Workflow Templates

Gmail Lead Reply Analyzer → HubSpot Task + Slack Alert Most sales teams read every email, guess if it’s important, and tell teammates manually. This workflow does it automatically: check intent and sentiment with AI, create follow-up tasks, send Slack alerts, and save everything to Google Sheets. Benefits AI checks sentiment, intent, urgency, and priority Creates HubSpot tasks only if follow-up is needed Sends Slack message with lead summary Logs all results to Google Sheets for tracking Runs 24/7 with no manual sorting How It Works Gmail trigger watches a label for new replies Workflow extracts sender, subject, and message AI analyzes message and returns: sentiment, intent, urgency, next step Code step cleans result, adds date, and checks if follow-up is needed If follow-up = yes → create HubSpot task, send Slack alert, log to Sheets If follow-up = no → just log to Sheets Who Is This For Sales teams getting many leads by email Founders who handle leads themselves Agencies needing clear and fast lead triage Setup Connect Gmail (choose or create label) Add OpenAI API key (model: GPT-4o mini) Connect HubSpot (App Token for tasks) Connect Slack (channel for alerts) Connect Google Sheets (Spreadsheet + Tab) Optional: change how urgency/priority is scored in the code ROI & Monetization Save 3–6 hours per week on email sorting Answer faster and close more deals Sell as $1k–$3k/month “inbox automation” service Strategy Insights In the full walkthrough, I show how to: Make sure AI always returns valid JSON Adjust what counts as a follow-up lead Format Slack messages for quick reading Use Google Sheets as a simple dashboard Check Out My Channel For more AI automation systems that get real results, check out my YouTube channel where I share exactly how I build automation workflows, sell high-value services, and scale to $20k+ monthly revenue.

Your inbox is overflowing with daily newsletters: Public Affairs, ESG, Legal, Finance, you name it. You want to stay informed, but reading 10 emails every morning? Impossible. What if you could get one single digest summarizing everything that matters, automatically? ❌ No more copy-pasting text into ChatGPT ❌ No more scrolling through endless email threads ✅ Just one smart, structured daily briefing in your inbox Who Is This For Public Affairs Teams: Stay ahead of political and regulatory updates—without drowning in emails. Executives & Analysts: Get daily summaries of key insights from multiple newsletters. Marketing, Legal, or ESG Departments: Repurpose this workflow for your own content sources. How It Works Gmail collects all newsletters from the day (based on sender or label). HTML noise and formatting are stripped automatically. Long texts are split into chunks and logged in Google Sheets. An AI Agent (Gemini or OpenAI) summarizes all content into one clean daily digest. The workflow structures the summary into an HTML email and sends it to your chosen recipients. Setup Guide • You’ll need Gmail and Google Sheets credentials. • Add your own AI Model (e.g., Gemini or OpenAI) with an API key. • Adjust the prompt inside the “Public Affairs Consultant” node to fit your topic (e.g., Legal, Finance, ESG, Marketing). • Customize the email subject and design inside the “Structure HTML-Mail” node. • Optional: Use Memory3 to let the AI learn your preferred tone and style over time. Cost & Runtime Runs once per day. Typical cost: ~$0.10–0.30 per run (depending on model and input length). Average runtime: <2 minutes.

This workflow automates brand monitoring on X by analyzing both the text and the images in posts. It uses multi-modal AI to score brand relevance, filters out noise, logs important mentions in Airtable, and sends real-time alerts to a Telegram group for high-priority posts. What it does Traditional brand monitoring tools often miss the most authentic user content because they only track text. They can't "see" your logo in a photo or your product featured in a video without a direct keyword mention. This workflow acts as an AI agent that overcomes this blind spot. It finds mentions of your brand on X and then uses Google Gemini's multi-modal capabilities to perform a comprehensive analysis of both the text and any attached images. This allows it to understand the full context of a mention, score its relevance to your brand, and take the appropriate action, creating a powerful "visual intelligence" system. How it works The workflow runs on a schedule to find, analyze, and triage brand mentions. Get New Tweets: The workflow begins by using an Apify actor to scrape X for recent posts based on a defined set of search terms (e.g., Tesla OR $TSLA). It then filters these results to find unique mentions not already processed. Check for Duplicates: It cross-references each found tweet with an Airtable base to ensure it hasn't been analyzed before, preventing duplicate work. Analyze Post Content: For each new, unique post, the workflow performs two parallel analyses using Google Gemini: Analyze the Photos: The AI examines the images in the post to describe the scene, identify logos or products, and determine the visual mood. Analyze the Text: A separate AI call analyzes the text of the post to understand its context and sentiment. Final Relevance Check: A "Head Strategist" AI node receives the outputs from both the visual and text analyses. It synthesizes this information to assign a final brand relevance score from 1 to 10. Triage and Action: Based on this score, the workflow automatically triages the post: High Relevance (Score > 7): The post is logged in the Airtable base, and an instant, detailed alert is sent to a Telegram monitoring group. Medium Relevance (Score 4-7): The post is quietly logged in Airtable for later strategic review. Low Relevance (Score < 4): The post is ignored, effectively filtering out noise. Setup Instructions To get this workflow running, you will need to configure your Airtable base and provide credentials for Apify, Google, and Telegram. Required Credentials Apify: You will need an Apify API Token to run the X scraper. Airtable: You will need Airtable API credentials to connect to your base. Google AI: You will need credentials for the Google AI APIs to use the Gemini models. Telegram: You will need a Bot Token and the Chat ID for the channel where you want to receive high-relevance alerts. Of course. Based on the Config node parameters you