by Cheng Siong Chin
How It Works This workflow automates continuous data integrity monitoring and intelligent alert management across multiple data sources. Designed for data engineers, IT operations teams, and business intelligence analysts, it solves the critical challenge of detecting data anomalies and orchestrating appropriate responses based on severity levels. The system operates on scheduled intervals, fetching data from software metrics APIs and BI dashboards, then merging these sources for comprehensive analysis. It employs AI-powered validation and orchestration agents to detect anomalies, assess severity, and determine optimal response strategies. The workflow intelligently routes alerts based on severity classification, triggering critical notifications via email and Slack for high-priority issues while sending standard reports for routine findings. By maintaining detailed compliance audit logs and preparing executive summaries, it ensures stakeholders receive timely, actionable intelligence while creating audit trails for data quality monitoring initiatives. Setup Steps Configure Schedule Data Integrity Check trigger with monitoring frequency Connect Workflow Configuration node with data source parameters Set up Fetch Software Metrics and Fetch BI Dashboard Data nodes with respective API credentials Configure Merge Data Sources node for data consolidation logic Connect Data Validation Agent with OpenAI/Nvidia API credentials for anomaly detection Set up Orchestration Agent with AI API credentials for severity assessment Configure Check for Anomalies node with routing conditions Connect Route by Severity node with classification logic Prerequisites OpenAI or Nvidia API credentials for AI-powered analysis, API access to software metrics platforms Use Cases SaaS platforms monitoring service health metrics, e-commerce businesses tracking inventory data quality Customization Adjust scheduling frequency for monitoring intervals, modify severity thresholds for alert classification Benefits Reduces mean time to detection by 75%, eliminates manual data quality checks
by Cheng Siong Chin
How It Works MQTT ingests real-time sensor data from connected devices. The workflow normalizes the values and trains or retrains machine learning models on a defined schedule. An AI agent detects anomalies, validates the results for accuracy, and ensures reliable alerts. Detected issues are then routed to dashboards for visualization and sent via email notifications to relevant stakeholders, enabling timely monitoring and response. Setup Steps MQTT: Configure broker connection, set topic subscriptions, and verify data flow. ML Model: Define retraining schedule and specify historical data sources for model updates. AI Agent: Connect Claude or OpenAI APIs and configure anomaly validation prompts. Alerts: Set dashboard URL and email recipients to receive real-time notifications. Prerequisites MQTT broker credentials; historical training data; OpenAI/Claude API key; dashboard access; email service Use Cases IoT sensor monitoring; server performance tracking; network traffic anomalies; application log analysis; predictive maintenance alerts Customization Adjust sensitivity thresholds; swap ML models; modify notification channels; add Slack/Teams integration; customize validation rules Benefits Reduces detection latency 95%; eliminates manual monitoring; prevents false alerts; enables rapid incident response; improves system reliability
by Feras Dabour
Social Media Foto Creation Bot with Approval Loop Create & Share AI Photos with Telegram, Gemini & Post to Facebook, Instagram & X Description This n8n workflow turns your Telegram messenger into a complete AI Photo Content Pipeline. You send your photo idea as a text or voice message to a Telegram bot, collaborate with an AI to refine the prompt and social media caption, let Gemini generate the image, and then automatically publish it after your approval to Facebook, Instagram, and X (Twitter) – including status tracking and Telegram confirmations. What You Need to Get Started This workflow connects several external services. You will need the following credentials: Telegram Bot API Key** Create a bot via BotFather and copy the bot token. This is used by the Listen for incoming events and other Telegram nodes. OpenAI API Key** Required for Speech to Text (OpenAI Whisper) to transcribe voice notes. Used by the AI Agent model (OpenAI Chat Model) for prompt creation. Google Gemini API Key** Used by the Generate an image node (model: models/gemini-2.5-flash-image) to create the AI image. Google Drive & Sheets Access** The generated image is temporarily stored in a Google Drive folder (Upload image1) and later retrieved by Blotato. Prompts and post texts are logged to Google Sheets (Save Prompt & Post-Text) for tracking. Blotato API Key** The layer for social media publishing. Uploads the image as a media asset (Upload media1) and