Workflow Templates

4 nodes149 views

Call Center Analytics with Dual-AI Verification using DeepSeek Models

by Omar Akoudad

The workflow is well-designed for CRM analysis with a robust quality control mechanism. The dual-AI approach ensures reliable results, while the webhook integration makes it production-ready for real-time CRM data processing. Dual-AI Architecture: Uses DeepSeek Reasoner for analysis and DeepSeek Chat for verification. Flexible Input: Supports both manual testing and production webhook integration. Quality Assurance: Built-in verification system to ensure report accuracy. Comprehensive Analysis: Covers lead conversion, upsell metrics, agent ranking, and more. Professional Output: Generates structured markdown reports with actionable insights

📈Monitoring & Alerts

4 nodes73 views

Text-to-Image Generation with Flux AI, Google Drive Storage & Sheets Logging

by Sk developer

🎨 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.

📝Content Management

4 nodes3 views

Build a Document QA System with Google Drive, Pinecone, and OpenAI RAG

by Abdullahi Ahmed

Title RAG AI Agent for Documents in Google Drive → Pinecone → OpenAI Chat (n8n workflow) Short Description This n8n workflow implements a Retrieval-Augmented Generation (RAG) pipeline + AI agent, allowing users to drop documents into a Google Drive folder and then ask questions about them via a chatbot. New files are indexed automatically to a Pinecone vector store using OpenAI embeddings; the AI agent loads relevant chunks at query time and answers using context plus memory. Why this workflow matters / what problem it solves Large language models (LLMs) are powerful, but they lack up-to-date, domain-specific knowledge. RAG augments the LLM with relevant external documents, reducing hallucination and enabling precise answers. (Pinecone) This workflow automates the ingestion, embedding, storage, retrieval, and chat logic — with minimal manual work. It’s modular: you can swap data sources, vector DBs, or LLMs (with some adjustments). It leverages the built-in AI Agent node in n8n to tie all the parts together. (n8n) How to get the required credentials | Service | Purpose in Workflow | Setup Link | What you need / steps | | ------------------------- | ------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------- | | Google Drive (OAuth2) | Trigger new file events & download the file | https://docs.n8n.io/integrations/builtin/credentials/google/oauth-generic/ | Create a Google Cloud OAuth app, grant it Drive scopes, get client ID & secret, configure redirect URI, paste into n8n credentials. | | Pinecone | Vector database for embeddings | https://docs.n8n.io/integrations/builtin/credentials/pinecone/ | Sign up at Pinecone, in dashboard create an index, get API key + environment, paste into n8n credential. | | OpenAI | Embeddings + chat model | https://docs.n8n.io/integrations/builtin/credentials/openai/ | Log in to OpenAI, generate a secret API key, paste into n8n credentials. | You’ll configure these under n8n → Credentials → New Credential, matching credential names referenced in your workflow nodes. Detailed Walkthrough: How the Workflow Works Here’s a step-by-step of what happens inside your workflow (matching your JSON): 1. Google Drive Trigger Watches a specified folder in Google Drive. Whenever a new file appears (fileCreated event), the workflow is triggered (polling every minute). You must set the folder ID (in “folderToWatch”) to the Drive folder you want to monitor. 2. Download File Takes the file ID from the trigger and downloads the file content (binary). 3. Indexing Path: Embeddings + Storage (This path only runs when new files arrive) The file is sent to the Default Data Loader node (via the Recursive Character Text Splitter) to break it into chunks with overlap (so context is preserved). Each chunk is fed into Embeddings OpenAI to convert text into embedding vectors. Then Pinecone Vector Store (insert mode) ingests the vector + text metadata into your Pinecone index. This ensures your vector store stays up-to-date with files you drop into Drive. 4. Chat / Query Path (Triggered by user chat via webhook) When a chat message arrives via When Chat Message Received, it gets passed into the AI Agent node. Before generation, the AI Agent calls the Pinecone Vector Store1 set in “retrieve-as-tool” mode, which runs a vector-based retrieval using the user query embedding. The relevant text chunks are pulled as tools/context. The OpenAI Chat Model node is linked as the language model for the agent. Simple Memory** node provides conversational memory (keeping history across messages). The agent combines retrieved context + memory + user input and instructs the model to produce a response. 