provided, the setup process is much more centralized. Here is the corrected and rewritten "Step-by-Step Configuration" section. Of course. Here is the rewritten "Step-by-Step Configuration" section with the link to the advanced search documentation. Step-by-Step Configuration Set up Your Airtable Base: Before configuring the workflow, create a new table in your Airtable base. For the workflow to function correctly, this table must contain fields to store the analysis results. Create fields with the following names: postId, postURL, postText, postDateCreated, authorUsername, authorName, sentiment, relevanceScore, relevanceReasoning, mediaPhotosAnalysis, and status. Once the table is created, have your Base ID and Table ID ready to use in the Config node. Edit the Config Node: The majority of the setup is handled in the first Config node. Click on it and edit the following parameters in the "Expressions" tab: searchTerms: Replace the example with the keywords, hashtags, and accounts you want to monitor. The field supports advanced search operators for complex queries. For a full list of available parameters, see the Twitter Advanced Search documentation. airtableBaseId: Paste your Airtable Base ID here. airtableTableId: Paste your Airtable Table ID here. lang: Set the two-letter language code for the posts you want to find (e.g., "en" for English). min_faves: Set the minimum number of "favorites" a post should have to be considered. tweetsToScrape: Define the maximum number of posts the scraper should find in each run. actorId: This is the specific Apify actor for scraping X. You can leave this as is unless you intend to use a different one. Configure the Telegram Node: In the final node, "Send High Relevance Posts to Monitoring Group", you need to manually set the destination for the alerts. Enter the Chat ID for your Telegram group or channel. How to Adapt the Template This workflow is a powerful framework that can be adapted for various monitoring needs. Change the Source:* Replace the *Apify** node with a different trigger or data source. You could monitor Reddit, specific RSS feeds, or a news API for mentions. Customize the AI Logic:* The core of this workflow is in the AI prompts. You can edit the prompts in the *Google Gemini** nodes to change the analysis criteria. For example, you could instruct the AI to check for specific competitor logos, analyze the sentiment of comments, or identify if the post is from an influential account. Modify the Scoring:** Adjust the logic in the "Switch" node to change the thresholds for what constitutes a high, medium, or low-relevance post to better fit your brand's needs. Change the Actions:* Replace the *Telegram** node with a different action. Instead of sending an alert, you could: Create a ticket in a customer support system like Zendesk or Jira. Send a summary email to your marketing team. Add the post to a content curation tool or a social media management platform.

Here’s a clean, English-only template description you can paste into the n8n “Description” field. Overview This workflow analyzes customer survey responses, groups them by sentiment (positive / neutral / negative), generates themes and insights with an AI agent, and delivers a consolidated report to your destinations (Google Sheets, Slack). It runs on a daily schedule and uses batch-based AI analysis for accuracy. Flow: Schedule → Fetch from Sheets → Group & batch (Code) → AI analysis → Aggregate → Save/Notify (Sheets, Slack) What You’ll Need A survey data source (Google Sheets recommended) AI model credentials (e.g., OpenAI or OpenRouter) Optional destinations: Google Sheets (summary sheet), Slack channel Setup Data source (Google Sheets) In Get Survey Responses, replace YOUR_SHEET_ID and YOUR_SHEET_NAME with your sheet details. Ensure the sheet includes columns like: 満足度 (Rating), 自由記述コメント (Comment), 回答日時 (Timestamp). AI model Add credentials to your preferred LLM node (OpenAI/OpenRouter). Keep the prompt’s JSON-only requirement so the structured parser can consume it reliably. Destinations Save to Sheet: set your output documentId / sheetName. Slack: set the target channelId on the Slack node. How It Works Daily Schedule Trigger — starts the workflow at your chosen time. Get Survey Responses (Sheets) — reads survey data. Group & Prepare Data (Code) — classifies by rating (>=4: positive, =3: neutral, <3: negative) and creates batches (max 50 per batch). Loop Over Batches — feeds each sentiment batch to the AI separately for cleaner signals. Analyze Survey Batch (AI Agent) — returns structured JSON: themes, insights, recommendations. Add Metadata (Code) — attaches original sentiment and item counts to each AI result. Aggregate Results (Code) — merges all batches; outputs Top Themes, Key Insights, Priority Recommendations, and an Executive Summary. Save to Sheet / Slack — appends the summary to a sheet and posts highlights to Slack. Data Assumptions (Columns) Your source should include at least: 満足度 (Rating) — integer 1–5 自由記述コメント (Comment) — string 回答日時 (Timestamp) — ISO string or date Outputs Consolidated summary** containing: Top themes (with example quotes) Key insights Priority recommendations Executive summary Destinations**: Google Sheets (one row per run) and Slack (high-level highlights) Customize Adjust sentiment thresholds (e.g., require >=5 for positive) or batch size (default 50) in the Code node. Tailor the AI prompt or the output JSON schema to your domain. Add more outputs (CSV export, database insert, additional channels) in parallel after the Aggregate step. Before You Run (Checklist) [ ] Add credentials for Sheets / AI / Slack in Credentials [ ] Update documentId, sheetName, and Slack channelId [ ] Confirm your column names match the Code node references [ ] Verify schedule time and timezone (e.g., Asia/Tokyo) Troubleshooting Parser errors on AI output: ensure the model response is **JSON-only; reduce temperature or simplify schema if needed. Only some batches run**: check batch size in Loop and ensure each sentiment bucket actually contains responses. No output to Sheets/Slack**: verify credentials, IDs, and required fields; confirm permissions. Security & Template Notes Do not include credentials in the template file. Users add their own after import. Use Sticky Notes to document Overview, Setup, Processing Logic, and Output choices. This template already includes guideline-friendly notes.

