by Oneclick AI Squad
Overview This workflow retrieves airline web check-in URLs from Google Sheets, scrapes their content, employs an LLM to generate structured JSON data, refreshes the sheet, creates embeddings, and saves them in a Postgres vector DB for future semantic searches or question-answering. Quick Notes Verify that Google Sheets has accurate URLs for scraping. Ensure the Postgres vector DB is set up correctly for embedding storage. Process Flow Start the workflow with the Chat Trigger - Start node. Retrieve airline check-in URLs using the Fetch Airline URLs node. Scrape webpage data with the Scrape Airline Webpage node. Extract JSON data using the Extract info with LLM node with a Chat Model. Pause for a response with the Wait for Response node. Update Google Sheets with the Store Extracted Data node. Create embeddings with the Generate Embeddings node and store in Postgres vector DB with the Save to Vector DB node. Break down long text with the Split Long Text node and delay the next batch with the Wait Before Next Batch node. Getting Started Import the workflow into n8n and set up Google Sheets and Postgres vector DB credentials. Run a test with a sample URL to confirm scraping and embedding storage. Tailored Adjustments Tweak the Extract info with LLM node to adjust JSON output or modify the Fetch Airline URLs node to pull from different sheet fields.
by Charles
Modern AI systems are powerful but pose privacy risks when handling sensitive data. Organizations need AI capabilities while ensuring: ✅ Sensitive data never leaves secure environments ✅ Compliance with regulations (GDPR, HIPAA, PCI, SOX) ✅ Real-time decision making about data sensitivity ✅ Comprehensive audit trails for regulatory review The Concept: Intelligent Data Classification + Smart Routing The goal of this concept is to build the foundations of the safe and compliant use of LLMs in Agentic workflows by automatically detecting sensitive data, applying sanitization rules, and intelligently routing requests through secure processing channels. This workflow will analyze the user's chat or webhook input and attempt to detect PII using the Enhanced PII Pattern Detector. If detected, the workflow will process that input via a series of Compliance, Auditing, and Security steps which log and sanitizes the request prior to any LLM being pinged. Why Multi-Tier Routing? Traditional systems use binary decisions (sensitive/not sensitive). Our 3-tier approach provides: ✅ Granular Security: Critical PII gets maximum protection ✅ Performance Optimization: Clean data gets full cloud capabilities ✅ Cost Efficiency: Expensive local processing only when needed ✅ User Experience: Maintains conversational flow across security levels Why Context-Aware Detection? Regex patterns alone miss contextual sensitivity. Our approach: ✅ Catches Intent: "Bank account" discussion is sensitive even without account numbers ✅ Reduces False Negatives: Medical discussions stay secure even without explicit medical IDs ✅ Proactive Protection: Identifies sensitive contexts before PII is shared ✅ Compliance Alignment: Matches how regulations actually define sensitive data Why Risk Scoring vs Binary Classification? Binary PII detection creates artificial boundaries. Risk scoring provides: ✅ Nuanced Decisions: Multiple low-risk patterns might aggregate to high risk ✅ Adaptive Thresholds: Organizations can adjust sensitivity based on their needs ✅ Better UX: Users aren't unnecessarily restricted for low-risk scenarios ✅ Audit Transparency: Clear reasoning for every routing decision Why Comprehensive Monitoring? Privacy systems require trust and verification: ✅ Compliance Proof: Audit trails demonstrate regulatory compliance ✅ Performance Optimization: Identify bottlenecks and improve efficiency ✅ Security Validation: Ensure no sensitive data leakage occurs ✅ Operational Insights: Understand usage patterns and system health How to Install: All that you will need for this workflow are credentials for your LLM providers such as Ollama, OpenRouter, OpenAI, Anthropic, etc. This workflow is customizable and allows the user to define the best LLM and storage/memory solutions for their specific use case.
by Yulia
Free template for voice & text messages with short-term memory This n8n workflow template is a blueprint for an AI Telegram bot that processes both voice and text messages. Ready to use with minimal setup. The bot remembers the last several messages (10 by default), understands commands and provides responses in HTML. You can easily swap GPT-4 and Whisper for other language and speech-to-text models to suit your needs. Core Features Text: send or forward messages Voice: transcription via Whisper Extend this template by adding LangChain tools. Requirements Telegram Bot API OpenAI API (for GPT-4 and Whisper) 💡 New to Telegram bots? Check our step-by-step guide on creating your first bot and setting up OpenAI access. Use Cases Personal AI assistant Customer support automation Knowledge base interface Integration hub for services that you use: Connect to any API via HTTP Request Tool Trigger other n8n workflows with Workflow Tool
by Yaron Been
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
by n8n Team
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.
