Workflow Templates

Overview Tired of cookie-cutter “AI LinkedIn post generators”? This workflow goes beyond just text generation — it orchestrates the entire lifecycle of a LinkedIn post. From idea capture to deduplication, from GPT-powered drafting to automatic image generation and link storage, it creates ready-to-publish posts while keeping your content unique and audit-friendly. What does this workflow do? This workflow: Captures Ideas & Briefs – Inputs are logged in Google Sheets with audience, goals, and angles. Deduplicates Smartly – Avoids repeating hooks or ideas with fuzzy GPT-based dedupe + GSheet logs. Generates Posts – GPT (OpenAI) drafts sharp LinkedIn-ready posts based on your brief. Creates Images – Post hook + body is sent to an Image Gen model (DALL·E / SDXL) → PNG asset. Stores & Links – Final text + image uploaded to Google Drive with shareable links. Audit Trail – GSheets keeps full history: raw idea, draft, final post, assets, notes. Why is this useful? Most “AI post generators” just spit out text. This workflow builds a real publishing pipeline: 🔄 No duplicates → keeps posts fresh & original. 🖼 Images included → auto-generated visuals increase engagement on LinkedIn. 📊 Audit-ready → every post has a traceable log in Sheets. ⚡ Fast iteration → from half-baked thought → polished post in minutes. Tools used n8n (Orchestrator): Automates triggers, merges, retries, and Google connectors. OpenAI (LLM): Idea generation, drafting, fuzzy dedupe, and voice conformity. Google Sheets: Source of truth — stores ideas, dedupe logs, audit trail. Google Drive: Stores rendered images and shares links for publishing. Image Generation (DALL·E / SDXL): Creates header graphics from hook + body. Who is this for? 🧑‍💻 Product Managers / Founders who want to post consistently but don’t have time. 🎨 Creators who want to add unique visuals without hiring a designer. ⚙️ n8n Builders who want to see how AI + automation + storage can be stitched into one pipeline. Workflow Highlights ✅ Full content pipeline (ideas → images → final copy). ✅ GPT-based fuzzy dedupe to avoid repetition. ✅ Auto-generated images for higher engagement. ✅ Clean logs in Google Sheets for future reuse & audits. ✅ Ready-to-publish LinkedIn post in minutes.

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 AI-powered chatbot that can answer natural language questions about your QuickBooks Online data. Using OpenAI's GPT models and the Model Context Protocol (MCP), the agent can retrieve customer information, analyze balances, and provide insights through a conversational interface. Users can simply ask questions like "How many customers do we have?" or "What's our total customer balance?" and get instant answers from live QuickBooks data. Key Features Natural language queries**: Ask questions about your QuickBooks data in plain English MCP architecture**: Uses Model Context Protocol to manage tools efficiently, making it easy to expand with additional QuickBooks operations Public chat interface**: Share the chatbot URL with team members who need QuickBooks insights without direct access Real-time data**: Queries live QuickBooks data for up-to-date answers Common Use Cases Customer service teams checking account balances without logging into QuickBooks Sales teams quickly looking up customer information Finance teams getting quick answers about customer data Managers monitoring key metrics through conversational queries Setup Requirements QuickBooks Developer Account: Register at developer.intuit.com and create an app with Accounting scope permissions. You'll receive a Client ID and Client Secret. Configure OAuth: In your Intuit Developer dashboard, add the redirect URL provided by n8n when creating QuickBooks credentials. Set the environment to Sandbox for testing, or complete Intuit's app approval process for Production use. OpenAI API: Add your OpenAI API credentials to power the chat model. The workflow uses GPT-4.1-mini by default, but you can select other models based on your performance and cost requirements. Chat Access: The chat trigger is set to public by default. Configure access settings based on your security requirements before sharing the chat URL.