creates posts for Facebook, Instagram, and X. How the Workflow Operates – Step by Step 1. Input & Initial Processing (Telegram + Voice Handling) This phase receives your messages and prepares the input for the AI. | Node Name | Role in Workflow | | :--- | :--- | | Listen for incoming events | Telegram Trigger node that starts the workflow on any incoming message. | | Voice or Text | Set node that structures the incoming message into a unified text field. | | A Voice? | IF node that checks if the message is a voice note. | | Get Voice File | If voice is detected, this downloads the audio file from Telegram. | | Speech to Text | Uses OpenAI Whisper to convert the voice note into a text transcript. | The output of this stage is always a clean text string containing your image idea. 2. AI Core & Refinement Loop (Prompt + Caption via AI) Here, the AI drafts the image prompt (for Gemini) and the social media caption (for all platforms) and enters an approval loop with you. | Node Name | Role in Workflow | | :--- | :--- | | AI Agent | Central logic agent. Creates a videoPrompt (used for image generation) and socialMediaText based on your idea, and asks for feedback. | | OpenAI Chat Model | The LLM backing the agent (e.g., GPT-4.1-mini). | | Window Buffer Memory | Stores recent turns, allowing the agent to maintain context during revisions. | | Send questions or proposal to user | Sends the AI's suggestion for review back to you. | | Approved from user? | IF node that checks if the output is the approved JSON (meaning you replied with "ok" or "approved"). | | Parse AI Output | Code node that extracts the videoPrompt and socialMediaText fields from the agent’s final JSON output. | 3. Content Generation & Final Approval Once the prompt and caption are set, the image is created and sent to you for final approval before publishing. | Node Name | Role in Workflow | | :--- | :--- | | Inform user about processing | Telegram node to confirm: "Okay. Your image is being prepared now..." | | Save Prompt & Post-Text | Google Sheets node that logs the videoPrompt and socialMediaText. | | Generate an image | Gemini node that creates the image based on the videoPrompt. | | Send a photo message | Sends the generated image to Telegram for review. | | Send message and wait for response | Telegram node that waits for your response to the image (e.g., "Good?" / "Approve"). | | Upload image1 | Temporarily saves the generated image to Google Drive. | | Download image from Drive | Downloads the image back from Drive. | | If1 | IF node that checks if the image was approved in the previous step (approved == true). | 4. Upload & Publishing (Blotato) After final approval, the image is uploaded to Blotato, and post submissions for the social media platforms are created. | Node Name | Role in Workflow | | :--- | :--- | | Upload media1 | Blotato Media node. Uploads the approved image as a media asset and returns a public url. | | Create instagram Post | Creates an Instagram post using the media URL and socialMediaText. | | Create x post | Creates an X (Twitter) post using the media URL and socialMediaText. | | Create FB post | Creates a Facebook post using the media URL and socialMediaText. | 5. Status Monitoring & Retry Loops (X, Facebook, Instagram) An independent loop runs for each platform, polling Blotato until the post is either published or failed. | Node Name | Role in Workflow | | :--- | :--- | | Wait, Wait1, Wait2 | Initial pauses after post creation. | | Check Post Status, Get post1, Check Post Status1 | Blotato Get operations to fetch the current status of the post. | | Published to X?, Published to Facebook?, Published to Instagram? | IF nodes checking for the "published" status. | | Confirm publishing to X, Confirm publishing to Facebook, Confirm publishing to Instagram | Telegram nodes that notify you of successful publication (often including the post link). | | In Progress?, In Progress?1, In Progress?2 | IF nodes that check for "in-progress" status and loop back to the Wait nodes (Give Blotat other 5s). | | Send X Error Message, Send Facebook Error Message, Send Instagram Error Message | Telegram nodes that notify you if a failure occurs. | 🛠️ Personalizing Your Content Bot The workflow is highly adaptable to your personal brand and platform preferences: Tweak the AI Prompt & Behavior: Where: In the AI Agent node, within the System Message. Options: Change the tone (casual, professional, humorous) and the level of detail required for the prompt generation or the social media captions. Change Gemini Model or Image Options: Where: In the Generate an image node. Options: Swap the model or adjust image options like Aspect Ratio or Style based on Gemini's API capabilities. Modify Which Platforms You Post To: Where: In the Blotato nodes: Create instagram Post, Create x post, Create FB post. Options: Disable or delete branches for unused platforms, or add new platforms supported by Blotato.