by Michael Gullo
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.
by Abdulaziz
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
by Oneclick AI Squad
This AI-powered workflow reads emails, understands the request using an LLM, and creates structured Jira issues. Key Insights Poll for new emails every 5 minutes; ensure Gmail/IMAP is properly configured. AI analysis requires a reliable LLM model (e.g., Chat Model or AI Tool). Workflow Process Trigger the workflow with the Check for New Emails Gmail Trigger node. Fetch full email content using the Fetch Full Email Content get message node. Analyze email content with the Analyze Email & Extract Tasks node using AI. Parse the AI-generated JSON output into tasks with the Parse JSON Output from AI node. Create the main Jira issue with the Jira - Create Main Issue create: issue node. Split subtasks from JSON and create them with the Split Subtasks JSON Items and Create Subtasks create: issue nodes. Usage Guide Import the workflow into n8n and configure Gmail and Jira credentials. Test with a sample email to ensure ticket creation and subtask assignment. Prerequisites Gmail/IMAP credentials for email polling Jira API credentials with issue creation permissions Customization Options Adjust the Analyze Email & Extract Tasks node to refine AI task extraction or modify the polling frequency in the trigger node.
by The O Suite
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. How It works: When the user clicks "Execute Workflow" they are prompted for a URL, from there the Puppeteer node extracts JavaScript links from the provided URL. The links are then filtered down to ones that are relevant to the original URL that was quieried. From there an AI Agent searches the provided JavaScript links for API Keys, email addresses, and PII leaks. Finally a report is generated and sent via gmail to a desired destination. The report contains discovered links as well as any sensitive information that may have been found. Why It's Useful: This is a great tool for Cybersecurity testing. For Developers, make sure your scripts are clean and you didn't leave anything behind. For Ethical Hackers, this is a great tool for Bug Bounties by discovering sensitive information hidden in JavaScript.
by Angel Menendez
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
by Oneclick AI Squad
Automate your post-event networking with this intelligent n8n workflow. Triggered instantly after an event, it collects attendee and interaction data, enriches profiles with LinkedIn insights, and uses GPT-4 to analyze engagement and generate tailored follow-up messages. High-value leads are prioritized, messages are sent via email, LinkedIn, or Slack, and all activity is logged in your CRM and database. Save hours of manual follow-up while boosting relationship-building and ROI. 🤝✨ Advanced Features Webhook automation** – Starts instantly on event completion Multi-Source Enrichment** – Combines event data, interactions, and LinkedIn profiles AI-Powered Insights** – GPT-4 analyzes behavior and suggests personalized talking points Smart Priority Filtering** – Routes leads into High, Medium, and Low priority paths Personalized Content Generation** – AI crafts custom emails and LinkedIn messages Multi-Channel Outreach** – Sends via Email, LinkedIn DM, and Slack CRM Integration** – Automatically updates HubSpot with contact notes and engagement PostgreSQL Logging** – Stores full interaction history and analytics ROI Dashboard** – Tracks response rates, meetings booked, and pipeline impact What It Does Collects attendee data from your event platform Enriches with LinkedIn profiles & real-time interaction logs Scores networking potential using engagement algorithms Uses AI to analyze conversations, roles, and mutual interests Generates hyper-personalized follow-up emails and LinkedIn messages Sends messages through preferred channels (email, LinkedIn, Slack) Updates HubSpot CRM with follow-up status and next steps Logs all actions and tracks analytics for performance reporting Workflow Process The Webhook Trigger initiates the workflow via POST request with event and attendee data. Get Attendees** fetches participant list from the event platform. Get Interactions** pulls Q&A, chat, poll, and networking activity logs. Enrich LinkedIn Data** retrieves professional profiles, job titles, and company details via LinkedIn API. Merge & Enrich Data** combines all sources into a unified lead profile. AI Analyze Profile** uses GPT-4 to evaluate interaction depth, role relevance, and conversation context. Filter High Priority** routes top-tier leads (e.g., decision-makers with strong engagement). Filter