5. Connections / Flow Logic The Embeddings OpenAI node’s output is wired into Pinecone Vector Store (insert) and also into Pinecone Vector Store1 (so the same embeddings can be used for retrieval). The AI Agent has tool access to Pinecone retrieval and memory. The Download File node triggers the insert path. The When chat message triggers the agent path. Similar Workflows / Inspirations & Comparisons To help understand how your workflow fits into what’s already out there, here are a few analogues: n8n Blog: “Build a custom knowledge RAG chatbot”** — they show a workflow that ingests documents from external sources, indexes them in Pinecone, and responds to queries via n8n + LLM. (n8n Blog) Index Documents from Google Drive to Pinecone** — this is nearly identical for the ingestion part: trigger on Drive, split, embed, upload. (n8n) Build & Query RAG System with Google Drive, OpenAI, Pinecone** — shows the full RAG + chat logic, same pattern. (n8n) Chat with GitHub API Documentation (RAG)** — demonstrates converting API spec into chunks, embedding, retrieving, and chatting. (n8n) Community tutorials & forums** talk about using the AI Agent node with tools like Pinecone, and how the RAG part is often built as a sub-workflow feeding an agent. (n8n Community) What sets your workflow apart is your explicit combination: Google Drive → automatic ingestion → chat agent with tool integration + memory. Many templates show either ingestion or chat, but fewer show them combined cleanly with n8n’s AI Agent. Suggested Published Description (you can paste/adjust) > RAG AI Agent for Google Drive Documents (n8n workflow) > > This workflow turns a Google Drive folder into a live, queryable knowledge base. Drop PDF, docx, or text files into the folder → new documents are automatically indexed into a Pinecone vector store using OpenAI embeddings → you can ask questions via a webhook chat interface and the AI agent will retrieve relevant text, combine it with memory, and answer in context. > > Credentials needed > > * Google Drive OAuth2 (see: https://docs.n8n.io/integrations/builtin/credentials/google/oauth-generic/) > * Pinecone (see: https://docs.n8n.io/integrations/builtin/credentials/pinecone/) > * OpenAI (see: https://docs.n8n.io/integrations/builtin/credentials/openai/) > > How it works > > 1. Drive trigger picks up new files > 2. Download, split, embed, insert into Pinecone > 3. Chat webhook triggers AI Agent > 4. Agent retrieves relevant chunks + memory > 5. Agent uses OpenAI model to craft answer > > This is built on the core RAG pattern (ingest → retrieve → generate) and enhanced by n8n’s AI Agent node for clean tool integration. > > Inspiration & context > This approach follows best practices from existing n8n RAG tutorials and templates, such as the “Index Documents from Google Drive to Pinecone” ingestion workflow and “Build & Query RAG System” templates. (n8n) > > You're free to swap out the data source (e.g. Dropbox, S3) or vector DB (e.g. Qdrant) as long as you adjust the relevant nodes. If you like, I can generate a polished Markdown README for you (with badges, diagrams, instructions) ready for GitHub/n8n community publishing. Do you want me to build that? [1]: https://www.pinecone.io/learn/retrieval-augmented-generation/?utm_source=chatgpt.com "Retrieval-Augmented Generation (RAG) - Pinecone" [2]: https://n8n.io/integrations/agent/?utm_source=chatgpt.com "AI Agent integrations | Workflow automation with n8n" [3]: https://blog.n8n.io/rag-chatbot/?utm_source=chatgpt.com "Build a Custom Knowledge RAG Chatbot using n8n" [4]: https://n8n.io/workflows/4552-index-documents-from-google-drive-to-pinecone-with-openai-embeddings-for-rag/?utm_source=chatgpt.com "Index Documents from Google Drive to Pinecone with OpenAI ... - N8N" [5]: https://n8n.io/workflows/4501-build-and-query-rag-system-with-google-drive-openai-gpt-4o-mini-and-pinecone/?utm_source=chatgpt.com "Build & Query RAG System with Google Drive, OpenAI GPT-4o-mini ..." [6]: https://n8n.io/workflows/2705-chat-with-github-api-documentation-rag-powered-chatbot-with-pinecone-and-openai/?utm_source=chatgpt.com "Chat with GitHub API Documentation: RAG-Powered Chatbot ... - N8N"

