Workflow Templates

🎨 Instagram Carousel & Caption Generator on Autopilot (GPT-5 + Nano Banana + Blotato + Google Sheets) Description Watch the full step-by-step tutorial on YouTube: https://youtu.be/id22R7iBTjo Disclaimer (self-hosted requirement): This template assumes you have valid API credentials for OpenAI, Wavespeed/Nano Banana, Blotato, and Google. If using n8n Self-Hosted, ensure HTTPS access and credentials are set in your instance. How It Works Chat Trigger – Receive a topic/idea (e.g. “5 best podcast tips”). Image Prompt Generator (GPT-5) – Creates 5 prompts using the “Hook → Problem → Insight → Solution → CTA” framework. Structured Output Parser – Formats output into a JSON array. Generate Images (Nano Banana) – Converts prompts into high-quality visuals. Wait for Render – Ensures image generation completes. Fetch Rendered Image URLs – Retrieves image links. Upload to Blotato – Hosts and prepares images for posting. Collect Media URLs – Gathers all uploaded image URLs. Log to Google Sheets – Stores image URLs + timestamps for tracking. Caption Generator (GPT-5) – Writes an SEO-friendly caption. Merge Caption + Images – Combines data. Post Carousel (Blotato) – Publishes directly to Instagram. Step-by-Step Setup Instructions 1) Prerequisites n8n (Cloud or Self-Hosted) OpenAI API Key (GPT-5) Wavespeed API Key (Nano Banana) Blotato API credentials (connected to Instagram) Google Sheets OAuth credentials 2) Add Credentials in n8n OpenAI: Settings → Credentials → Add “OpenAI API” Wavespeed: HTTP Header Auth (e.g. Authorization: Bearer <API_KEY>) Blotato: Add “Blotato API” Google Sheets: Add “Google Sheets OAuth2 API” 3) Configure & Test Run with an idea like “Top 5 design hacks”. Check generated images, caption, and logged sheet entry. Confirm posting works via Blotato. 4) Optional Add a Schedule Trigger for weekly automation. Insert a Slack approval loop before posting. Customization Guide ✏️ Change design style: Modify adjectives in the Image Prompt Generator. 📑 Adjust number of slides: Change Split node loop count. 💬 Tone of captions: Edit Caption Generator’s system prompt. ⏱️ Adjust render wait time: If image generation takes longer, increase the Wait node duration from 30 seconds to 60 seconds or more. 🗂️ Log extra data: Add columns in Google Sheets for campaign or topic. 🔁 Swap posting tool: Replace Blotato with your scheduler or email node. Requirements OpenAI API key (GPT-5 or compatible) Wavespeed API key (Nano Banana) Blotato API credentials Google Sheets OAuth credentials n8n account (Cloud or Self-Hosted)

📊 Google Ads + OpenAI + Sheets — Monthly AI Performance Analysis Automate monthly ad performance insights with AI-powered recommendations 🧩 Overview This workflow automatically analyzes Google Ads performance every month, using the Google Ads API and OpenAI (GPT-4o) to uncover which ad themes, categories, and messages perform best. It then generates a structured AI report, saves it to Google Sheets, and sends a Slack summary to your marketing team. 💡 Perfect for digital marketers, agencies, and growth analysts who want automated campaign insights without manually crunching numbers. ⚙️ Features ✅ Automatically runs on the 1st of each month ✅ Fetches last 30 days of ad performance via Google Ads API (GAQL) ✅ Uses GPT-4o for natural-language insights & improvement ideas ✅ Groups ads by category and theme (e.g., “Free Shipping,” “Premium”) ✅ Generates a clean, formatted markdown report ✅ Archives reports in Google Sheets for trend tracking ✅ Notifies your Slack channel with AI-driven recommendations 🧠 Architecture | Component | Purpose | | ------------------- | ------------------------------------------------ | | n8n | Workflow engine | | Google Ads API | Source of ad performance data | | OpenAI (GPT-4o) | Analyzes CTR patterns and writes recommendations | | Google Sheets | Report archiving and history tracking | | Slack | Team notifications | 🧭 Workflow Logic (Summary) Monthly Trigger (1st of Month) ⬇️ 1️⃣ Get Performance Data (Google Ads API) Fetches 30-day CTR, clicks, impressions for all responsive search ads. ⬇️ 2️⃣ Prepare Performance Data Groups data by ad group and theme keywords, builds an AI prompt. ⬇️ 3️⃣ AI Agent (LangChain) + GPT-4o Analyzes patterns and generates actionable insights. ⬇️ 4️⃣ Generate Report (Code) Formats a Markdown report with AI recommendations and KPIs. ⬇️ 5️⃣ Save to Google Sheets Archives results for long-term analytics. ⬇️ 6️⃣ Send Report to Slack Delivers the summary directly to your marketing channel. 