by Tamas Demeter
This n8n template shows you how to turn outbound sales into a fully automated machine: scrape verified leads, research them with AI, and fire off personalized cold emails while you sleep. Use cases are simple: scale B2B lead gen without hiring more SDRs, run targeted outreach campaigns that don’t feel generic, and give founders or agencies a repeatable system that books more calls with less effort. Good to know At time of writing, each AI call may incur costs depending on your OpenAI plan. This workflow uses Apollo/Apify for lead scraping, which requires an active token. Telegram approval flow is optional but recommended for quality control. How it works Define your ICP (role, location, industry) in the workflow. Generate Apollo search URLs and scrape verified contacts. AI enriches leads with personal + company research. Hormozi-style cold emails are generated and queued for approval. Approve drafts in Telegram, then Gmail automatically sends them out. How to use Start with the included Schedule Trigger or replace with a Webhook/Form trigger. Adjust ICP settings in the Set node to fit your target audience. Test with a small batch of leads before scaling to larger runs. Requirements Google Sheets, Docs, Drive, and Gmail connected to n8n Apollo/Apify account and token OpenAI API key Telegram bot for approvals Customising this workflow Swap Apollo scraping with another data source if needed. Adapt the AI prompt for a different email tone (formal, friendly, etc.). Extend with a CRM integration to sync approved leads and outreach results.
by DIGITAL BIZ TECH
Weekly Timesheet Report + Pending Submissions Workflow Overview This workflow automates the entire weekly timesheet reporting cycle by integrating Salesforce, OpenAI, Gmail, and n8n. It retrieves employee timesheets for the previous week, identifies which were submitted or not, summarizes all line-item activities using OpenAI, and delivers a consolidated, manager-ready summary that mirrors the final email output. The workflow eliminates manual checking, reduces repeated follow-ups, and ensures leadership receives an accurate, structured, and consistent weekly report. Workflow Structure Data Source: Salesforce DBT Timesheet App This workflow requires the Digital Biz Tech – Simple Timesheet managed package to be installed in Salesforce. Install the Timesheet App: https://appexchange.salesforce.com/appxListingDetail?listingId=a077704c-2e99-4653-8bde-d32e1fafd8c6 The workflow retrieves: dbt__Timesheet__c — weekly timesheet records dbt__Timesheet_Line_Item__c — project and activity entries dbt__Employee__c — employee reference and metadata Billable, non-billable, and absence hour details Attendance information These combined objects form the complete dataset used for both submitted and pending sections. Trigger Weekly n8n Schedule Trigger — runs once every week. Submitted Path Retrieve submitted timesheets → Fetch line items → Convert to HTML → OpenAI summary → Merge with employee details. Pending Path Identify “New” timesheets → Fetch employee details → Generate pending submission list. Final Output Merge both paths → Build formatted report → Gmail sends weekly email to managers. Detailed Node-by-Node Explanation 1. Schedule Trigger Runs weekly without manual intervention and targets the previous full week. 2. Timesheet – Salesforce GetAll Fetches all dbt__Timesheet__c records matching: Timesheet for <week-start> to <week-end> Extracted fields include: Employee reference Status Billable, non-billable, absence hours Total hours Reporting period Feeds both processing paths. Processing Path A — Submitted Timesheets 3. Filter Submitted Filters timesheets where dbt__Status__c == "Submitted". 4. Loop Through Each Submitted Record Each employee’s timesheet is processed individually. 5. Retrieve Line Items Fetches all dbt__Timesheet_Line_Item__c entries: Project / Client Activity Duration Work description Billable category 6. Convert Line Items to HTML (Code Node) Transforms line items into well-structured HTML tables for clean LLM input. 