the extracted fields into a structured row.Example mappings: Vendor** → {{ $json.vendor_name }} Invoice Number** → {{ $json.invoice_number }} Date** → {{ $json.invoice_date }} Amount** → {{ $json.total_amount }} Service Type** → {{ $json.line_items[0].description }} 💡 Tips & best practices Add multiple sender filters if you have more than one utility provider. Ensure invoices are text-based PDFs for best extraction results. Use Google Drive as a reliable long-term archive, or keep only FTP if you prefer local storage. Create charts in Google Sheets for tracking: Monthly utility cost trends Year-over-year comparison Consumption spikes (if included in invoices) ⚠️ Important notes Utility invoices contain personal and financial data. Keep your FTP/SFTP server secure. Google APIs require proper OAuth2 or Service Account setup; misconfiguration may cause permission errors. This workflow is for personal automation, not a replacement for official fiscal archiving. AI extraction quality depends on invoice formatting and the model you choose.

🚀 Remote Job Automation Workflow Automatically fetch, clean, and broadcast the latest remote job listings — powered by RemoteOK, Airtable, and Telegram. 🔧 Key Features Seamless Data Fetching: Pulls the latest job listings from the RemoteOK API using an HTTP Request node. Smart Data Processing (via Code Node): Filters out irrelevant metadata Cleans and sanitizes job descriptions (e.g., HTML tags, special characters) Handles malformed or encoded text gracefully Extracts and formats salary ranges for clarity Airtable Integration (Upsert): Stores each job as a unique record using job ID Avoids duplication through conditional upserts using Airtable's Personal Access Token Telegram Bot Broadcasting: Automatically formats and sends job posts to a Telegram group or channel Keeps your community or team updated in real-time 📦 Tech Stack RemoteOK API – source of curated remote job listings Airtable – lightweight, accessible job database Telegram Bot API – for real-time job notifications n8n – workflow automation engine to tie everything together 🔁 Workflow Overview Fetch Jobs from RemoteOK API Clean & Normalize job descriptions and metadata Extract Salary ranges and standardize them Upsert to Airtable (avoiding duplicates) Format Post for visual clarity Send to Telegram via bot integration 🧠 Perfect For Remote job boards or aggregators Recruitment agencies/startups Developers building personal job feeds Communities or channels sharing curated remote opportunities Automating newsletters or job digests ✅ Benefits Near real-time updates Minimal maintenance Full control and extensibility with n8n

This n8n template demonstrates how to use AI to generate custom images from scratch - fully automated, prompt-driven, and ready to deploy at scale. Use cases are many: You can use it for marketing visuals, character art, digital posters, storyboards, or even daily image generation for your personal purposes. How It Works The flow is triggered by a chat message in N8N or via Telegram. The default image size is 1080 x 1920 pixels. To use a different size, update the values in the “Fields - Set Values” node before triggering the workflow. The input is parsed into a clean, structured prompt using a multi-step transformation process. Our AI Agent sends the final prompt to Google Gemini’s image model for generation (you can also integrate with OpenAI or other chat models). The raw image data created by the AI Agent will be run through a number of codes to make sure it's feasible for your preview if needed and downloading. Then, we use an HTTP node to fetch the result so you can preview the image. You can send it back to the chat message in N8N or Telegram, or save it locally to your disk. How To Use Download the workflow package. Import the package into your N8N interface. Set up the credentials in the following nodes for tool access and usability: "Telegram Trigger"; "AI Agent - Create Image From Prompt"; "Telegram Response" or "Save Image To Disk" (based on your wish). Activate the "Telegram Response" OR "Save Image To Disk" node to specify where you want to save your image later. Open the chat interface (via N8N or Telegram). Type your image prompt or detailed descriptions and send. Wait for the process to run and finish in a few seconds. Check the result in your desired saving location. Requirements Google Gemini account with image generation access. Telegram bot access and chat setup (optional). Connection to local storage (optional). How To Customize We’re setting the default image size to 1080 x 1920 pixels and the default image model to "flux". You can customize both of these values in the “Fields – Set Values” node. Supported image model options include: "flux", "kontext", "turbo", and "gptimage". In the “AI Agent – Create Image From Prompt” node, you can also change the AI chat model. By default, it uses Google Gemini, but you can easily replace it with OpenAI ChatGPT, Microsoft AI Copilot, or any other compatible provider. Need Help? Join our community on different platforms for support, inspiration and tips from others. Website: https://www.agentcircle.ai/ Etsy: https://www.etsy.com/shop/AgentCircle Gumroad: http://agentcircle.gumroad.com/ Discord Global: https://discord.gg/d8SkCzKwnP FB Page Global: https://www.facebook.com/agentcircle/ FB Group Global: https://www.facebook.com/groups/aiagentcircle/ X: https://x.com/agent_circle YouTube: https://www.youtube.com/@agentcircle LinkedIn: https://www.linkedin.com/company/agentcircle