Description Automatically consolidate Zendesk and Freshdesk ticket data into a unified performance dashboard with KPI calculations, Google Sheets logging, real-time Slack alerts, and weekly Gmail email reports. Provides complete visibility into support operations, SLA compliance, and customer satisfaction across multiple platforms. 📊💬📧 What This Template Does Runs weekly on schedule to fetch tickets from both Zendesk and Freshdesk. ⏰ Merges ticket data into a standardized JSON structure with normalized priorities, statuses, and channels. 🔄 Logs all tickets and metadata into Google Sheets for audit-ready performance tracking. 📑 Calculates advanced KPIs including resolution rates, SLA breaches, CSAT score estimation, urgent ticket rates, and performance grading. 📊 Evaluates alert conditions (e.g., high SLA breach, low CSAT, backlog risk). 🚨 Sends formatted Slack alerts with performance grades, key metrics, and recommendations. 💬 Generates corporate-style HTML weekly reports and delivers them via Gmail. 📧 Key Benefits Unifies Zendesk and Freshdesk data into one consistent reporting flow. 🌐 Provides actionable KPIs for SLA monitoring, customer satisfaction, and backlog health. ⏱️ Ensures leadership visibility with Google Sheets logs and professional email reports. 🧾 Alerts the support team instantly on Slack when performance drops. 🚨 Reduces manual data analysis with automated grading and recommendations. 🤖 Features Multi-Platform Ticket Integration – Fetches tickets from Zendesk and Freshdesk. 🎫 Data Normalization – Cleans descriptions, maps priorities/statuses, and detects escalations. 🧼 Google Sheets Logging – Tracks tickets with IDs, URLs, tags, timestamps, and metadata. 📈 KPI Calculation Engine – Computes SLA breach rate, resolution rate, CSAT, escalation %, and more. 🧮 Performance Grading – Grades support performance (A–D) with detailed descriptions. 🏅 Slack Alerts – Notifies with active alerts, recommendations, and emoji-based health signals. 📢 Weekly Gmail Reports – Delivers branded HTML reports for management and audits. ✨ Requirements n8n instance (cloud or self-hosted). Zendesk API credentials with ticket read access. Freshdesk API credentials with ticket read access. Google Sheets OAuth2 credentials with spreadsheet write permissions. Slack Bot API credentials with posting permissions. Gmail OAuth2 credentials with send email permissions. Pre-configured Google Sheet for KPI logging. Target Audience Support managers overseeing multi-platform ticketing systems. 👩‍💻 Customer success teams monitoring SLA compliance and CSAT health. 🚀 SMBs running Zendesk + Freshdesk who need unified dashboards. 🏢 Remote/global support teams needing automated KPI visibility. 🌐 Executives requiring weekly performance reports and recommendations. 📈 Step-by-Step Setup Instructions Connect Zendesk, Freshdesk, Google Sheets, Slack, and Gmail credentials in n8n. 🔑 Update the Google Sheet ID in the “Log KPIs in Google Sheets” node. 📊 Configure Slack channel ID for alerts (default: zendesk-churn-alerts). 💬 Replace {Enter Your Email} in the Gmail node with your recipient email. 📧 Adjust thresholds in the KPI calculation node (default: 4h response, 24h resolution). ⏱️ Test with sample tickets to validate Sheets logging, Slack alerts, and Gmail reports. ✅ Deploy on schedule (default: weekly at 8 PM) for continuous tracking. 🗓️

🧾An intelligent automation system that turns WhatsApp into your personal receipt manager — integrating Meta WhatsApp Cloud API, Google Drive, Google Sheets, and OpenAI GPT-4o-mini via n8n. 🎥 Demo: Watch the Loom walkthrough ⚙️ What It Does The AI-Powered WhatsApp Receipt Bot automates the complete invoice handling process through a conversational interface. Workflow Summary: User sends a receipt image via WhatsApp. The bot automatically downloads the media using the WhatsApp Cloud API. The image is uploaded to a Google Drive “Invoices” folder. The file is shared publicly, generating a shareable URL. The receipt is analyzed using OpenAI GPT-4o-mini to extract structured data: Store name Items purchased Payment method Total amount The extracted details are appended to a Google Sheet for record-keeping. The bot sends a human-readable summary back to WhatsApp with emojis and the invoice link. Output Example: 🏬 Store: Big Bazaar 📝 Items: Rice, Detergent, Snacks 💳 Payment: Card 💰 Total: ₹1520.75 🔗 Link: https://drive.google.com/file/d/1abcXYZ/view This system eliminates manual expense tracking, improves accuracy through OCR, and provides a seamless way to manage receipts in real time. 