Description 📌 Overview This workflow creates a chat-based Retrieval-Augmented Generation (RAG) agent that lets you upload documents to Google Drive and then query them directly through Telegram. It uses embeddings, vector storage, and an AI agent to retrieve, analyze, and answer user questions with context-aware responses. 🧩 Key Features 📂 Google Drive Integration Watches a folder for new file uploads. Downloads and loads documents automatically into the system. 🔎 Vector Embeddings & Storage Uses OpenAI embeddings to transform documents into vectors. Stores them in an in-memory vector store for retrieval. 🤖 AI Agent with Memory Built on LangChain Agent + GPT-4.1-mini. Performs similarity search in the vector store. Provides contextual answers with citations from the uploaded documents. Maintains short-term conversation memory for better continuity. 💬 Telegram Bot Integration Users can send questions directly to the bot. AI agent retrieves relevant information and replies with clear answers. ⚙️ How It Works Trigger: Upload a file into the Google Drive folder. Processing: Workflow downloads the file → loads → embeds → stores in vector memory. Query: User sends a question via Telegram. Retrieval & Response: AI agent searches stored documents → analyzes results → returns summarized answer in Telegram. 🔐 Requirements Google Drive OAuth credentials. OpenAI API key (for embeddings + LLM). Telegram Bot API token. 📥 Use Cases 📑 Knowledge base assistant – Upload internal docs and query them in chat. 🏫 Learning support – Students upload study materials and ask questions. 📊 Business intelligence – Teams upload reports and get instant summaries.

📘 Description This workflow automates a daily women-focused job discovery and delivery system. It runs every morning, fetches jobs from multiple targeted categories using SerpAPI, filters and ranks them based on relevance and recency, and uses AI to validate and format the best opportunities. The final curated list (top 3 jobs) is sent as a clean, readable digest to a Telegram channel. ⚙️ Step-by-Step Flow Daily 9AM Trigger (Schedule) Runs automatically every day at 9:00 AM to initiate the job discovery pipeline. Fetch Jobs (4 Parallel HTTP Requests) Pulls job listings from Google Jobs via SerpAPI across four categories: Women returnship programs Diversity hiring roles Remote jobs for women Female-focused hiring initiatives Merge All Results (Merge Node) Combines all fetched job results into a single unified dataset. Extract Job Items (Code Node) Normalizes raw API responses into structured fields: Title Company Location Description Apply link Source Keyword Filter (IF Node) Filters jobs using regex for relevance: women | diversity | returnship | female | remote Only matching jobs move forward. Rank by Recency & Take Top 3 (Code Node) Converts posting time (e.g., “2 days ago”) into numeric scores Sorts jobs by most recent Keeps only top 3 high-signal listings AI Agent: Validate & Format Job (OpenAI GPT-4o-mini) For each job: Verifies real relevance (rejects generic/senior/unrelated roles) Assigns category tag (👩 🌍 🏠 🔁) Generates clean, human-readable output Drops irrelevant jobs using IGNORE Build Telegram Digest Message (Code Node) Combines all formatted jobs into a single structured message with numbering and footer. Send Daily Digest to Telegram (Telegram Node) Delivers the final curated job digest to a Telegram chat/channel using HTML formatting. 🧩 Prerequisites • SerpAPI key (added in all HTTP nodes) • OpenAI API credential (GPT-4o-mini) • Telegram Bot API credential + Chat ID • Proper keyword alignment for filtering 💡 Key Benefits ✔ Fully automated daily job sourcing and curation ✔ Multi-source aggregation with deduplication logic ✔ AI-based quality filtering (removes noise) ✔ High-signal output (top 3 only, no clutter) ✔ Direct delivery to Telegram for instant consumption 👥 Perfect For Women-focused job communities and Telegram channels Career platforms targeting diversity hiring Returnship and re-entry job programs Curated job newsletter automation systems

📋 WORKFLOW OVERVIEW Automate reactions for Telegram Channel Posts - Automated Telegram reaction system for specific posts Flow: User sends message to a receiver bot AI parses request (emoji type & quantity) Code processes and validates data Loop sends reactions one by one User receives confirmation Key Features: Natural language processing by sending a message to a chat bot to react to a post on a different channel Reiterates through bot token rotation. This means that if you use 100 bots then you will be able to have 100 reactions per post of your choice Rate limit protection Error handling with helpful messages You will need to first add the bots that you personally own which can be acquired from BotFather to the channel that you would want them to react posts to and allow it to manage messages. Required Bot Permissions: Bot Must Be an Administrator The bot needs to be added as an admin to the channel (regular member status won't work for reactions). Specific Admin Rights Needed: When adding the bot as admin, you need to enable: ✅ "Post Messages" - This is actually the key permission needed ✅ "Add Subscribers" (optional, but sometimes required depending on channel settings) Credentials needed are: Target Channel ID, Bot tokens, Bot Receiver token, OpenAI API Example Usage: "https://t.me/channel/123 needs 10 hearts and 10 fire reactions If in need of help contact me at: elijahmamuri@gmail.com

