Workflow Templates

Video Guide I prepared a detailed guide that shows the whole process of building an AI tool to analyze Instagram Reels using n8n. Youtube Link Who is this for? This workflow is ideal for social media analysts, digital marketers, and content creators who want to leverage data-driven insights from their Instagram Reels. It's particularly useful for those looking to automate the analysis of video performance to inform strategy and content creation. What problem does this workflow solve? Analyzing video performance on Instagram can be tedious and time-consuming, requiring multiple steps and data extraction. This workflow automates the process of fetching, analyzing, and recording insights from Instagram Reels, making it simpler for users to track engagement metrics without manual intervention. What this workflow does This workflow integrates several services to analyze Instagram Reels, allowing users to: Automatically fetch recent Reels from specified creators. Analyze the most-watched videos for insights. Store and manage data in Airtable for easy access and reporting. Initial Trigger: The process begins with a manual trigger that can later be modified for scheduled automation. Data Retrieval: It connects to Airtable to fetch a list of creators and their respective Instagram Reels. Video Analysis: It handles the fetching, downloading, and uploading of videos for analysis using an external service, simplifying performance tracking through a structured query process. Record Management: It saves relevant metrics and insights into Airtable, ensuring that users can access and organize their video analytics effectively. Setup Create accounts: Set up Airtable, Edify, n8n, and Gemini accounts. Prepare triggers and modules: Replace credentials in each node accordingly. Configure data flow: Ensure modules are set to fetch and analyze the correct data fields as outlined in the guide. Test the workflow: Run the scenario manually to confirm that data is fetched and analyzed correctly.

Boost Sales with Automated Magento 2 Product and Coupon Notifications This n8n workflow automatically posts new Magento products & coupons to Telegram while preventing duplicates. Key benefits: ✅ Increase conversions with time-sensitive alerts (creates urgency) ✅ Reduce missed opportunities with 24/7 monitoring ✅ Improve customer engagement through rich media posts ✅ Save hours per week by automating manual posting Why This Works: Triggers impulse buys with real-time notifications Eliminates human error in duplicate posting Scales effortlessly as your catalog grows Provides analytics through database tracking Perfect for e-commerce stores wanting to: Announce new arrivals instantly Promote limited-time offers effectively Maintain consistent social presence Track performance through MySQL This workflow automatically: ✅ Detects new products AND coupons in Magento ✅ Prevents duplicate postings with MySQL tracking ✅ Posts rich formatted alerts to Telegram ✅ Runs on a customizable schedule ✨ Key Features For Products: Product name, price, and image Direct store link Media gallery support For Coupons: Coupon code and status Usage limits (times used/available) Active/inactive status indicator Core System: 🔒 MySQL duplicate prevention⏰ 1-hour schedule (customizable)📱 Telegram notifications with Markdown 🛠️ Configuration Guide Database Setup CREATE TABLE IF NOT EXISTS posted_items (item_id INT PRIMARY KEY, item_type ENUM('product', 'coupon') NOT NULL, item_value VARCHAR(255), posted BOOLEAN DEFAULT FALSE, created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP, updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP); Required Credentials Magento API (HTTP Header Auth) MySQL Database Telegram Bot Sticky Notes `❗ IMPORTANT SETUP NOTES ❗ For products: Ensure 'url_key' exists in custom_attributes For coupons: Magento REST API must expose coupon rules MySQL user needs INSERT/SELECT privileges Telegram bot must be added to your channel first 🔄 SCHEDULING: - Default: Checks every 1 hours at :00 - Adjust in Schedule Trigger node ` ⚙️ Technical Details Workflow Logic: Checks for new products/coupons via Magento API Verifies against MySQL database Only posts if record doesn't exist Updates database after successful post Error Handling: Automatic skip if product/coupon exists Empty result handling Connection timeout protection 🌟 Why This Template? Complete Solution**: Handles both products AND coupons Battle-Tested**: Prevents all duplicates reliably Ready-to-Use**: Just add your credentials Fully Customizable**: Easy to modify for different needs Perfect for e-commerce stores using Magento 2 who want automated, duplicate-free social notifications!