💡 Use Cases | Scenario | Description | | ------------------------------------- | --------------------------------------------------------------------------------------------------------------------- | | Personal Expense Management | Automatically store and categorize receipts from daily purchases. | | Business Accounting | Collect employee expense receipts through WhatsApp and centralize them in Google Sheets. | | Freelancer or Consultant Tracking | Keep a digital record of client reimbursements or software purchase receipts. | | Family Budgeting | Family members send receipts to one shared WhatsApp number, all data gets logged centrally. | | E-commerce / Delivery Teams | Drivers or delivery agents send invoices from the field to WhatsApp; data automatically goes to the accounting sheet. | 🔧 Setup 1. Accounts and Tools Needed | Tool | Purpose | Link | | -------------------------- | ------------------------------------------- | -------------------------------------------------------------------------------------------- | | Meta Developer Account | To access WhatsApp Business Cloud API | https://developers.facebook.com/apps | | Google Cloud Account | For enabling Drive and Sheets APIs | https://console.cloud.google.com | | n8n Instance | Workflow automation engine (local or cloud) | https://app.n8n.cloud | | OpenAI API Key | For GPT-4o-mini model OCR + reasoning | https://platform.openai.com/account/api-keys | 2. Meta Developer Setup (WhatsApp Cloud API) Go to Meta Developer Dashboard → My Apps → Create App → Business type. Add WhatsApp product under your app. Retrieve the following from WhatsApp > Configuration: Permanent Access Token Phone Number ID WhatsApp Business Account ID Add these credentials in n8n → Credentials → WhatsApp API. Use the same credentials for WhatsApp Trigger and Send Message nodes. Verify webhook in Meta with your n8n webhook URL. Important: In your HTTP Node, set the header as: Authorization: Bearer <access_token> Replace <access_token> with your WhatsApp Cloud API permanent token. Without this, the workflow will fail to send or receive WhatsApp messages properly. 3. Google Drive Setup Create a folder named Invoices on your Google Drive. Copy the Folder ID (found in the Drive URL). In Google Cloud Console → APIs & Services → Enable APIs: Enable Google Drive API Enable Google Sheets API Go to Credentials → Create Credentials → OAuth 2.0 Client ID. Download the credentials.json file. Upload this to n8n → Credentials → Google Drive OAuth2 API. Authorize the connection on first workflow run. 4. Google Sheets Setup Create a new Google Sheet titled Invoices. Add the following headers in Row 1: store name | discription | image_url | payment | total Copy the Sheet ID (from the URL). Add the ID under the Google Sheets Append node in n8n. Map each field to its corresponding value extracted from the OCR result. 5. OpenAI Setup Generate an API key from https://platform.openai.com/account/api-keys. Add it to n8n → Credentials → OpenAI API. Use model gpt-4o-mini in the “Analyze Image” node. Can upgrade to gpt-4o for better OCR accuracy if account supports it. 6. n8n Workflow Setup Import the provided n8n workflow JSON. Configure credentials for: WhatsApp API Google Drive OAuth2 Google Sheets OAuth2 OpenAI API Activate workflow and set webhook in Meta Developer console. Send a test receipt image to your WhatsApp Business number. The bot will automatically: Download → Upload → Extract → Log → Summarize → Reply 📊 Example Google Sheet Record | store name | discription | image_url | payment | total | | ---------- | ----------------------- | -------------------------------------------------------------------------------------------- | ------- | ------- | | Big Bazaar | Rice, Detergent, Snacks | https://drive.google.com/file/d/1abcXYZ/view | Card | 1520.75 | 🧠 Result A fully automated AI pipeline that transforms WhatsApp into a smart expense-tracking interface — integrating vision, automation, and natural language processing for zero-manual financial documentation. Support & Contact: If you face any issues during setup or execution, contact: 📧 Email: atharvapj5@gmail.com 🔗 LinkedIn: Atharva Jaiswal

Overview Use your voice or text to command a Telegram-based AI agent that scrapes leads or generates detailed research reports—instantly. This workflow turns your Telegram bot into a full-blown outbound machine. Just tell it what type of leads you need, and it’ll use Apollo to find and save them into a spreadsheet. Or drop in a LinkedIn profile, and it’ll generate a personalized research dossier with info like job title, company summary, industry insights, and more. It handles voice messages too—just speak your request and get the results sent back like magic. Who’s it for Cold emailers and growth marketers Solo founders running outbound SDRs doing daily prospecting Agencies building high-quality lead lists or custom research for clients How it works Triggered by a message (text or voice) in Telegram If it’s voice, it transcribes using OpenAI Whisper Uses an AI agent to interpret intent: scrape leads or research a person For lead scraping: Gathers criteria (e.g., location, job title) via Telegram Calls the Apollo API to return fresh leads Saves the leads to Google Sheets For research reports: Takes a LinkedIn profile link Uses AI and lead data tools to create a 1-page professional research report Sends it back to the user via email Example outputs Lead scraping**: Populates a spreadsheet with names, roles, LinkedIn links, company info, emails, and more Research report**: A formatted PDF-style brief with summary of the person, company, and key facts How to set up Connect your Telegram bot to n8n Add your OpenAI credentials (for Whisper + Chat agent) Plug in your Apollo API key or scraping tool Replace the example spreadsheet with your own Customize the prompts for tone or data depth (Optional) Add PDF generation or CRM sync Requirements Telegram Bot Token OpenAI API Key Apollo (or other scraping API) credentials LinkedIn URLs for research functionality How to customize Replace Apollo with Clay, People Data Labs, or another scraping tool Add a CRM push step (e.g. Airtable, HubSpot, Notion) Add scheduling to auto-scrape daily Reformat the research report as a downloadable PDF Change the agent’s tone or role (e.g. “Outreach Assistant,” “Investor Scout,” etc.)