Overview This n8n workflow automates the creation of viral CCTV-style animal videos using AI, perfect for TikTok content creators looking to capitalize on the popular security camera animal footage trend. The workflow generates realistic surveillance-style videos featuring random animals in humorous situations, complete with authentic CCTV aesthetics. How It Works The workflow runs on a 4-hour schedule and automatically: AI Prompt Generation: Uses GPT-5 to create hyper-realistic CCTV-style prompts with random animals, locations, and funny actions Video Creation: Generates videos using Veo3 AI with authentic security camera aesthetics (black & white, grainy, timestamp overlay) Content Optimization: AI creates viral TikTok titles and hashtags optimized for maximum engagement Multi-Platform Publishing: Automatically uploads to TikTok via Blotato and sends to Telegram Data Tracking: Stores all content in a data table for analytics and management Key Features Authentic CCTV Style**: Black & white, grainy quality, timestamp overlays, night vision effects Random Content**: 50+ animals, 30+ locations, 50+ hilarious actions for endless variety AI-Powered Titles**: GPT-4 generates compelling, SEO-optimized titles and viral hashtags Automated Publishing**: Direct TikTok posting with proper AI-generated content labeling Multi-Channel Distribution**: TikTok + Telegram for maximum reach Content Management**: Built-in data tracking and status management Perfect For TikTok content creators Social media managers AI automation enthusiasts Viral content strategists Pet/animal content creators Requirements OpenAI API key (for GPT-5 and GPT-4) Veo3 AI API access Blotato account (for TikTok posting) Telegram bot token n8n Cloud or self-hosted instance Customization Options Modify animal lists, locations, and actions Adjust scheduling frequency Change video aspect ratios Add more social platforms Customize AI prompts for different styles Categories Content Creation AI Automation Social Media Multimodal AI Tags #AI #TikTok #VideoGeneration #CCTV #Animals #ViralContent #Automation #SocialMedia

🎙️ Audio-to-Insights Workflow (Form Upload + Google Drive Link) Description This workflow enables seamless speech-to-text transcription, AI-powered summarization, sentiment analysis, and automated email delivery. It supports two different input modes: Form Upload (Local File)** Form Submission (Google Drive Link)** How it Works Input Form 1: Upload an audio file (e.g., .mp3,.wav,.mp4) Form 2: Submit a Google Drive link File Handling Local uploads go directly to AssemblyAI. Drive links are parsed → File ID extracted → File fetched → Sent to AssemblyAI. Transcription AssemblyAI generates transcript text with punctuation and highlights. Workflow loops with Wait + If until transcript status = completed. AI Analysis Transcript is passed to OpenAI. Generates a structured output including: Executive summary Sentiment label & score Key points Action items Notable quotes Topics Email Delivery A formatted email is sent via Gmail with the summary and insights. Features Dual input support: Google Drive OR direct upload Handles long-running jobs with Wait + If polling AI-powered transcript analysis with structured JSON Automated sentiment scoring and summary generation Professional HTML email reports Requirements AssemblyAI API Key – transcription Google Drive OAuth2 – file fetch OpenAI API Key – summarization & sentiment analysis Gmail OAuth2 – email delivery How to Use Import this workflow into your n8n instance. Add and configure the required credentials. Update placeholders for: AssemblyAI API Key Google Drive Link Gmail ID Trigger via either form (local file or Google Drive link). 5.For long recordings, split before uploading (10–20 min per chunk, 2–5s overlap).Keep audio consistent (e.g., WAV/MP3, 16 kHz mono if possible).Process chunks sequentially and combine summaries/action items at the end. Customising this Workflow Adjust the OpenAI prompt to fit your reporting style (executive summary, bullet points, etc.). Extend email formatting with logos or branding. Add Slack, CRM, or Notion integrations for distribution. Use Cases Meeting or lecture transcription with summaries Podcast analysis with highlights and quotes Business call reviews with action item extraction Academic seminar notes emailed automatically