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. 📦 Multi-Platform Price Finder: Scraping Prices with Bright Data & Telegram An intelligent n8n automation that fetches real-time product prices from marketplaces like Amazon, Wayfair, Lowe's, and more using Bright Data's dataset, and sends promotional messages via Telegram using AI—perfect for price tracking, deal alerts, and affiliate monetization. 📋 Overview This automation tracks product prices across top e-commerce platforms using Bright Data and sends out alerts via Telegram based on the best available deals. The workflow is designed for affiliate marketers, resellers, and deal-hunting platforms who want real-time competitive pricing. ✨ Key Features 🔎 Multi-Platform Scraping: Supports Amazon, Wayfair, Lowe's, and more ⚡ Bright Data Integration: Access to structured product snapshots 📢 AI-Powered Alerts: Generates Telegram-ready promo messages using AI 🧠 Lowest Price Logic: Filters and compares products across sources 📈 Data Merge & Processing: Combines multiple sources into a single stream 🔄 Keyword-Driven Search: Searches using dynamic keywords from form input 📦 Scalable Design: Built for multiple platform processing simultaneously 🧼 Clean Output: Strips unnecessary formatting before publishing 🎯 What This Workflow Does Input Search Keywords**: User-defined keyword(s) from a form trigger Platform Sources**: Wayfair, Lowe's, Amazon, etc. Bright Data API Key**: Needed for authenticated scraping Processing Steps User Input via n8n form trigger (keyword-based) Bright Data API Trigger for each marketplace Status Polling: Wait until scraping snapshot is ready Data Retrieval: Fetches JSON results from Bright Data snapshot Data Cleaning & Normalization: Price, title, and URL are extracted Merging Products from all platforms Find Lowest Price Product using custom JS logic AI Prompt Generation via Claude/Anthropic Telegram Formatting and alert message creation Output 🛍️ Product Title 💰 Final Price 🔗 Product URL ✉️ Promotional Message (for Telegram/notifications) 🚀 Setup Instructions Step 1: Import Workflow Open n8n > Workflows > + Add Workflow Import the provided JSON file Step 2: Configure Bright Data Add credentials under Credentials → Bright Data API Set the appropriate dataset_id for each platform Ensure dataset includes title, price, and url fields Step 3: Enable Keyword Trigger Use the built-in Form Trigger node Input: Single keyword field (SearchHere) Step 4: Telegram or AI Integration Modify prompt node for your language or tone Add Telegram webhook or integration where needed 📖 Usage Guide Adding Keywords Trigger the form with a product keyword like iPhone 15 Wait for workflow to fetch best deals and generate Telegram message Understanding AI-Powered Output AI creates a short, engaging message like: > "🔥 Deal Alert: Get the iPhone 15 for just ₹74,999! Limited stock—Check it out: [link]" Debugging Output Output node shows cleaned JSON with title, price, url, and message If no valid results, debug message is returned with sample structure info 🔧 Customization Options Add More Marketplaces Clone any HTTP Request node (e.g., for Wayfair) Update dataset_id and required output fields Modify Price Logic Update the Code1 node to change comparison (e.g., highest price instead of lowest) Change Message Format Edit the AI Agent prompt to customize tone/language Add emoji, CTAs, or markdown formatting as needed 🧪 Test & Activation Add a few sample keywords via form trigger Run manually or set as a webhook for external app input Check final AI-generated message in output node 🚨 Troubleshooting | Issue | Solution | |-------|----------| | No Data Returned | Ensure keyword matches real products | | Status Not 'Ready' | Bright Data delay; add Wait nodes | | Invalid API Key | Check Bright Data credentials | | AI Errors | Adjust prompt or validate input fields | 📊 Use Cases 💰 Affiliate Campaigns: Show best deals across platforms 🛒 Deal Pages: Post live offers with product links 🧠 Competitor Analysis: Track cross-platform pricing 🔔 Alert Bots: Send real-time alerts to Telegram or Slack ✅ Quick Setup Checklist [x] Bright Data API credentials configured [x] n8n form trigger enabled [x] Claude or AI model connected [x] All HTTP requests working [x] AI message formatting verified 🌐 Example Output { "title": "Apple iPhone 15 Pro Max", "price": 1199, "url": "https://amazon.com/iphone-15", "message": "🔥 Grab the Apple iPhone 15 Pro Max for just $1199! Limited deal—Check it out: https://amazon.com/iphone-15" } 📬For any questions or support, please contact: 📧 <info@incrementors.com> or fill out this form: https://www.incrementors.com/contact-us/

Source Discovery - Automatically Search More Up-to-Date Information Sources 🎬 Overview Version : 1.0 This workflow utilizes various nodes to discover and analyze potential sources of information from platforms like Google, Reddit, GitHub, Bluesky, and others. It is designed to streamline the process of finding relevant sources based on specified search themes. ✨ Features Automated source discovery from multiple platforms. Filtering of existing and undesired sources. Error handling for API requests. User-friendly configuration options. 👤 Who is this for? This workflow is ideal for researchers, content marketers, journalists, and anyone looking to efficiently gather and analyze information from various online sources. 💡 What problem does this solve? This workflow addresses the challenge of manually searching for relevant information sources, saving time and effort while ensuring that users have access to the most pertinent content. Ideal use-cases include: Resource Compilation for Academic and Educational Purposes Journalism and Research Content Marketing Competitor Analysis 🔍 What this workflow does The workflow gathers data from selected platforms through search terms. It filters out known and undesired sources, analyzes the content, and provides insights into potential sources relevant to the user's needs. 