Who this is for? This workflow is designed for: Marketing analysts, **SEO specialists, and content strategists who want automated intelligence on their online competitors. Growth teams** that need quick insights from SERP (Search Engine Results Pages) without manual data scraping. Agencies** managing multiple clients’ SEO presence and tracking competitive positioning in real-time. What problem is this workflow solving? Manual competitor research is time-consuming, fragmented, and often lacks actionable insights. This workflow automates the entire process by: Fetching SERP results from multiple search engines (Google, Bing, Yandex, DuckDuckGo) using Thordata’s Scraper API. Using OpenAI GPT-4.1-mini to analyze, summarize, and extract keyword opportunities, topic clusters, and competitor weaknesses. Producing structured, JSON-based insights ready for dashboards or reports. Essentially, it transforms raw SERP data into strategic marketing intelligence — saving hours of research time. What this workflow does Here’s a step-by-step overview of how the workflow operates: Step 1: Manual Trigger Initiates the process on demand when you click “Execute Workflow.” Step 2: Set the Input Query The “Set Input Fields” node defines your search query, such as: > “Top SEO strategies for e-commerce in 2025” Step 3: Multi-Engine SERP Fetching Four HTTP request tools send the query to Thordata Scraper API to retrieve results from: Google Bing Yandex DuckDuckGo Each uses Bearer Authentication configured via “Thordata SERP Bearer Auth Account.” Step 4: AI Agent Processing The LangChain AI Agent orchestrates the data flow, combining inputs and preparing them for structured analysis. Step 5: SEO Analysis The SEO Analyst node (powered by GPT-4.1-mini) parses SERP results into a structured schema, extracting: Competitor domains Page titles & content types Ranking positions Keyword overlaps Traffic share estimations Strengths and weaknesses Step 6: Summarization The Summarize the content node distills complex data into a concise executive summary using GPT-4.1-mini. Step 7: Keyword & Topic Extraction The Keyword and Topic Analysis node extracts: Primary and secondary keywords Topic clusters and content gaps SEO strength scores Competitor insights Step 8: Output Formatting The Structured Output Parser ensures results are clean, validated JSON objects for further integration (e.g., Google Sheets, Notion, or dashboards). 4. Setup Prerequisites n8n Cloud or Self-Hosted instance** Thordata Scraper API Key** (for SERP data retrieval) OpenAI API Key** (for GPT-based reasoning) Setup Steps Add Credentials Go to Credentials → Add New → HTTP Bearer Auth → Paste your Thordata API token. Add OpenAI API Credentials for the GPT model. Import the Workflow Copy the provided JSON or upload it into your n8n instance. Set Input In the “Set the Input Fields” node, replace the example query with your desired topic, e.g.: “Google Search for Top SEO strategies for e-commerce in 2025” Execute Click “Execute Workflow” to run the analysis. How to customize this workflow to your needs Modify Search Query Change the search_query variable in the Set Node to any target keyword or topic. Change AI Model In the OpenAI Chat Model nodes, you can switch from gpt-4.1-mini to another model for better quality or lower cost. Extend Analysis Edit the JSON schema in the “Information Extractor” nodes to include: Sentiment analysis of top pages SERP volatility metrics Content freshness indicators Export Results Connect the output to: Google Sheets / Airtable** for analytics Notion / Slack** for team reporting Webhook / Database** for automated storage Summary This workflow creates an AI-powered Competitor Intelligence System inside n8n by blending: Real-time SERP scraping (Thordata) Automated AI reasoning (OpenAI GPT-4.1-mini) Structured data extraction (LangChain Information Extractors)

A robust n8n workflow designed to enhance Telegram bot functionality for user management and broadcasting. It facilitates automatic support ticket creation, efficient user data storage in Redis, and a sophisticated system for message forwarding and broadcasting. How It Works Telegram Bot Setup: Initiate the workflow with a Telegram bot configured for handling different chat types (private, supergroup, channel). User Data Management: Formats and updates user data, storing it in a Redis database for efficient retrieval and management. Support Ticket Creation: Automatically generates chat tickets for user messages and saves the corresponding topic IDs in Redis. Message Forwarding: Forwards new messages to the appropriate chat thread, or creates a new thread if none exists. Support Forum Management: Handles messages within a support forum, differentiating between various chat types and user statuses. Broadcasting