7. OpenAI — Weekly Activity Summary OpenAI receives the HTML + Employee ID and returns a 4-point activity summary avoiding: Hours Dates Repeated or irrelevant metadata 8. Fetch Employee Details Retrieves employee name, email, and additional fields if needed. 9. Merge Employee + Summary Combines: Timesheet data Employee details OpenAI summary Creates a unified object. 10. Prepare Submitted Section (Code Node) Produces the formatted block used in the final email: Employee: Name Period: Start → End Status: Submitted Total Hours: ... Timesheet Line Items Breakdown: summary point summary point summary point summary point Processing Path B — Not Submitted Timesheets 11. Identify Not Submitted Timesheets still in dbt__Status__c == "New" are flagged. 12. Retrieve Employee Information Fetches employee name and email. 13. Merge Pending Information Maps each missing submission with its reporting period. 14. Prepare Pending Reporting Block Creates formatted pending entries: TIMESHEET NOT SUBMITTED Employee Name Email: user@example.com Final Assembly & Report Delivery 15. Merge Submitted + Pending Sections Combines all processed data. 16. Create Final Email (Code Node) Builds: Subject HTML body Section headers Manager recipient group Matches the final email layout. 17. Send Email via Gmail Automatically delivers the weekly summary to managers via Gmail OAuth. No manual involvement required. What Managers Receive Each Week 👤 Employee: Name 📅 Period: Start Date → End Date 📌 Status: Submitted 🕒 Total Hours: XX hrs Billable: XX hrs Non-Billable: XX hrs Absence: XX hrs Weekly Requirement Met: ✔️ / ❌ 📂 Timesheet Line Items Breakdown: • Summary point 1 • Summary point 2 • Summary point 3 • Summary point 4 🟥 TIMESHEET NOT SUBMITTED 🟥 Employee Name 📧 Email: user@example.com Data Flow Summary Salesforce → Filter Submitted / Not Submitted ↳ Submitted → Line Items → HTML → OpenAI Summary → Merge ↳ Not Submitted → Employee Lookup → Merge → Code Node formats unified report → Gmail sends professional weekly summary Technologies & Integrations | System | Purpose | Authentication | |------------|----------------------------------|----------------| | Salesforce | Timesheets, Employees, Timesheet Line Items | Salesforce OAuth | | OpenAI | Weekly activity summarization | API Key | | Gmail | Automated email delivery | Gmail OAuth | | n8n | Workflow automation & scheduling | Native | Agent System Prompt Summary > You are an AI assistant that extracts and summarizes weekly timesheet line items. Produce a clean, structured summary of work done for each employee. Focus only on project activities, tasks, accomplishments, and notable positives or negatives. Follow a strict JSON-only output format with four short points and no extra text or symbols. Key Features AI-driven extraction: Converts raw line items into clean weekly summaries. Strict formatting: Always returns controlled 4-point JSON summaries. Error-tolerant: Works even when timesheet entries are incomplete or messy. Seamless integration: Works smoothly with Salesforce, n8n, Gmail, or OpenAI. Setup Checklist Install DBT Timesheet App from Salesforce AppExchange Configure Salesforce OAuth Configure Gmail OAuth Set OpenAI model for summarization Update manager recipient list Activate the weekly schedule Summary This unified workflow delivers a complete, automated weekly reporting system that: Eliminates manual timesheet checking Identifies missing submissions instantly Generates high-quality AI summaries Improves visibility into employee productivity Ensures accurate billable/non-billable tracking Automates end-to-end weekly reporting Need Help or More Workflows? We can integrate this into your environment, tune the agent prompt, or extend it for more automation. We can also help you set it up for free — from connecting credentials to deployment. Contact: anushapriya.subaskar@digitalbiz.tech Website: https://www.digitalbiz.tech LinkedIn: https://www.linkedin.com/company/digital-biz-tech/ You can also DM us on LinkedIn for any help.