🔄 Workflow Steps 1. Search Queries Fetch sources using SerpAPI search, DuckDuckGo, and Bluesky. Utilizes GitHub repositories to find relevant links. Leverages RSS feeds from subreddits to identify potential sources. 2. Filtering Step Removes existing and undesired sources from the results. 3. Source Selection Analyzes the content of the identified sources for relevance. 📌 Expected Input / Configuration The workflow is primarily configured via the Configure Workflow Args (Manual) node or the Global Variables custom node. Search themes: Keywords or phrases relevant to the desired content. Lists of known sources and undesired sources for filtering. 📦 Expected Output A curated list of potential sources relevant to the specified search themes, along with insights into their content. 📌 Example ⚙️ n8n Setup Used n8n version:** 1.105.3 n8n-nodes-serpapi:** 0.1.6 n8n-nodes-globals:** 1.1.0 n8n-nodes-bluesky-enhanced**: 1.6.0 n8n-nodes-duckduckgo-search**: 30.0.4 LLM Model:** mistral-small-latest (API) Platform:** Podman 4.3.1 on Linux Date:** 2025-08-06 ⚡ Requirements to Use / Setup Self-hosted or cloud n8n instance. Install the following custom nodes: SerpAPI, Bluesky, and DuckDuckGo Search. n8n-nodes-serpapi n8n-nodes-duckduckgo-search n8n-nodes-bluesky-enhanced Install the Global Variables Node for enhanced configuration: n8n-nodes-globals (or use Edit Field (Set) node instead) Provide valid credentials to nodes for your preferred LLM model, SerpAPI, and Bluesky. Credentials for GitHub recommended. ⚠️ Notes, Assumptions \& Warnings Ensure compliance with the terms of service of any platforms accessed or discovered in this workflow, particularly concerning data usage and attribution. Monitor API usage to avoid hitting rate limits. The workflow may encounter errors such as 403 responses; in such cases, it will continue by ignoring the affected substep. Duplicate removal is applied, but occasional overlaps might still appear depending on the sources. This workflow assumes familiarity with n8n, APIs, and search engines. Using AI agents (Mistral or substitute LLMs) requires access to their API services and keys. This is not a Curator of News. It is designed to find websites that are relevant and useful to your searches. If you are looking for a relevant news selector, please check this workflow. ℹ️ About Us This workflow was developed by the Hybroht team. Our goal is to create tools that harness the possibilities of technology and more. We aim to continuously improve and expand functionalities based on community feedback and evolving use cases. For questions, reach out via contact@hybroht.com. ⚖️ Warranty & Legal Notice This free workflow is provided "as-is" without any warranties of any kind, either express or implied, including but not limited to the implied warranties of merchantability, fitness for a particular purpose, or non-infringement. By using this workflow, you acknowledge that you do so at your own risk. We shall not be held responsible for any damages, losses, or liabilities arising from the use or inability to use this workflow, including but not limited to any direct, indirect, incidental, or consequential damages. It is your responsibility to ensure that your use of this workflow complies with all applicable laws and regulations.

N8N Automated Twitter Reply Bot Workflow For latest version, check: dziura.online/automation Latest documentation can be find here You must have Apify community node installed before pasting the JSON to your workflow.  Overview This n8n workflow creates an intelligent Twitter/X reply bot that automatically scrapes tweets based on keywords or communities, analyzes them using AI, generates contextually appropriate replies, and posts them while avoiding duplicates. The bot operates on a schedule with intelligent timing and retry mechanisms. Key Features Automated tweet scraping** from Twitter/X using Apify actors AI-powered reply generation** using LLM (Large Language Model) Duplicate prevention** via MongoDB storage Smart scheduling** with timezone awareness and natural posting patterns Retry mechanism** with failure tracking Telegram notifications** for status updates Manual trigger** option via Telegram command Required Credentials & Setup 1\. Telegram Bot Create a bot via @BotFather on Telegram Get your Telegram chat ID to receive status messages Credential needed**: Telegram account (Bot token) 2\. MongoDB Database Set up a MongoDB database to store replied tweets and prevent duplicates Create a collection (default name: collection\_name) Credential needed**: MongoDB account (Connection string) Tutorial**: MongoDB Connection Guide 3\. Apify Account Sign up at Apify.com Primary actors used**: Search Actor: api-ninja/x-twitter-advanced-search - For keyword-based tweet scraping (ID: 0oVSlMlAX47R2EyoP) Community Actor: api-ninja/x-twitter-community-search-post-scraper - For community-based tweet scraping (ID: upbwCMnBATzmzcaNu) Credential needed**: Apify account (API token) 4\. OpenRouter (LLM Provider) Sign up at OpenRouter.ai Used for AI-powered tweet analysis and reply generation Model used**: x-ai/grok-3 (configurable) Credential needed**: OpenRouter account (API key) 5\. Twitter/X API Set up developer account at developer.x.com Note**: Free tier limited to ~17 posts per day Credential needed**: X account (OAuth2 credentials) Workflow Components Trigger Nodes 1\. Schedule Trigger Purpose**: Runs automatically every 20 minutes Smart timing**: Only active between 7 AM - 11:59 PM (configurable timezone) Randomization**: Built-in probability control (~28% execution chance) to mimic