System: Implements a broadcasting mechanism that sends channel posts to all previous bot users, with a system to filter out blocked users. Blocked User Management: Identifies and manages blocked users, preventing them from receiving broadcasted messages. Versatile Channel Handling: Ensures that messages from verified channels are properly managed and broadcasted to relevant users. Set Up Steps Estimated Time**: Around 30 minutes. Requirements**: A Telegram bot, a Redis database, and Telegram group/channel IDs are necessary. Configuration**: Input the Telegram bot token and relevant group/channel IDs. Configure message handling and user data processing according to your needs. Detailed Instructions**: Sticky notes within the workflow provide extensive setup information and guidance. Live Demo Workflow Bot: Telegram Bot Link (Click here) Support Group: Telegram Group Link (Click here) Broadcasting Channel: Telegram Channel Link (Click here) Keywords: n8n workflow, Telegram bot, chat ticket system, Redis database, message broadcasting, user data management, support forum automation

AI-Powered Financial Document Processing with Google Gemini This comprehensive workflow automates the complete financial document processing pipeline using AI. Upload invoices via chat, drop expense receipts into a folder, or add bank statements - the system automatically extracts, categorizes, and organizes all your financial data into structured Google Sheets. What this workflow does Processes three types of financial documents automatically: Invoice Processing**: Upload PDF invoices through a chat interface and get structured data extraction with automatic file organization Expense Management**: Monitor a Google Drive folder for new receipts and automatically categorize expenses using AI Bank Statement Processing**: Extract and organize transaction data from bank statements with multi-transaction support Financial Analysis**: Query all your financial data using natural language with an AI agent Key Features Multi-AI Persona System**: Four specialized AI personas (Mark, Donna, Victor, Andrew) handle different financial functions Google Gemini Integration**: Advanced document understanding and data extraction from PDFs Smart Expense Categorization**: Automatic classification into 17 business expense categories using LLM Real-time Monitoring**: Continuous folder watching for new documents with automatic processing Natural Language Queries**: Ask questions about your financial data in plain English Automatic File Management**: Intelligent file naming and organization in Google Drive Comprehensive Error Handling**: Robust processing that continues even when individual documents fail How it works Invoice Processing Flow User uploads PDF invoice via chat interface File is saved to Google Drive "Invoices" folder Google Gemini extracts structured data (vendor, amounts, line items, dates) Data is parsed and saved to "Invoice Records" Google Sheet File is renamed as "{Vendor Name} - {Invoice Number}" Confirmation message sent to user Expense Processing Flow User drops receipt PDF into "Expense Receipts" Google Drive folder System detects new file within 1 minute Google Gemini extracts expense data (merchant, amount, payment method) OpenRouter LLM categorizes expense into appropriate business category All data saved to "Expenses Recording" Google Sheet Bank Statement Processing Flow User uploads bank statement to "Bank Statements" folder Google Gemini extracts multiple transactions from statement Custom JavaScript parser handles various bank formats Individual transactions saved to "Bank Transactions Record" Google Sheet Financial Analysis Enable the analysis trigger when needed Ask questions in natural language about your financial data AI agent accesses all three spreadsheets to provide insights Get reports, summaries, and trend analysis What you need to set up Required APIs and Credentials Google Drive API** - For file storage and monitoring Google Sheets API** - For data storage and retrieval Google Gemini API** - For document processing and data extraction OpenRouter API** - For expense categorization (supports multiple LLM providers) Google Drive Folder Structure Create these folders in your Google Drive: "Invoices" - Processed invoice storage "Expense Receipts" - Drop zone for expense receipts (monitored) "Bank Statements" - Drop zone for bank statements (monitored) Google Sheets Setup Create three spreadsheets with these column headers: Invoice Records Sheet: Vendor Name, Invoice Number, Invoice Date, Due Date, Total Amount, VAT Amount, Line Item Description, Quantity, Unit Price, Total Price Expenses Recording Sheet: Merchant Name, Transaction Date, Total Amount, Tax Amount, Payment Method, Line Item Description, Quantity, Unit Price, Total Price, Category Bank Transactions Record Sheet: Transaction ID, Date, Description/Payee, Debit (-), Credit (+), Currency, Running Balance, Notes/Category Use Cases Small Business Accounting**: Automate invoice and expense tracking for bookkeeping Freelancer Financial Management**: Organize client invoices and business expenses Corporate Expense Management**: Streamline employee expense report processing Financial Data Analysis**: Generate insights