by Avkash Kakdiya
How it works This workflow monitors incoming Gmail messages for refund requests and uses AI to extract the order ID and reason. It then retrieves order details from Shopify to evaluate refund eligibility. Based on the order status, it automatically approves or routes the request for manual review. Customers and internal teams are notified accordingly, and all actions are logged in Google Sheets. Step-by-step Capture refund requests from email** Gmail Trigger – Detects unread emails with “Refund Request” in the subject. AI Agent2 – Extracts order ID and reason using AI. Groq Chat Model – Provides the language model used by the AI agent. Code in JavaScript – Converts AI output into structured JSON. Fetch order details from Shopify** Get an order – Retrieves order information using the extracted order ID. Evaluate refund eligibility** If – Checks whether the order status is “Delivered” to allow auto-approval. Handle responses and logging** Send a message to customer – Sends approval confirmation if eligible. Send a message to the team – Notifies team for manual review cases. Send a message to customer for "Pending" Status – Updates customer about manual review. Logs to Sheet – Records all refund actions and details in Google Sheets. Why use this? Automates repetitive refund handling tasks and reduces workload Improves customer experience with faster response times Ensures consistent decision-making based on order status Keeps a centralized log for auditing and reporting Easily extendable with additional validation rules or integrations
by Cheng Siong Chin
How It Works This workflow automates procurement fraud detection and supplier compliance monitoring for organizations managing complex purchasing operations. Designed for procurement teams, audit departments, and compliance officers, it solves the challenge of identifying fraudulent transactions, contract violations, and supplier misconduct across thousands of purchase orders and vendor relationships. The system schedules continuous monitoring, generates sample transaction data, analyzes patterns through dual AI agents (Price Reasonableness validates pricing against market rates, Delivery Agent assesses fulfillment performance), orchestrates comprehensive risk evaluation through Orchestration Agent, routes findings by severity (critical/high/medium/low), and triggers multi-channel responses: critical issues activate immediate Slack/email alerts with detailed logging; high-priority cases receive escalation workflows; medium/low findings generate routine compliance reports. By combining AI-powered anomaly detection with intelligent routing and coordinated notifications, organizations prevent fraud losses by 75%, ensure vendor compliance, maintain audit trails, and enable procurement teams to focus on strategic sourcing rather than manual transaction reviews. Setup Steps Connect Schedule Trigger for monitoring frequency Configure procurement systems with API credentials Add AI model API keys to Price Reasonableness, Delivery, and Orchestration Agent nodes Define fraud indicators and compliance thresholds in agent prompts based on company policies Link Slack webhooks for critical and high-priority fraud alerts to procurement and audit teams Connect email credentials for stakeholder notifications and escalation workflows Prerequisites Procurement system API access, AI service accounts, market pricing databases for benchmarking Use Cases Invoice fraud detection, bid rigging identification, duplicate payment prevention Customization Modify agent prompts for industry-specific fraud patterns, adjust risk scoring algorithms Benefits Prevents fraud losses by 75%, automates compliance monitoring across unlimited transactions
by Avkash Kakdiya