Medium Priority** handles warm prospects for lighter follow-up. AI Agent1** generates personalized email content using chat model and memory. Generate Email** creates a professional, context-aware follow-up email. Send Email** delivers the message to the lead’s inbox. AI Agent2** crafts a concise, friendly LinkedIn connection message. Generate LinkedIn Msg** produces a tailored outreach note. Send LinkedIn** posts the message via LinkedIn API. Slack Notification** alerts your team in real-time about high-priority outreach. Update CRM (HubSpot)** adds contact, tags, and follow-up tasks automatically. Save to Database (Insert)** logs full lead journey and message content in PostgreSQL. Generate Analytics** compiles engagement metrics and success rates. Send Response** confirms completion back to the event system. Setup Instructions Import the workflow JSON into n8n Configure credentials: Event Platform API (for attendees & interactions) LinkedIn API (OAuth2) OpenAI (GPT-4) SMTP (for email) or Email Service (SendGrid, etc.) HubSpot API Key PostgreSQL Database Slack Webhook URL Trigger with a webhook POST containing event ID and settings Watch personalized outreach happen automatically! Prerequisites Event platform with webhook + attendee/interaction API LinkedIn Developer App with API access OpenAI API key with GPT-4 access HubSpot account with API enabled PostgreSQL database (table for leads & logs) Slack workspace (optional, for team alerts) Example Webhook Payload { "eventId": "evt_spring2025", "eventName": "Annual Growth Summit", "triggerFollowUp": true, "priorityThreshold": { "high": 75, "medium": 50 } } Modification Options Adjust scoring logic in AI Analyze Profile (e.g., weight Q&A participation higher) Add custom email templates in Generate Email with your brand voice Include meeting booking links (Calendly) in high-priority messages Route VIP leads to Send SMS via Twilio Export analytics to Google Sheets or BI tools (Looker, Tableau) Add approval step before sending LinkedIn messages Ready to 10x your event ROI? Get in touch with us for custom n8n automation!
by Oneclick AI Squad
This n8n workflow transforms simple chat requests into professional Center of Excellence (COE) blog posts using AI, then automatically publishes them to Google Drive. What Is This? An intelligent blog creation system that takes a topic from chat and produces executive-level blog posts. Uses three AI stages to ensure high-quality, professional content suitable for business consumption. Why Use This? Professional Content**: Creates sophisticated blogs with business insights Save Time**: Topic to published blog in 2-3 minutes No Writing Skills Needed**: AI handles all the writing and formatting Auto-Publishing**: Creates and shares Google Docs automatically Easy to Use**: Just chat your topic, get your blog How It Works 1. Blog Request & Planning Start Blog Request**: Chat interface receives your blog topic Create Blog Outline**: AI generates structured outline with sections AI Brain for Outline**: Powers the initial content planning 2. Content Review & Writing Review & Fix Outline**: AI improves outline structure and flow Write Full Blog Post**: Transforms outline into complete professional blog AI Brain for Review/Writing**: Advanced AI models handle content creation 3. Publish & Share Blog Clean Up Text Format**: Removes formatting issues for clean presentation Save Blog to Google Drive**: Creates properly formatted Google Doc Email Blog to Stakeholder**: Shares with specified team members Make Blog Public**: Creates shareable public link Send Blog Link to User**: Returns document URL via chat How to Use Start Chat: Access the chat interface and type your blog topic Wait: AI automatically processes (2-3 minutes) Get Your Blog: Receive Google Drive link to your published blog Good to Know Processing Time**: 2-3 minutes per blog Content Quality**: Uses advanced Gemini AI models for professional output Auto-Formatting**: Creates clean Google Docs ready for sharing Instant Sharing**: Stakeholders get email notifications automatically Public Access**: Generates shareable links for broader distribution Customizing This Workflow Content Style Modify AI prompts to match your company's writing tone Adjust content evaluation criteria for different audiences Change blog structure templates Publishing & Sharing Update stakeholder email addresses Change Google Drive folder destinations Modify sharing permissions (public/private) Add more distribution channels AI Enhancement Switch between different AI models for speed vs quality Add more review stages for specialized content Include company-specific knowledge sources