from historical financial data Bank Reconciliation**: Automate transaction recording and account reconciliation Tax Preparation**: Maintain organized records with proper categorization Technical Highlights Expense Categories**: 17 predefined business expense categories (Cost of Goods Sold, Marketing, Payroll, etc.) Multi-format Support**: Handles various PDF layouts and bank statement formats Scalable Processing**: Processes multiple documents simultaneously Error Recovery**: Continues processing even when individual documents fail Natural Language Interface**: No technical knowledge required for financial queries Real-time Processing**: Documents processed within minutes of upload Benefits Time Savings**: Eliminates manual data entry from financial documents Accuracy**: AI-powered extraction reduces human error Organization**: Automatic file naming and categorization Insights**: Query financial data using natural language Compliance**: Maintains organized records for accounting and audit purposes Scalability**: Handles growing document volumes without additional overhead This workflow transforms tedious financial document processing into an automated, intelligent system that grows with your business needs.

Description AI-Powered Business Idea Generation & Social Media Content Strategy Workflow This intelligent content discovery and strategy system features 15 nodes that automatically monitor Reddit communities, analyze business opportunities, and generate targeted social media content for AI automation agencies and entrepreneurs. It leverages AI classification, structured analysis, and automated content creation to transform community discussions into actionable business insights and marketing materials. Core Components Reddit Intelligence: Multi-subreddit monitoring across AI automation, n8n, and entrepreneur communities with keyword-based filtering. AI Classification Engine: Intelligent categorization of posts into "Questions" vs "Requests" using LangChain text classification. Dual Analysis System: Specialized AI agents for educational content (questions) and sales-focused content (service requests). Content Strategy Generator: Automated creation of LinkedIn and Twitter content tailored to different audience engagement strategies. Telegram Integration: Real-time delivery of formatted content strategies and business insights. Structured Output Processing: JSON-formatted analysis with relevancy scores, feasibility assessments, and actionable content recommendations. Target Users • AI Automation Agency Owners seeking consistent lead generation and thought leadership content • Entrepreneurs wanting to identify market opportunities and position themselves as industry experts • Content Creators in the automation/AI space needing data-driven content strategies • Business Development Professionals looking for systematic opportunity identification • Digital Marketing Agencies serving tech and automation clients Setup Requirements To get started, you'll need: Reddit API Access: OAuth2 credentials for accessing Reddit's API and monitoring multiple subreddits. Required APIs: • OpenRouter (for AI model access - supports GPT-4, Claude, and other models) • Reddit OAuth2 API (for community monitoring and data extraction) n8n Prerequisites: • Version 1.7+ with LangChain nodes enabled • Webhook configuration for Telegram integration • Proper credential storage and management setup Telegram Bot: Create via @BotFather for receiving formatted content strategies and business insights. Disclaimer: This template uses LangChain nodes and Reddit API integration. Ensure your n8n instance supports these features and verify API rate limits for production use. Step-by-Step Setup Guide Install n8n: Ensure you're running n8n version 1.7 or higher with LangChain node support enabled. Set Up API Credentials: • Create Reddit OAuth2 application at reddit.com/prefs/apps • Set up OpenRouter account and obtain API key • Store credentials securely in n8n credential manager Create Telegram Bot: • Go to Telegram, search for @BotFather • Create new bot and note the token • Configure webhook pointing to your n8n instance Import the Workflow: • Copy the workflow JSON from the template submission • Import into your n8n dashboard • Verify all nodes are properly connected Configure Monitoring Settings: • Adjust subreddit targets (currently: ArtificialIntelligence, n8n, entrepreneur) • Set keyword filters for relevant topics • Configure post limits and sorting preferences Customize AI Analysis: • Update system prompts to match your business expertise • Adjust relevancy and feasibility scoring criteria • Modify content generation templates for your brand voice Test the Workflow: • Run manual execution to verify Reddit data collection • Check AI classification and analysis outputs • Confirm Telegram delivery of formatted content Schedule Automation: • Set up daily trigger (currently configured for 12 PM) • Monitor execution logs for any API rate limit issues • Adjust frequency based on content volume needs Usage Instructions Automated Discovery: The workflow runs daily at 12 PM, scanning three key subreddits for relevant posts about AI automation, business opportunities, and n8n workflows. Intelligent