How it works This workflow fetches the latest blog post from a WordPress API and checks against a Google Sheets tracker to prevent duplicate processing. If a new post is found, the workflow updates the tracker and cleans the blog data. The cleaned content is then sent to a Gemini-powered AI agent to generate a newsletter and LinkedIn teaser. Finally, the workflow distributes the content via LinkedIn and Gmail to subscribers. Step-by-step Detect new blog content** Schedule Trigger – Runs the workflow automatically at intervals. HTTP Request – Fetches the latest blog post from WordPress. Last ID – Retrieves the last processed blog ID from Google Sheets. If – Compares IDs to check if the blog is new. Update Last ID – Updates the sheet with the latest blog ID. Clean and generate AI content** data cleanse – Cleans HTML, extracts title, content, and image. AI Agent2 – Generates newsletter and teaser content. Google Gemini Chat Model – Provides AI model for content generation. Distribute content across channels** Format Response – Parses and structures AI output. Create a post – Publishes content on LinkedIn. Email List – Fetches subscriber emails from Google Sheets. Loop Over Items – Iterates through each recipient. Send Email – Sends HTML newsletter via Gmail. Why use this? Automates end-to-end blog promotion workflow Prevents duplicate publishing using ID tracking Uses AI to generate engaging content instantly Saves time on manual posting and emailing Easily scalable for growing audiences
by Paul Karrmann
This n8n template helps you turn inbound messages into a clean, deduped queue of actionable tickets. It includes Slack and Gmail as ready to use examples, but the key idea is the universal intake normalizer: you can plug in other sources later (forms, webhooks, chat tools, other inboxes) as long as you map them into the same normalized schema. Good to know This workflow sends message content to an LLM for classification. Keep sensitive data out of the prompt, and only process messages you are allowed to process. Costs depend on message volume and length, so truncation and tight filters matter. How it works Collect inbound items (Slack and Gmail are included as examples). Normalize each item into one shared JSON format so every source behaves the same. Deduplicate items using a data table so repeats are skipped. Use an AI agent with structured output to score urgency and importance, produce a summary, and draft a reply. Create a Notion ticket for tracking, and optionally notify Slack for high priority items. Setup steps Connect credentials for Slack, Gmail, Notion, and your LLM provider. Choose your Slack channel and set a Gmail filter that keeps volume manageable. Select your Notion database and ensure properties match the field mappings. Create or select a data table and map the unique ID column for deduplication. Adjust the notification threshold and schedule interval to match your workflow. Requirements Slack workspace access (optional if you swap the source) Gmail access (optional if you swap the source) Notion database for ticket creation LLM API credentials Customising this workflow Add new sources by mapping them into the normalizer schema. Truncate long messages before the AI step to reduce cost. Change categories, scoring, and thresholds to match your operating model.
by Automate With Marc
Image to Video Social Media Reel Generator + Autopost Without AI Slop Google Drive → AI Video Generation → Captions → Approval → Instagram & TikTok Watch Step-By-Step Video: https://www.youtube.com/watch?v=jPOYxQF25ws Turn a folder of images into fully-produced short-form social media reels—automatically. This workflow picks a random image, generates a cinematic AI video from it, adds text overlays and captions, waits for your approval, and then posts to Instagram and TikTok. What this template does On a scheduled basis (default: daily at 9:00 AM), this workflow: Selects a random image from a Google Drive folder Uploads the image for processing Generates a cinematic image-to-video prompt using AI Creates an 8-second vertical video using an image-to-video model (via Wavespeed) Applies captions and text overlays using Submagic Waits for human approval via email Automatically posts the approved reel to: Instagram TikTok If the video is not approved, the workflow loops and tries again on the next run. Why this workflow is useful Converts static images into high-engagement video content Removes repetitive manual work in short-form content creation Keeps a human-in-the-loop before anything is published Perfect for: Creators & solopreneurs Social media managers Small businesses & local brands AI-first content pipelines High-level flow Schedule → Pick Image → Generate Video → Add Captions → Approve → Post Node overview Schedule Trigger Runs the workflow automatically at a fixed time (default: daily at 9 AM). Google Drive – Search Files