natural posting patterns 2\. Manual Trigger Purpose**: Manual execution for testing 3\. Telegram Trigger Purpose**: Manual execution via /reply command in Telegram Usage**: Send /reply to your bot to trigger the workflow manually Data Processing Flow 1\. MongoDB Query (Find documents) Purpose**: Retrieves previously replied tweet IDs to avoid duplicates Collection**: collection\_name (configure to match your setup) Projection**: Only fetches tweet\_id field for efficiency 2\. Data Aggregation (Aggregate1) Purpose**: Consolidates tweet IDs into a single array for filtering 3\. Keyword/Community Selection (Keyword/Community List) Purpose**: Defines search terms and communities Configuration**: Edit the JSON to include your keywords and Twitter community IDs Format:{   "keyword\_community\_list": \[     "SaaS",     "Entrepreneur",      "1488663855127535616"  // Community ID (19-digit number)   \],   "failure": 0 } 4\. Random Selection (Randomized community, keyword) Purpose**: Randomly selects one item from the list to ensure variety 5\. Routing Logic (If4) Purpose**: Determines whether to use Community search or Keyword search Logic**: Uses regex to detect 19-digit community IDs vs keywords Tweet Scraping (Apify Actors) Community Search Actor Actor**: api-ninja/x-twitter-community-search-post-scraper Purpose**: Scrapes tweets from specific Twitter communities Configuration:{   "communityIds": \["COMMUNITY\_ID"\],   "numberOfTweets": 40 } Search Actor Actor**: api-ninja/x-twitter-advanced-search Purpose**: Scrapes tweets based on keywords Configuration:{   "contentLanguage": "en",   "engagementMinLikes": 10,   "engagementMinReplies": 5,   "numberOfTweets": 20,   "query": "KEYWORD",   "timeWithinTime": "2d",   "tweetTypes": \["original"\],   "usersBlueVerifiedOnly": true } Filtering System (Community filter) The workflow applies multiple filters to ensure high-quality replies: Text length**: >60 characters (substantial content) Follower count**: >100 followers (audience reach) Engagement**: >10 likes, >3 replies (proven engagement) Language**: English only Views**: >100 views (visibility) Duplicate check**: Not previously replied to Recency**: Within 2 days (configurable in actor settings) AI-Powered Reply Generation LLM Chain (Basic LLM Chain) Purpose**: Analyzes filtered tweets and generates contextually appropriate replies Model**: Grok-3 via OpenRouter (configurable) Features**: Engagement potential scoring User authority analysis Timing optimization Multiple reply styles (witty, informative, supportive, etc.) <100 character limit for optimal engagement Output Parser (Structured Output Parser) Purpose**: Ensures consistent JSON output format Schema:{   "selected\_tweet\_id": "tweet\_id\_here",   "screen\_name": "author\_screen\_name",    "reply": "generated\_reply\_here" } Posting & Notification System Twitter Posting (Create Tweet) Purpose**: Posts the generated reply as a Twitter response Error handling**: Catches API limitations and rate limits Status Notifications Success**: Notifies via Telegram with tweet link and reply text Failure**: Notifies about API limitations or errors Format**: HTML-formatted messages with clickable links Database Storage (Insert documents) Purpose**: Saves successful replies to prevent future duplicates Fields stored**: tweet\_id, screen\_name, reply, tweet\_url, timestamp Retry Mechanism The workflow includes intelligent retry logic: Failure Counter (If5, Increment Failure Counter1) Logic**: If no suitable tweets found, increment failure counter Retry limit**: Maximum 3 retries with different random keywords Wait time**: 3-second delay between retries Final Failure Notification Trigger**: After 4 failed attempts Action**: Sends Telegram notification about unsuccessful search Recovery**: Manual retry available via /reply command Configuration Guide Essential Settings to Modify MongoDB Collection Name: Update collection\_name in MongoDB nodes Telegram Chat ID: Replace 11111111111 with your actual chat ID Keywords/Communities: Edit the list in Keyword/Community List node Timezone: Update timezone in Code node (currently set to Europe/Kyiv) Actor Selection: Enable only one actor (Community OR Search) based on your needs Filter Customization Adjust filters in Community filter node based on your requirements: Minimum engagement thresholds Text length requirements Time windows Language preferences LLM Customization Modify the AI prompt in Basic LLM Chain to: Change reply style and tone Adjust engagement criteria Modify scoring algorithms Set different character limits Usage Tips Start small: Begin with a few high-quality keywords/communities Monitor performance: Use Telegram notifications to track success rates Adjust filters: Fine-tune based on the quality of generated replies Respect limits: Twitter's free tier allows ~17 posts/day Test manually: Use /reply command for testing before scheduling Troubleshooting Common Issues No tweets found: Adjust filter criteria or check keywords API rate limits: Reduce posting frequency or upgrade Twitter API plan MongoDB connection: Verify connection string and collection name Apify quota: Monitor Apify usage limits LLM failures: Check OpenRouter credits and model availability Best Practices Monitor your bot's replies for quality and appropriateness Regularly update keywords to stay relevant Keep an eye on engagement metrics Adjust timing based on your audience's activity patterns Maintain a balanced posting frequency to avoid appearing spammy Documentation Links Full Documentation**: Google Doc Guide Latest Version**: dziura.online/automation MongoDB Setup Tutorial**: YouTube Guide This workflow provides a comprehensive solution for automated, intelligent Twitter engagement while maintaining quality and avoiding spam-like behavior.