Classification: Posts are automatically categorized as either "Questions" (educational opportunities) or "Requests" (potential service leads) using AI text classification. Dual Analysis Approach: • Questions → Educational content strategy with relevancy and detail scoring • Requests → Sales-focused content with relevancy and feasibility scoring Content Strategy Generation: Each analyzed post generates: • 3 LinkedIn posts (thought leadership, case studies, educational frameworks) • 3 Twitter posts (quick insights, engagement questions, thread starters) Telegram Delivery: Receive formatted content strategies with: • Post summaries and business context • Relevancy/feasibility scores • Ready-to-use social media content • Strategic recommendations Content Customization: Adapt generated content for different tones (business, educational, technical) and posting schedules. Workflow Features Multi-Platform Monitoring: Simultaneous tracking of 3 key Reddit communities with customizable keyword filters. AI-Powered Classification: Automatic categorization of posts into actionable content types. Dual Scoring System: • Relevancy scores (0.05-0.95) for business alignment • Detail/Feasibility scores (0.05-0.95) for content quality assessment Content Variety: Generates both educational and sales-focused social media strategies. Structured Output: JSON-formatted analysis for easy integration with other systems. Real-time Delivery: Instant Telegram notifications with formatted content strategies. Scalable Monitoring: Easy addition of new subreddits and keyword filters. Error Handling: Comprehensive validation with graceful failure management. Performance Specifications • Monitoring Frequency: Daily automated execution with manual trigger capability • Post Analysis: 5 posts per subreddit (15 total daily) • Content Generation: 6 social media posts per analyzed opportunity • Classification Accuracy: AI-powered with structured output validation • Delivery Method: Real-time Telegram integration • Scoring Range: 0.05-0.95 scale for relevancy and feasibility assessment Why This Workflow? Systematic Opportunity Identification: Never miss potential business opportunities or content ideas from key communities. AI-Enhanced Analysis: Leverage advanced language models for intelligent content categorization and strategy generation. Time-Efficient Content Creation: Transform community discussions into ready-to-use social media content. Data-Driven Insights: Quantified scoring helps prioritize opportunities and content strategies. Automated Lead Intelligence: Identify potential service requests and educational content opportunities automatically. Workflow Image Need help customizing this workflow for your specific use case? As a fellow entrepreneur passionate about automation and business development, I'd be happy to consult. Connect with me on LinkedIn: https://www.linkedin.com/in/femi-adedayo-h44/ or email for support. Let's make your AI automation agency even more efficient!

This workflow is designed for creators, marketers, and agencies who want to automate content publishing while keeping quality control through human review. It integrates four powerful tools — Google Sheets, OpenAI, GoToHuman, and Blotato — to deliver a seamless AI-assisted, human-approved, auto-publishing system for LinkedIn. ⚙️ What This Workflow Does 📅 Pulls Today’s Topic from Google Sheets You store ideas in a spreadsheet with a date column. The workflow runs daily (or manually) and selects the row matching today’s date. 🧠 Generates a Caption with OpenAI The selected idea is passed to GPT-4 via an AI Agent node. OpenAI returns a short, emoji-rich LinkedIn caption (1–2 sentences). The result is saved back to the sheet. 👤 Sends the Caption for Human Review via GoToHuman A human reviewer sees the AI-generated caption. They approve or reject it using a GoToHuman review template. Only approved captions move forward. 🚀 Publishes the Approved Caption to LinkedIn via Blotato The caption is posted to a LinkedIn account via Blotato's API. No additional input is required — it's fully automated after approval. 🔧 Setup Requirements ✅ Google Sheets Create or copy the provided sample sheet. Connect your Google Sheets account in n8n using OAuth2. ✅ OpenAI Create an API key at platform.openai.com. Add it to n8n as an OpenAI credential. ✅ GoToHuman Create an account and a Review Template at gotohuman.com. Add your API credential in n8n and use your reviewTemplateId in the node. ✅ Blotato Create an account at blotato.com. Get your API key and Account ID. Insert them into the HTTP Request node that publishes the LinkedIn post. 🧪 Testing the Workflow Use the Manual Trigger node for step-by-step debugging. Review nodes like AI Agent, Ask Human for Approval, and Post to LinkedIn to verify output. Once confirmed, activate the schedule for fully hands-free publishing. 👋 Built By Robert Breen Founder of Ynteractive — Automation, AI, and Data Strategy 🌐 Website: https://ynteractive.com 📧 Email: robert@ynteractive.com 🔗 LinkedIn: https://www.linkedin.com/in/robert-breen-29429625/ 📺 YouTube: YnteractiveTraining 🏷 Tags linkedin openai gotohuman social automation ai content approval workflow google sheets blotato marketing automation