Fetches all images from a selected Drive folder. Randomizer (Code Node) Selects one random image to avoid repetitive posting. Upload Media Uploads the selected image so it can be used by downstream tools. Prompt Generator (AI) Generates a high-quality cinematic prompt optimized for image-to-video models Wavespeed – Image to Video Creates an 8-second, 9:16 video from the image + prompt. Wait & Polling (IF Nodes) Waits and checks until video generation is completed. Submagic – Text Overlay & Captioning Adds captions and overlays in a short-form style optimized for social platforms. Gmail – Send for Approval Sends a preview link and caption to your inbox and waits for approval. IF (Approved?) Yes: posts the reel automatically No: skips posting and retries in the next run Blotato – Social Posting Publishes the approved reel to: Instagram TikTok Requirements Before running this template, you’ll need to configure: Google Drive OAuth (image source folder) OpenAI API key (prompt generation) Wavespeed API key (image-to-video generation) Submagic API key (captions & overlays) Gmail OAuth (approval workflow) Blotato account (Instagram & TikTok posting) All credentials must be added manually after importing. Setup instructions Import the template into your n8n workspace Connect your Google Drive account and set your image folder Add credentials for: OpenAI Wavespeed Submagic Gmail Blotato Adjust the Schedule Trigger if needed Run the workflow once to test the full flow Enable the workflow to start daily automated posting Customization ideas Change video duration, aspect ratio, or style Modify the AI prompt to match your brand voice Post only after manual approval (already built-in) Add a Slack or Telegram approval step Duplicate posting logic for YouTube Shorts or Facebook Reels Store generated videos in cloud storage or a content database Troubleshooting No images found: check Drive folder ID and permissions Video stuck generating: increase wait time or polling interval Approval email not received: verify Gmail OAuth and inbox filters Posting fails: confirm Blotato account and platform permissions
by Neloy Barman
Self-Hosted This workflow provides a complete end-to-end system for capturing, analyzing, and routing customer feedback. By combining local multimodal AI processing with structured data storage, it allows teams to respond to customer needs in real-time without compromising data privacy. Who is this for? This is designed for Customer Success Managers, Product Teams, and Community Leads who need to automate the triage of high-volume feedback. It is particularly useful for organizations that handle sensitive customer data and prefer local AI processing over cloud-based API calls. 🛠️ Tech Stack Tally.so**: For front-end feedback collection. LM Studio**: To host the local AI models (Qwen3-VL). PostgreSQL**: For persistent data storage and reporting. Discord**: For real-time team notifications. ✨ How it works Form Submission: The workflow triggers when a new submission is received from Tally.so. Multimodal Analysis: The OpenAI node (pointing to LM Studio) processes the input using the Qwen3-VL model across three specific layers: Sentiment Analysis: Evaluates the text to determine if the customer is Positive, Negative, or Neutral. Zero-Shot Classification: Categorizes the feedback into pre-defined labels based on instructions in the prompt. Vision Processing: Analyzes any attached images to extract descriptive keywords or identify UI elements mentioned in the feedback. Data Storage: The PostgreSQL node logs the user's details, the original message, and all AI-generated insights. AI-Driven Routing: The same Qwen3-VL model makes the routing decision by evaluating the classification results and determining the appropriate path for the data to follow. Discord Notification: The Discord node sends a formatted message to the corresponding channel, ensuring the support team sees urgent issues while the marketing team sees positive testimonials. 📋 Requirements LM Studio** running a local server on port 1234. Qwen3-VL-4B** (GGUF) model loaded in LM Studio. PostgreSQL** instance with a table configured for feedback data. Discord Bot Token** and specific Channel IDs. 