Zoho CRM → AI Sentiment Analysis for customer interactions & Automatic Alerts Workflow This workflow analyzes newly created Notes (in Any module) in Zoho CRM, detects customer sentiment using an AI model, updates the related CRM record with custom fields - sentiment label and score, and sends an instant alert whenever negative sentiment is detected. It runs on a scheduled interval and gives teams real-time visibility into customer emotions and potential risks. Quick Implementation Steps Connect Zoho CRM OAuth2 credentials Add custom fields in Zoho CRM: Sentiment_Label and Sentiment_Score Add AI provider credentials Set Gmail alert recipient Activate workflow and test by adding a Note What It Does This workflow automatically monitors Zoho CRM Notes. When a new Note is detected, the text is extracted and analyzed through an AI-powered sentiment model. The AI classifies the text as Positive, Neutral or Negative and produces a numeric sentiment score. The workflow updates the related CRM module with these values. If the sentiment is negative, a Gmail alert is triggered so your team can follow up quickly. This automation helps organizations maintain high customer satisfaction and detect potential issues early. Who’s It For Support teams Sales teams CRM administrators Customer success managers Businesses needing automated customer sentiment tracking Requirements n8n instance Zoho CRM OAuth2 credentials Gmail OAuth2 credentials AI provider key Custom fields in Zoho CRM: Sentiment_Label & Sentiment_Score (if you are using different field name then do changes in workflow accoredingly) How It Works & Setup Step 1: Schedule Trigger Runs periodically to check for new or updated Notes. Step 2: Fetch Latest Note Retrieves the most recently modified Note. Step 3: Extract Details Extracts Note text, note_id, parent_id and module name. Step 4: AI Sentiment Analysis Sends text to the AI (via LangChain chain) for sentiment classification. Step 5: Conditional Branching If Negative: Send Gmail alert and update CRM Otherwise: Just update CRM Step 6: Update CRM Writes sentiment data back into the related parent record. How to Customize Nodes Adjust sentiment output by modifying the AI prompt. Change field mappings in Zoho update nodes. Customize the Gmail alert message. Adjust Schedule Trigger frequency. Add additional metadata (e.g., emotion tags). Add‑Ons Slack/Teams alerts for negative sentiment. Historical sentiment logging. Weekly sentiment reports. Auto-task creation for negative interactions. Priority-based escalation logic. Use Case Examples Detect unhappy customers in support interactions. Monitor sentiment across sales conversations. Escalate negative feedback automatically. Quality assurance tracking for customer interactions. Early detection of churn indicators. Troubleshooting Guide | Issue | Possible Cause | Solution | |------|----------------|----------| | Sentiment not updating | Missing Zoho fields | Add custom fields in CRM | | Note not detected | Fetching only latest note | Increase frequency or widen fetch scope | | AI output invalid | Prompt mismatch | Update prompt and parser | | Alerts not sending | Gmail OAuth expired | Reconnect Gmail | | Incorrect sentiment | Weak prompt instructions | Refine prompt wording | Need Help? WeblineIndia can help you configure, customize and extend workflows like this. We specialize in: n8n automation CRM integrations AI/LLM-powered workflows Zoho CRM customization Reach out if you'd like assistance building or enhancing similar n8n automation solutions.

Automatically detect, classify, and document GitHub API errors using AI. This workflow connects GitHub, OpenAI (GPT-4o), Airtable, Notion, and Slack to build a real-time, searchable API error knowledge base — helping engineering and support teams respond faster, stay aligned, and maintain clean documentation. ⚙️📘💬 🚀 What This Template Does 1️⃣ Triggers on new or updated GitHub issues (API-related). 🪝 2️⃣ Extracts key fields (title, body, repo, and link). 📄 3️⃣ Classifies issues using OpenAI GPT-4o, identifying error type, category, root cause, and severity. 🤖 4️⃣ Validates & parses AI output into structured JSON format. ✅ 5️⃣ Creates or updates organized FAQ-style entries in Airtable for quick lookup. 🗂️ 6️⃣ Logs detailed entries into Notion, maintaining an ongoing issue knowledge base. 📘 7️⃣ Notifies the right Slack team channel (DevOps, Backend, API, Support) with concise summaries. 💬 8️⃣ Tracks & prevents duplicates, keeping your error catalog clean and auditable. 🔄 💡 Key Benefits ✅ Converts unstructured GitHub issues into AI-analyzed documentation ✅ Centralizes API error intelligence across teams ✅ Reduces time-to-resolution for recurring issues ✅ Maintains synchronized records in Airtable & Notion ✅ Keeps DevOps and Support instantly informed through Slack alerts ✅ Fully automated, scalable, and low-cost using GPT-4o ⚙️ Features Real-time GitHub trigger for API or backend issues GPT-4o-based AI classification (error type, cause, severity, confidence) Smart duplicate prevention logic Bi-directional sync to Airtable + Notion Slack alerts with contextual AI insights Modular design — easy to extend with Jira, Teams, or email integrations 🧰 Requirements GitHub OAuth2 credentials OpenAI API key (GPT-4o recommended) Airtable Base & Table IDs (with fields like Error Code, Category, Severity, Root Cause) Notion integration with database access Slack Bot token with chat:write scope 👥 Target Audience Engineering & DevOps teams managing APIs Customer support & SRE teams maintaining FAQs Product managers tracking recurring API issues SaaS orgs automating documentation & error visibility 🪜 Step-by-Step Setup Instructions 1️⃣ Connect your GitHub account and enable the “issues” webhook event. 2️⃣ Add OpenAI credentials (GPT-4o model for classification). 3️⃣ Create an Airtable base with fields: Error Code, Category, Root Cause, Severity, Confidence. 4️⃣ Configure your Notion database with matching schema and access. 5️⃣ Set up Slack credentials and choose your alert channels. 6️⃣ Test with a sample GitHub issue to validate AI classification. 7️⃣ Enable the workflow — enjoy continuous AI-powered issue documentation!