📊Data Processing

8 nodes

Smart Email Responder Workflow using AI

by Ankur Parag Kulkarni

💬Communication & Collaboration

This project presents an intelligent email management system powered by advanced artificial intelligence. It utilizes Google's Gemini 2.0 AI model to automatically categorize incoming emails into queries, project updates, and feedback, and generates context-specific responses in real time. Approach: The system processes emails promptly, ensuring consistent and timely communication. In addition to crafting automated replies, it streamlines workflow efficiency by sending calendar invitations for meetings without manual intervention. Results: The Smart Email Auto-Responder enhances email management by marking emails as read, applying appropriate labels, and systematically logging correspondence. This significantly reduces manual workload while improving client engagement and operational productivity.

6 nodes3217 views

Create Song Lyric Documents and Spotify Playlists for Singers with Google Docs

by Eric Mooney

Setlist Manager This workflow takes a Google spreadsheet called 'Setlist_Manager' with 'Artist' and 'SongTitle' entries and get's Lyrics for each song and creates a playlist for that set of songs. Create Spotify Playlist (naming it 'Setlist - [date of today]') Create the Google doc that will store the lyrics found. (naming it 'Setlist - [date of today]') Get the rows of songs from 'Setlist_Manager'. Use AI to verify the Artist name and song title. Get the lyrics to the song. Append the Google Doc with the lyrics. Search for the song in Spotify. Add that song to the Spotify Playlist. Go to band practice and be prepared! =)

6 nodes266 views

Extract Customer Pain Points from Support Forums with Bright Data & GPT-4

by Yaron Been

💬Communication & Collaboration

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This workflow automatically monitors customer support forums and Q&A platforms to extract valuable customer insights and pain points. It saves you time by eliminating the need to manually browse through forum discussions and provides structured analysis of customer questions, answers, and recurring issues. Overview This workflow automatically scrapes customer support forums like Stack Exchange and SuperUser to find questions and discussions related to specific topics or brands. It uses AI to analyze forum content, extract customer pain points, and identify recurring issues, then sends structured insights directly to your product team via email. Tools Used n8n**: The automation platform that orchestrates the workflow Bright Data**: For scraping forum pages and Q&A platforms without being blocked OpenAI**: AI agent for intelligent forum content analysis and insight extraction Gmail**: For sending automated insight reports to your team 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 Gmail: Connect your Gmail account for sending team notifications Customize: Set target forum URLs and define the topics or brands to monitor Use Cases Product Teams**: Identify customer pain points and feature requests from forum discussions Customer Support**: Monitor common issues and questions customers are asking Market Research**: Understand customer needs and challenges in your industry Competitive Analysis**: Track how customers discuss competitor products and services 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 #forummonitoring #customersupport #brightdata #webscraping #customerinsights #n8nworkflow #workflow #nocode #forumautomation #customerresearch #supportmonitoring #painpointanalysis #communitymonitoring #forumanalysis #customerfeedback #productinsights #supportforums #stackexchange #customervoice #userresearch #productfeedback #techsupport #communitylistening #customerexperience #supportanalysis #forumdata #qandamonitoring #customerpainpoints