🚀 How to set up Prepare your Local AI: Open LM Studio and download the Qwen3-VL-4B model. Start the Local Server on port 1234 and ensure CORS is enabled. Disable the Require Authentication setting in the Local Server tab. Configure PostgreSQL: Ensure your database is running. Create a table named customer_feedback with columns for name, email_address, feedback_message, image_url, sentiment, category, and img_keywords. Import the Workflow: Import the JSON file into your n8n instance. Link Services: Update the Webhook node with your Tally.so URL. In the Discord nodes, paste the relevant Channel IDs for your #support, #feedback, and #general channels. Test and Activate: Toggle the workflow to Active. Send a test submission through your Tally form and verify the data appears in PostgreSQL and Discord. 🔑 Credential Setup To run this workflow, you must configure the following credentials in n8n: OpenAI API (Local)**: Create a new OpenAI API credential. API Key: Enter any placeholder text (e.g., lm-studio). Base URL: Set this to your machine's local IP address (e.g., http://192.168.1.10:1234/v1) to ensure n8n can connect to the local AI server, especially if running within a Docker container. PostgreSQL**: Create a new PostgreSQL credential. Enter your database Host, Database Name, User, and Password. If using the provided Docker setup, the host is usually db. Discord Bot**: Create a new Discord Bot API credential. Paste your Bot Token obtained from the Discord Developer Portal. Tally**: Create a new Tally API credential. Enter your API Key, which you can find in your Tally.so account settings. ⚙️ How to customize Refine AI Logic**: Update the System Message in the AI node to change classification categories or sentiment sensitivity. Switch to Cloud AI: If you prefer not to use a local model, you can swap the local **LM Studio connection for any 3rd party API, such as OpenAI (GPT-4o), Anthropic (Claude), or Google Gemini, by updating the node credentials and Base URL. Expand Destinations: Add more **Discord nodes or integrate Slack to notify different departments based on the AI's routing decision. Custom Triggers: Replace the Tally webhook with a **Typeform, Google Forms, or a custom Webhook trigger if your collection stack differs.
by John Alejandro SIlva
Rizz AI: The Multimodal Dating Assistant 💘 Rizz AI is not just a chatbot; it's a full-featured, AI-powered CRM for your dating life. Built entirely in n8n, this workflow turns Telegram into a powerful "Wingman" that helps you craft the perfect reply, remember details about your matches, and optimize your dating strategy using Google Gemini 1.5 Pro. 🔥 Key Features 👁️ Multimodal Vision:** Send a screenshot of a Tinder/Hinge profile or a WhatsApp chat, and the AI will analyze the text, subtext, and vibe to give you tactical advice. 🗣️ Audio Analysis:** Forward voice notes, and the AI will transcribe and analyze the tone to tell you if they are interested. 🧠 Long-Term Memory:** Remembers details about specific matches (e.g., "Sofia likes sushi") so you don't ask the same thing twice. 📊 Lead Management (CRM):** Automatically tracks matching stage, interest level, and next steps in Google Sheets. 🎨 Personalized Style:** Adapts advice to your specific "Rizz Style" (e.g., Mystery, Direct, Funny) defined in your profile. 🛠️ How It Works Ingest: You send text, audio, or images to your private Telegram Bot. Process: The workflow routes the input through Gemini Vision (for images) or Whisper/Gemini (for audio). Retrieve: It queries your Google Sheet to see if this person is a new lead or an existing match. Reason: The AI Agent (with tools) decides the best move: suggesting a reply, logging a red flag, or scheduling a date. Respond: You receive 3 draft options to copy-paste directly into your dating app. 📋 Setup Instructions 1. Google Sheets (Database) Make a copy of the Rizz AI Database Template. Share/Connect your Google Drive credential in n8n. Update the Sheet ID in the Get Rizzler Profile and other Sheet nodes. 2. Telegram Bot Talk to @BotFather on Telegram to create a new bot. Copy the API Token into the Telegram Trigger and Send Message nodes. 3. Google Gemini Get a free API Key from Google AI Studio. Connect it to the Google Gemini Chat Model node. 💡 Need Assistance? If you’d like help customizing or extending this workflow, feel free to reach out: 📧 Email: johnsilva11031@gmail.com 🔗 LinkedIn: John Alejandro Silva Rodríguez