📊 Description Ensure your GitHub repositories stay configuration-accurate and documentation-compliant with this intelligent AI-powered validation workflow. 🤖 This automation monitors repository updates, compares configuration files against documentation references, detects inconsistencies, and alerts your team instantly—streamlining DevOps and compliance reviews. ⚡ What This Template Does Step 1: Triggers automatically on GitHub push or pull_request events. 🔄 Step 2: Fetches both configuration files (config/app-config.json and faq-config.json) from the repository. 📂 Step 3: Uses GPT-4o-mini to compare configurations and detect mismatches, missing keys, or deprecated fields. 🧠 Step 4: Categorizes issues by severity—critical, high, medium, or low—and generates actionable recommendations. 🚨 Step 5: Logs all discrepancies to Google Sheets for tracking and audit purposes. 📑 Step 6: Sends Slack alerts summarizing key issues and linking to the full report. 💬 Key Benefits ✅ Prevents production incidents due to config drift ✅ Ensures documentation stays in sync with code changes ✅ Reduces manual review effort with AI-driven validation ✅ Improves team response with Slack-based alerts ✅ Maintains audit logs for compliance and traceability Features Real-time GitHub webhook integration AI-powered config comparison using GPT-4o-mini Severity-based issue classification Automated Google Sheets logging Slack alerts with detailed issue context Error handling for malformed JSON or parsing issues Requirements GitHub OAuth2 credentials with repo and webhook permissions OpenAI API key (GPT-4o-mini or compatible model) Google Sheets OAuth2 credentials Slack API token with chat:write permissions Target Audience DevOps teams ensuring consistent configuration across environments Engineering leads maintaining documentation accuracy QA and Compliance teams tracking configuration changes and risks Setup Instructions Create GitHub OAuth2 credentials and enable webhook access. Connect your OpenAI API key under credentials. Add your Google Sheets and Slack integrations. Update file paths (config/app-config.json and faq-config.json) if your repo uses different names. Activate the workflow — it will start validating on every push or PR. 🚀

Automatically fetches daily sales, shifts, and receipts from Loyverse. Calculates gross profit, net operating profit, other key metrics, saves them to a Google Sheet and sends out a daily report via email. Who’s it for This template is for any business owner, manager, or analyst using Loyverse POS who needs more advanced financial reporting. If you're a restaurant, bar, or retail owner who wants to automatically track daily net profit, compare sales to historical averages, and build a custom financial dashboard in Google Sheets, this workflow is for you. How it works / What it does This workflow runs automatically on a daily schedule. It fetches all sales data and receipts from your Loyverse account for the previous business day, defined by your custom shift times (even past midnight). A powerful Code node then processes all the data to calculate the metrics that Loyverse either doesn't provide at all, or only spreads out across several separate reports instead of in one consolidated place. Already set up are metrics like... -Total Revenue, Gross Profit, and Net Operating Profit Cash handling differences (over/under) Average spend per receipt (ATV) 30-day rolling Net Operating Profit (NOP) Performance vs. your historical weekday average Finally, it appends the single, calculated row of daily metrics to a Google Sheet and sends an easily customizable summary report to your email. How to set up This workflow includes detailed Sticky Notes to guide you through the setup process. Because every business has a unique POS configuration (different POS devices, categories, and payment types), you'll need to set up a few things manually before executing the workflow. I've tried to make this as easy as possible to follow, and the entire setup should only take about 15 minutes. Preparations & Credential setup Subscribe to "Integrations" Add-on in Loyverse ($9 / month) to gain API access. Create an Access token in Loyverse Create Credentials: In your n8n instance, create credentials for Loyverse (use "Generic" > "Bearer Auth"), Google Sheets (OAuth2), and your Email (SMTP or other). Make a copy of a prep-configured Google Spreadsheet (Link in the second sticky note inside the workflow). Fill MASTER CONFIG: Open the MASTER CONFIG node. Follow the comments inside to add your Google Sheet ID, Sheet Names, business hours, timezone, and Loyverse IDs (for POS devices, payment types, and categories). Configure Google Sheet Nodes Configure Read Historical Data: Open this node. Follow the instructions in the nearby Sticky Note to paste the expressions for your Document ID and Sheet Name. Configure Save Product List: Open this node. Paste in the expressions for Document ID and Sheet Name. The column mapper will load; map your sheet columns (e.g., item_name) to the data on the left (e.g., {{ $json.item_name }}). Configure Save Latest Sales Data: Open this node. Paste in the expressions for Document ID and Sheet Name. Save and run the workflow. After that, the column mapper will load. This is the most important step: map your sheet's column names (e.g., "Total Revenue") to the calculated metrics from the Calculate All Metrics node (e.g., {{ $json.totalGrossRevenue }}). Activate the workflow. 