5 nodes19 views

IT Ops AI SlackBot Workflow - Chat with your knowledge base

by Angel Menendez

Video Demo: Click here to see a video of this workflow in action. Summary Description: The "IT Department Q&A Workflow" is designed to streamline and automate the process of handling IT-related inquiries from employees through Slack. When an employee sends a direct message (DM) to the IT department's Slack channel, the workflow is triggered. The initial step involves the "Receive DMs" node, which listens for new messages. Upon receiving a message, the workflow verifies the webhook by responding to Slack's challenge request, ensuring that the communication channel is active and secure. Once the webhook is verified, the workflow checks if the message sender is a bot using the "Check if Bot" node. If the sender is identified as a bot, the workflow terminates the process to avoid unnecessary actions. If the sender is a human, the workflow sends an acknowledgment message back to the user, confirming that their query is being processed. This is achieved through the "Send Initial Message" node, which posts a simple message like "On it!" to the user's Slack channel. The core functionality of the workflow is powered by the "AI Agent" node, which utilizes the OpenAI GPT-4 model to interpret and respond to the user's query. This AI-driven node processes the text of the received message, generating an appropriate response based on the context and information available. To maintain conversation context, the "Window Buffer Memory" node stores the last five messages from each user, ensuring that the AI agent can provide coherent and contextually relevant answers. Additionally, the workflow includes a custom Knowledge Base (KB) tool (see that tool template here) that integrates with the AI agent, allowing it to search the company's internal KB for relevant information. After generating the response, the workflow cleans up the initial acknowledgment message using the "Delete Initial Message" node to keep the conversation thread clean. Finally, the generated response is sent back to the user via the "Send Message" node, providing them with the information or assistance they requested. This workflow effectively automates the IT support process, reducing response times and improving efficiency. To quickly deploy the Knowledge Ninja app in Slack, use the app manifest below and don't forget to replace the two sample urls: { "display_information": { "name": "Knowledge Ninja", "description": "IT Department Q&A Workflow", "background_color": "#005e5e" }, "features": { "bot_user": { "display_name": "IT Ops AI SlackBot Workflow", "always_online": true } }, "oauth_config": { "redirect_urls": [ "Replace everything inside the double quotes with your slack redirect oauth url, for example: https://n8n.domain.com/rest/oauth2-credential/callback" ], "scopes": { "user": [ "search:read" ], "bot": [ "chat:write", "chat:write.customize", "groups:history", "groups:read", "groups:write", "groups:write.invites", "groups:write.topic", "im:history", "im:read", "im:write", "mpim:history", "mpim:read", "mpim:write", "mpim:write.topic", "usergroups:read", "usergroups:write", "users:write", "channels:history" ] } }, "settings": { "event_subscriptions": { "request_url": "Replace everything inside the double quotes with your workflow webhook url, for example: https://n8n.domain.com/webhook/99db3e73-57d8-4107-ab02-5b7e713894ad", "bot_events": [ "message.im" ] }, "org_deploy_enabled": false, "socket_mode_enabled": false, "token_rotation_enabled": false } }

5 nodes27845 views

📄🌐PDF2Blog - Create Blog Post on Ghost CRM from PDF Document

by Joseph LePage

From PDF to Powerful Blog Posts: AI-Powered Content Transformation Turn complex documents into engaging digital content that drives results. This n8n Workflow uses AI to transforms lengthy PDFs into compelling blog posts that attract and retain readers while you focus on strategic initiatives. Time-Saving Innovation 🚅Lightning-Fast Processing Transform lengthy documents into polished blog content in under 1 minute, eliminating hours of manual work. Our system handles the heavy lifting, delivering up to a 95% reduction in content production time. 📱Intelligent Analysis The AI engine identifies and extracts key insights, organizing information for maximum impact. Each document undergoes comprehensive analysis to ensure no valuable content is overlooked. Advanced Content Optimization ✍️Dynamic Writing Styles Possible Adjust the prompt for multiple tone options: Professional for corporate communications Conversational for engaging blogs Thought leadership for industry authority 📊SEO-Ready Content Potential Adjust the prompt to automatically optimized for search engines, incorporating relevant keywords and semantic structure to improve visibility and drive organic traffic. Ideal Applications 🤼Content Marketing Teams Scale content production without sacrificing quality or consistency. Perfect for teams looking to maintain a robust publishing schedule while maximizing resource efficiency. 🏫Academic Communication Help researchers and institutions share complex findings with broader audiences through accessible, engaging content that maintains academic integrity. 🧑‍💻Digital Publishers Streamline the content transformation process while ensuring each piece meets modern digital standards and reader expectations. Transform your content strategy with an intelligent system that delivers consistent, high-quality results while dramatically reducing production time.