Revenue Growth Strategy with CRO-led Multi-Agent Team using O3 & GPT-4.1-mini 🔥 Powered by OpenAI O3 & GPT-4.1-mini Multi-Agent System \#RevOps #n8nWorkflows #AIRevenue #OpenAI #GrowthHacking ⚡ Section 1: Start & Orchestrator 💬 Chat Trigger* → Listens for revenue-related requests (e.g., *“Optimize our sales funnel”). 🤖 CRO Agent (O3)* → Acts as the *Chief Revenue Officer**. Thinks strategically with the Think Node. Decides which specialist agents to call. 🧠 OpenAI O3 Model** → Provides advanced reasoning for CRO decisions. Benefit: Central orchestration ensures every request gets a strategic, executive-level response before delegation. 🛠️ Section 2: Specialist Agents Each specialist agent uses GPT-4.1-mini for fast, cost-effective execution. They receive the CRO’s instructions and return insights. 📈 Sales Pipeline Analyst Funnel optimization, conversion tracking, bottleneck fixes. Outputs: Pipeline health, drop-off points, recommendations. 🎯 Revenue Attribution Specialist Multi-touch attribution, ROI analysis, campaign efficiency. Outputs: Attribution models, marketing ROI. 📊 Revenue Forecasting Analyst Predictive modeling, scenario planning, growth projections. Outputs: Forecast reports, “what-if” scenarios. ⚙️ Revenue Operations Manager CRM optimization, territory planning, sales automation. Outputs: Process improvements, efficiency boosts. 💰 Pricing & Packaging Strategist Competitive pricing analysis, packaging strategy, revenue optimization. Outputs: Price models, package recommendations. 🧠 Revenue Intelligence Analyst BI dashboards, performance tracking, KPI insights. Outputs: Reports with actionable intelligence. Benefit: Breaks complex revenue problems into specialized tasks handled by domain experts. 🔄 Section 3: Feedback & Integration Each agent → sends results back to CRO Agent. CRO Agent → compiles a comprehensive revenue strategy. Can integrate with CRM, BI dashboards, or Slack/Email for delivery. Benefit: Clear, actionable insights delivered in one place — like having a virtual RevOps team on demand. 📊 Workflow Overview | Section | Key Nodes | Purpose | Benefit | | ----------------------- | ----------------------------------- | ------------------------------------------------- | ------------------------------------ | | ⚡ Start & Orchestration | Chat Trigger, CRO Agent, O3 Model | Capture request & assign to CRO | Centralized leadership | | 🛠️ Specialists | 6 Agent Nodes + GPT-4.1-mini models | Analyze pipeline, pricing, ops, attribution, etc. | Specialized, cost-efficient insights | | 🔄 Feedback Loop | CRO Agent aggregation | Compiles strategy from multiple agents | Unified, data-driven revenue plan | 💡 Use Cases Pipeline Optimization** → Identify bottlenecks, improve conversions. Attribution Modeling** → Know exactly where revenue comes from. Revenue Forecasting** → Plan growth scenarios and projections. Ops Excellence** → Automate CRM, streamline sales ops. Pricing Strategy** → Compete smarter with optimized pricing models. Revenue Intelligence** → Ongoing tracking and performance monitoring. 💸 Cost Optimization O3 only for CRO decisions** → Strategic layer. GPT-4.1-mini for specialists** → Low-cost execution (\~90% cheaper). Parallel processing** → All agents can run simultaneously. ✅ Final Result: A virtual AI-powered RevOps team that turns any revenue-related question into a comprehensive growth strategy — instantly.

Adaptive LLM Router for Optimized AI Chat Responses Elevate your AI chatbots with intelligent model selection: automatically route simple queries to cost-effective LLMs and complex ones to powerful ones, balancing performance and expenses seamlessly. What It Does This workflow listens for chat messages, uses a lightweight Gemini model to classify query complexity, then selects and routes to the optimal LLM (Gemini 2.5 Pro for complex, OpenAI GPT-4.1 Nano for simple) to generate responses—ensuring efficient resource use. Key Features Complexity Classifier** - Quick assessment using Gemini 2.0 Flash Dynamic Model Switching** - Routes to premium or budget models based on needs Chat Trigger** - Webhook-based for real-time conversations Current Date Awareness** - Injects $now into system prompt Modular Design** - Easy to add more models or adjust rules Cost Optimization** - Reserves heavy models for demanding tasks only Perfect For Chatbot Developers**: Build responsive, cost-aware AI assistants Customer Support**: Handle routine vs. technical queries efficiently Educational Tools**: Simple facts vs. in-depth explanations Content Creators**: Quick ideas vs. detailed writing assistance Researchers**: Basic lookups vs. complex analysis Business Apps**: Optimize API costs in production environments Technical Highlights Harnessing n8n's LangChain nodes, this workflow demonstrates: Webhook triggers for instant chat handling Agent-based classification with strict output rules Conditional model selection for AI chains Integration of multiple LLM providers (Google Gemini, OpenAI) Scalable architecture for expanding model options Ideal for minimizing AI costs while maximizing response quality. No coding required—import, configure credentials, and deploy!