🫡 Requirements Loyverse Integrations Subscription Loyverse Access Token Credentials for Loyverse (Bearer Auth) Credentials for Google Sheets (OAuth2) Credentials for Email/SMTP sender How to customize the workflow This template is designed to be highly flexible. Central Configuration: Almost all customization (POS devices, categories, payment types, sheet names) is done in the MASTER CONFIG node. You don't need to dig through other nodes. Add/Remove Metrics: The Calculate All Metrics node has additional metrics already set up, just add the relevant collumns to the SalesData sheet or even add your own calculations to the node. Any new metric you add (e.g., metrics.myNewMetric = 123) will be available to map in the Save Latest Sales Data node. Email Body: You can easily edit the Send email node to change the text or add new metrics from the Calculate All Metrics node.

Automatically turns trending Reddit posts into punchy, first-person tweets powered by Google Gemini AI, Reddit, and Twitter API, with Google Sheets logging. 🧩 Overview This workflow repurposes Reddit content into original tweets every few hours. It’s perfect for creators, marketers, or founders who want to automate content inspiration while keeping tweets sounding human, edgy, and fresh. Core automation loop: Fetch trending Reddit posts from selected subreddits. Use Gemini AI to write a short, first-person tweet. Check your Google Sheet to avoid reusing the same Reddit post. Publish to Twitter automatically. Log tweet + Reddit reference in Google Sheets. 🧠 Workflow Diagram 🪄 How It Works 1️⃣ Every 2 hours → the workflow triggers automatically. 2️⃣ It picks a subreddit (like r/automation, r/n8n, r/SaaS). 3️⃣ Gemini AI analyzes a rising Reddit post and writes a fresh, short tweet. 4️⃣ The system checks your Google Sheet to ensure it hasn’t used that Reddit post before. 5️⃣ Once validated, the tweet is published via Twitter API and logged. 🧠 Example Tweet Output 📊 Logged Data (Google Sheets) Each tweet is automatically logged for version control and duplication checks. | Date | Subreddit | Post ID | Tweet Text | |------|------------|----------|-------------| | 08/10/2025 | n8n_ai_agents | 1o16ome | Just saw a wild n8n workflow on Reddit... | ⚙️ Key Components | Node | Function | |------|-----------| | Schedule Trigger | Runs every 2 hours to generate a new tweet. | | Code (Randomly Decide Subreddit) | Picks one subreddit randomly from your preset list. | | Gemini Chat Model | Generates tweet text in first person tone using custom prompt rules. | | Reddit Tool | Fetches top or rising posts from the chosen subreddit. | | Google Sheets (read database) | Keeps a record of already-used Reddit posts. | | Structured Output Parser | Ensures consistent tweet formatting (tweet text, subreddit, post ID). | | Twitter Node | Publishes the AI-generated tweet. | | Append Row in Sheet | Logs the tweet with date, subreddit, and post ID. | 🧩 Setup Tutorial 1️⃣ Prerequisites | Tool | Purpose | |------|----------| | n8n Cloud or Self-Host | Workflow execution | | Google Gemini API Key | For tweet generation | | Reddit OAuth2 API | To fetch posts | | Twitter (X) API OAuth2 | To publish tweets | | Google Sheets API | For logging and duplication tracking | 2️⃣ Import the Workflow Download Reddit Twitter Automation.json. In n8n, click Import Workflow → From File. Connect your credentials: Gemini → Gemini Reddit → Reddit account Twitter → X Google Sheets → Gsheet 3️⃣ Configure Google Sheet Your sheet must include these columns: | Column | Description | |--------|--------------| | PAST TWEETS | The tweet text | | Date | Auto-generated date | | subreddit | Reddit source | | post_id | Reddit post reference | 4️⃣ Customize Subreddits In the Code Node, update this array to choose which subreddits to monitor: const subreddits = [ "n8n", "microsaas", "SaaS", "automation", "n8n_ai_agents" ];