5 nodes6120 views

⚡AI-Powered YouTube Video Summarization & Analysis

by Joseph LePage

-- Disclaimer: This workflow uses a community node and therefore only works for self-hosted n8n users -- Transform YouTube videos into comprehensive summaries and structured analysis instantly. This n8n workflow automatically extracts, processes, and analyzes video transcripts to deliver clear, organized insights without watching the entire video. Time-Saving Features 🚀 Instant Processing Simply provide a YouTube URL and receive a structured summary within seconds, eliminating the need to watch lengthy videos. Perfect for research, learning, or content analysis. 🤖 AI-Powered Analysis Leverages GPT-4o-mini to analyze video transcripts, organizing key concepts and insights into a clear, hierarchical structure with main topics and essential points. Smart Processing Pipeline 📝 Automated Transcript Extraction Supports public YouTube video Handles multiple URL formats Extracts complete video transcripts automatically 🧠 Intelligent Content Organization Breaks down content into main topics Highlights key concepts and terminology Maintains technical accuracy while improving clarity Structures information logically with markdown formatting Perfect For 📚 Researchers & Students Quick comprehension of educational content and lectures without watching entire videos. 💼 Business Professionals Efficient analysis of industry talks, presentations, and training materials. 🎯 Content Creators Rapid research and competitive analysis of video content in your niche. Technical Implementation 🔄 Workflow Components Webhook endpoint for URL submission YouTube API integration for video details Transcript extraction system GPT-4 powered analysis engine Telegram notification system (optional) Transform your video content consumption with an intelligent system that delivers structured, comprehensive summaries while saving hours of viewing time.

5 nodes80445 views

Analyze Sales Territory Performance with Bright Data MCP & GPT-4o

by Yaron Been

This workflow automatically analyzes sales territory performance, comparing revenue, win rates, and activity across regions. Remove the guesswork from territory planning and drive balanced growth. Overview On a weekly schedule, the workflow pulls CRM data for each territory, merges it with demographic and market size info scraped via Bright Data, and feeds everything into OpenAI for performance benchmarking. Outliers—both high and low performers—are highlighted in a Google Data Studio dashboard and summarized in a Slack message. Tools Used n8n** – Orchestrates data collection and analysis CRM API** – Source of sales metrics by territory Bright Data** – Scrapes external market indicators (population, GDP, etc.) OpenAI** – Normalizes and benchmarks territories Google Sheets / Data Studio** – Stores and visualizes results Slack** – Sends the weekly summary How to Install Import the Workflow into n8n. Connect Your CRM API credentials. Configure Bright Data credentials. Set Up OpenAI API key. Authorize Google services & Slack. Customize Territory Definitions in the Set node. Use Cases Sales Leadership**: Rebalance territories based on potential. Revenue Operations**: Identify underserved regions. Financial Planning**: Allocate resources where ROI is highest. Incentive Design**: Reward reps fairly based on potential. 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 #territorymanagement #salesanalytics #brightdata #openai #n8nworkflow #nocode #revenueops

📈Monitoring & Alerts

7 nodes2 views

Auto-Sync Local Events to Google Calendar with n8n

by Yaron Been

Description This workflow automates the process of finding local events and adding them directly to your Google Calendar. It eliminates the need for manual event tracking by automatically scraping event information and creating calendar entries. Overview This workflow automates the process of finding local events and adding them to your Google Calendar. It uses Bright Data to scrape event information from a specified source and then creates new events in your calendar, ensuring you never miss out on what's happening around you. Tools Used n8n:** The automation platform that orchestrates the workflow. Bright Data:** For scraping event data from websites without getting blocked. Google Calendar API:** To create and manage calendar events. 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 Bright Data node. Set Up Google Calendar: Authenticate your Google Calendar account in the Google Calendar node. Customize: Adjust the workflow to target the specific websites and event types you're interested in. Use Cases Community Managers:** Keep track of local meetups and community events. Event Enthusiasts:** Never miss a concert, festival, or local gathering. Marketing Professionals:** Monitor competitor events and industry conferences. 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 #googlecalendar #brightdata #webscraping #events #eventautomation #localevents #calendarintegration #eventtracking #n8nworkflow #workflow #nocode #eventmanagement #productivitytools #timemanagement #eventplanning #automatedcalendar #eventdiscovery #techautomation #eventnotifications #eventscheduling #calendarsync #eventorganizer #automatedevents

📊Data Processing