Who’s it for Creators who want to create faceless videos automatically, while keeping human oversight and quality control. How it works / What it does AI generates 8 story beats, which can be reviewed, edited, or re-ordered by a human. Each beat is converted into narration (audio), imagery, and short clips. Final video is assembled and stored in Google Drive, ready for review and regeneration if needed. Chat commands trigger each step, giving full human control. How to set up Set up Google Drive and Google Sheets Get necessary credentials Requirements Google Drive account for storing videos. Access to AI tools for text, voice, and visuals. Basic familiarity with triggering chat commands or automation steps. How to customize the workflow Adjust the number of story beats or narration style Use models of your choice Use for any theme by updating Story prompt

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. 🧠 How It Works This workflow automates the process of screening resumes using AI, logging results to Google Sheets, and sending follow-up emails via Gmail. User uploads their resume via a form (PDF only). Resume content is extracted and sent to OpenAI for evaluation. AI scores the resume based on: Role-specific must-have qualifications Soft skills / strategic fit questions Based on the score threshold, the candidate is classified as: ✅ Accepted → Saved to Accepted sheet + Gmail invite ❌ Rejected → Logged to Rejected sheet + Gmail rejection message Output is stored in Google Sheets with detailed justification. ⚙️ Set Up Steps 🔑 Connect your OpenAI and Google Sheets credentials. Replace the placeholder tags in the AI prompt: COMPANY_NAME ROLE_NAME ROLE_DESCRIPTION CRITERIA_1 to CRITERIA_5 Q1 to Q5 THRESHOLD (score to pass) Customize Gmail messages (optional). ✅ Make sure your sheet has two tabs: Accepted and Rejected. 📌 Notes Sticky Notes included in the flow explain: What each node does Where to replace variables Tips for improving match scoring

Overview This workflow automates customer support ticket processing using AI-powered analysis. Incoming tickets from email (IMAP) or a webhook endpoint are automatically cleaned, translated to English if necessary, analyzed with AI, and routed based on urgency and category. The workflow can automatically generate draft replies for simple tickets or escalate critical issues to your support team. It also updates your CRM or helpdesk system with structured ticket insights and logs observability metrics for monitoring support performance. This automation helps support teams reduce manual triage work, respond faster to customers, and ensure urgent issues receive immediate attention. How It Works 1. Ticket Intake The workflow begins when a support request is received from one of two sources: IMAP Email Trigger** – Reads incoming support emails from a mailbox. Webhook Trigger** – Accepts tickets from external systems such as websites, chatbots, or applications. Both triggers feed the message into a unified processing pipeline. 2. Content Cleaning The workflow extracts readable text from incoming messages using an HTML extraction node. This ensures that emails or formatted messages can be analyzed reliably. 3. Ticket Data Normalization Incoming data is standardized to ensure consistent processing across all ticket sources. The workflow generates fields such as: ticket_id user_email original_message timestamp source_channel 4. Language Detection & Translation An AI agent detects the original language of the ticket. If the message is not written in English, it is automatically translated while preserving the original meaning and tone. 5. AI Support Intelligence A second AI agent analyzes the ticket and produces structured insights including: Sentiment (positive, neutral, negative) Urgency level (low, medium, high, critical) Ticket category Issue summary Customer churn risk score Recommended action path 6. Intelligent Routing A Switch node routes the ticket based on the AI analysis: Auto Reply Path** – Generates a draft response. Escalation Path** – Sends the ticket to a support escalation webhook. 7. Draft Reply Generation If the ticket qualifies for automatic handling, an AI agent generates a professional support response based on the ticket content, sentiment, and category. 8. CRM / Helpdesk Update The workflow sends structured ticket information to a CRM or helpdesk system, including: Ticket ID Category Sentiment Urgency Churn risk score AI-generated summary Draft reply 9. Observability Metrics The workflow logs operational metrics such as response time, ticket category, urgency, sentiment, and escalation status. These metrics can be sent to an observability or monitoring system. Setup Instructions Configure Email Credentials (Optional) Add IMAP credentials if you want to process support emails. Configure the Webhook Trigger Use the webhook URL generated by the workflow to receive support tickets from external systems. Add AI Model Credentials Connect your Anthropic API credentials to power the AI agents used for translation, analysis, and response generation. Configure Workflow Variables In the Workflow Configuration node, provide: CRM or Helpdesk API URL Escalation webhook URL Observability logging endpoint (optional) Connect Your CRM or Helpdesk System Ensure the API endpoint accepts JSON payloads containing ticket data and AI insights. Use Cases AI-powered customer support ticket triage Handling multilingual support requests Automatically generating draft responses Escalating critical support tickets Monitoring support performance metrics Requirements Anthropic API credentials IMAP email credentials (optional) CRM or Helpdesk API endpoint Escalation webhook endpoint Optional observability or monitoring endpoint