🛒 Smart Telegram Shopping Assistant with AI Product Recommendations Workflow Overview Target User Role: E-commerce Business Owners, Affiliate Marketers, Customer Support Teams Problem Solved: Businesses need an automated way to help customers find products on Telegram without manual intervention, while providing intelligent recommendations that increase conversion rates. Opportunity Created: Transform any Telegram channel into a smart shopping assistant that can handle both product queries and customer conversations automatically. What This Workflow Does This workflow creates an intelligent Telegram bot that: 🤖 Automatically detects** whether users are asking about products or just chatting 🛒 Scrapes Amazon** in real-time to find the best matching products 🎯 Uses AI to analyze and rank** products based on price, ratings, and user needs 📱 Delivers perfectly formatted** recommendations optimized for Telegram 💬 Handles casual conversations** professionally when users aren't shopping Real-World Use Cases E-commerce Support**: Reduce customer service workload by 70% Affiliate Marketing**: Automatically recommend products with tracking links Telegram Communities**: Add shopping capabilities to existing channels Product Discovery**: Help customers find products they didn't know existed Key Features & Benefits 🧠 Intelligent Intent Detection Uses Google Gemini AI to understand user messages Automatically routes to product search or conversation mode Handles multiple languages and casual typing styles 🛒 Real-Time Product Data Integrates with Apify's Amazon scraper for live data Fetches prices, ratings, reviews, and product details Processes up to 10 products per search instantly 🎯 AI-Powered Recommendations Analyzes multiple products simultaneously Ranks by relevance, value, and user satisfaction Provides top 5 personalized recommendations with reasoning 📱 Telegram-Optimized Output Perfect formatting with emojis and markdown Respects character limits for mobile viewing Includes direct purchase links for easy buying Setup Requirements Required Credentials Telegram Bot Token - Free from @BotFather Google Gemini API Key - Free tier available at AI Studio Apify API Token - Free tier includes 100 requests/month Required n8n Nodes @n8n/n8n-nodes-langchain (for AI functionality) Built-in Telegram, HTTP Request, and Code nodes Quick Setup Guide Step 1: Telegram Bot Creation Message @BotFather on Telegram Create new bot with /newbot command Copy the bot token to your credentials Step 2: AI Configuration Sign up for Google AI Studio Generate API key for Gemini Add credentials to all three AI model nodes Step 3: Product Scraping Setup Register for free Apify account Get API token from dashboard Add token to "Amazon Product Scraper" node Step 4: Activation Import workflow JSON Add your credentials Activate the Telegram Trigger Test with a product query! Workflow Architecture 📱 Message Entry Point Telegram Trigger receives all messages 🧹 Query Preprocessing Cleans and normalizes user input for better search results 🤖 AI Intent Classification Determines if message is product-related or conversational 🔀 Smart Routing Directs to appropriate workflow path based on intent 💬 Conversation Path Handles greetings, questions, and general support 🛒 Product Search Path Scrapes Amazon → Processes data → AI analysis → Recommendations 📤 Optimized Delivery Formats and sends responses back to Telegram Customization Opportunities Easy Modifications Multiple Marketplaces**: Add eBay, Flipkart, or local stores Product Categories**: Specialize for electronics, fashion, etc. Language Support**: Translate for different markets Branding**: Customize responses with your brand voice Advanced Extensions Price Monitoring**: Set up alerts for price drops User Preferences**: Remember customer preferences Analytics Dashboard**: Track popular products and queries Affiliate Integration**: Add commission tracking links Success Metrics & ROI Performance Benchmarks Response Time**: 3-5 seconds for product queries Accuracy**: 90%+ relevant product matches User Satisfaction**: 85%+ positive feedback in testing Business Impact Reduced Support Costs**: Automate 70% of product inquiries Increased Conversions**: Personalized recommendations boost sales 24/7 Availability**: Never miss a customer inquiry Scalability**: Handle unlimited concurrent users Workflow Complexity Intermediate Level - Requires API setup but includes detailed instructions. Perfect for users with basic n8n experience who want to create something powerful.

Description How it works This powerful workflow helps businesses and freelancers automatically manage invoices received on WhatsApp. It detects new messages, downloads attached invoices, extracts key data using OCR (Optical Character Recognition), summarizes the details with AI, updates Google Sheets for record-keeping, saves files to Google Drive, and instantly replies with a clean summary message all without manual effort. Perfect for small businesses, agencies, accountants, and freelancers who regularly receive invoices via WhatsApp. Say goodbye to manual data entry and hello to effortless automation. Set up steps Setup takes around 10–15 minutes: Connect your WhatsApp Cloud API to trigger incoming messages. Add your OCR.Space API key to extract invoice text. Link your Google Sheets and Google Drive accounts for data logging and storage. Enter your OpenAI API key for AI-based summarization. Import the template, test once, and you’re ready to automate your invoice workflow. Why use this workflow Save hours of manual data entry Keep all invoices safely stored and organized in Drive Get instant summaries directly in WhatsApp Improve efficiency for client billing, and expense tracking.