Who’s it for This template is designed for traders, investors, and finance enthusiasts who want quick stock insights and technical analysis delivered directly in Telegram. It’s ideal for anyone who wants to explore candlestick patterns, MACD signals, volume trends, and market sentiment without switching between multiple tools. What it does A Telegram Trigger starts the workflow whenever a user sends a message. The AI Agent (powered by OpenAI) engages in a professional yet friendly conversation about stocks and finance. If a ticker symbol is provided, the agent uses the Get Chart workflow to fetch and analyze the chart. The workflow generates candlestick, MACD, and volume insights, returning both the chart image and a plain-language breakdown of key patterns, support/resistance levels, and momentum signals. Results are sent back to the user in Telegram. How to set up Connect your Telegram account in the Telegram Trigger and Send nodes. Add your Chart-IMG API key in the HTTP Request node (Get Chart URL). Connect your OpenAI account to power the AI Agent. Deploy the workflow and start interacting with your Telegram bot. Requirements Telegram bot credentials OpenAI API key Chart-IMG API key How to customize the workflow Adjust the technical indicators (e.g., timeframe, studies like RSI or Bollinger Bands) in the Get Chart URL node. Fine-tune the AI Agent’s tone or level of detail in its system prompt. Modify sticky notes for clarity or to add setup instructions.

Chat with Your GitHub Issues Using AI 🤖 Ever wanted to just ask your repository what's going on instead of scrolling through endless issue lists? This workflow lets you do exactly that. What Does It Do? Turn any GitHub repo into a conversational knowledge base. Ask questions in plain English, get smart answers powered by AI and vector search. "Show me recent authentication bugs"** → AI finds and explains them "What issues are blocking the release?"** → Instant context-aware answers "Are there any similar problems to #247?"** → Semantic search finds connections you'd miss The Magic ✨ Slurp up issues from your GitHub repo (with all the metadata goodness) Vectorize everything using OpenAI embeddings and store in Redis Chat naturally with an AI agent that searches your issue database Get smart answers with full conversation memory Quick Start You'll need: OpenAI API key (for the AI brain) Redis 8.x (for vector search magic) GitHub repo URL (optional: API token for speed) Get it running: Drop in your credentials Point it at your repo (edit the owner and repository params) Run the ingestion flow once to populate the database Start chatting! Tinker Away 🔧 This is your playground. Here are some ideas: Swap the data source**: Jira tickets? Linear issues? Notion docs? Go wild. Change the AI model**: Try different GPT models or even local LLMs Add custom filters**: Filter by labels, assignees, or whatever matters to you Tune the search**: Adjust how many results come back, tweak relevance scores Make it public**: Share the chat interface with your team or users Auto-update**: Hook it up to webhooks for real-time issue indexing Built with n8n, Redis, and OpenAI. No vendor lock-in, fully hackable, 100% yours to customize.

This workflow automatically scores and categorizes new GoHighLevel contacts using AI (GPT-4), then tags and assigns them to the appropriate team member based on their score. Hot leads also trigger a Slack notification for immediate follow-up. What does it do? Triggers when a new contact is added in GoHighLevel. Fetches full contact details and recent engagement data. Uses AI (GPT-4) to analyze and score the lead (1-100), categorize it (Hot, Warm, Cold), and provide an explanation. Tags the contact in GoHighLevel based on the score. Assigns the lead to the correct sales or nurturing team member. Sends a Slack alert for Hot leads to ensure fast response. Use case Use this workflow to automate lead qualification and assignment in sales teams using GoHighLevel. It helps prioritize high-quality leads, ensures fast follow-up, and reduces manual work. How to configure GoHighLevel API: Set your GoHighLevel API URL and API key in the Workflow Configuration node. Update user IDs for assignment as needed. Slack Integration: Add your Slack webhook URL or credentials in the Slack Notify Hot Lead node. AI Provider: Configure your OpenAI (or compatible) credentials in the AI Lead Scoring (GPT-4) node. Adjust thresholds: If needed, change the score thresholds in the IF nodes to match your business logic. Activate the workflow: Once configured, activate the workflow to start processing new leads automatically. Tip: You can further customize the workflow to fit your sales process, add more notifications, or integrate with other tools as needed.