🔑 Environment Variables | Variable | Example | Description | | ------------------------ | ----------------------------- | ------------------------------ | | GOOGLE_ADS_CUSTOMER_ID | 123-456-7890 | Google Ads customer account ID | | GOOGLE_ADS_API_VERSION | v17 | Current Ads API version | | GOOGLE_SHEET_ID | 1xA1B2c3D4EFgH... | Target spreadsheet ID | | OPENAI_API_KEY | sk-xxxxx | OpenAI API key for GPT-4o | | SLACK_WEBHOOK_URL | https://hooks.slack.com/... | Slack incoming webhook | 🔐 Credential Setup | Service | Type | Required Scopes | | ----------------- | ----------------------------- | ---------------------------------------------- | | Google Ads | OAuth2 (googleAdsOAuth2Api) | https://www.googleapis.com/auth/adwords | | OpenAI | API key (openAiApi) | Full access | | Google Sheets | OAuth2 | https://www.googleapis.com/auth/spreadsheets | | Slack | Webhook | chat:write | 🧱 Node-by-Node Breakdown | Node | Purpose | Key Configuration | | ---------------------------------- | ----------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------- | | Monthly Trigger | Starts workflow on 1st of every month | Cron: 0 0 1 * * | | Get Performance Data | Queries Ads data | Endpoint: https://googleads.googleapis.com/v17/customers/{id}/googleAds:searchQuery: GAQL (CTR, clicks, impressions, last 30 days) | | Prepare Performance Data | Aggregates and builds AI prompt | Groups by ad group and theme, computes CTRs | | AI Agent – Analyze Performance | Passes formatted data to GPT-4o | System message: “You are a Google Ads performance analyst…” | | OpenAI Chat Model (GPT-4o) | Analytical reasoning engine | Model: gpt-4o, Temperature 0.2 | | Generate Report | Parses AI output, formats Markdown report | Adds recommendations + next steps | | Save Report to Sheets | Archives report | Sheet name: Performance Reports | | Send Report (Slack) | Sends summary | Uses report_markdown variable | 🧠 AI Report Example 30-Day Performance Analysis Report Executive Summary Analyzed: 940 ads Period: Last 30 days Top Performing Categories Running Shoes: 9.4% CTR (120 ads) Fitness Apparel: 8.2% CTR (90 ads) Top Performing Themes "Free Shipping" messaging: 9.8% CTR (58 ads) "Premium" messaging: 8.5% CTR (44 ads) AI-Powered Recommendations [HIGH] Emphasize “Free Shipping” across more ad groups. Expected Impact: +5 % CTR [MEDIUM] Test “Premium Quality” vs. “New Arrivals.” Expected Impact: +3 % CTR Next Steps Implement new ad variations A/B test messaging Re-analyze next month 🧩 Testing Procedure 1️⃣ Temporarily disable the cron trigger. 2️⃣ Run the workflow manually. 3️⃣ Confirm: Google Ads node returns JSON with results. AI Agent output is valid JSON. Report is written to Sheets. Slack message received. 4️⃣ Re-enable the monthly trigger once verified. 🧾 Output in Google Sheets | Date | Ads Analyzed | Top Category | Top Theme | Key Recommendations | Generated At | | ---------- | ------------ | ------------- | ------------- | ---------------------------------- | ----------------- | | 2025-10-01 | 940 | Running Shoes | Free Shipping | “Add Free Shipping copy to 10 ads” | 2025-10-01T00:05Z | 🪜 Maintenance | Frequency | Task | | --------- | ----------------------------------------- | | Monthly | Review AI accuracy and update themes list | | Quarterly | Refresh Google Ads API credentials | | As needed | Update GAQL fields for new metrics | ⚙️ API Verification Endpoint: POST https://googleads.googleapis.com/v17/customers/{customer_id}/googleAds:search Scopes: https://www.googleapis.com/auth/adwords GAQL Query: SELECT ad_group_ad.ad.id, ad_group_ad.ad.responsive_search_ad.headlines, ad_group.name, metrics.impressions, metrics.clicks, metrics.ctr FROM ad_group_ad WHERE segments.date DURING LAST_30_DAYS AND metrics.impressions > 100 ORDER BY metrics.clicks DESC LIMIT 1000 ✅ Fully valid query — verified for GAQL syntax, fields, and resource joins. ✅ OAuth2 flow handled by n8n’s googleAdsOAuth2Api. ✅ Optional: add "timeout": 60000 for large accounts. 📈 Metrics of Success | KPI | Target | | -------------------------- | ---------------- | | Report accuracy | ≥ 95 % | | Monthly automation success | ≥ 99 % | | CTR improvement tracking | +3–5 % over time | 🔗 References Google Ads API Docs LangChain in n8n OpenAI API Reference Google Sheets API Slack Incoming Webhooks 🎯 Conclusion You now have a fully automated Google Ads performance analysis workflow powered by: Google Ads API** for granular metrics OpenAI GPT-4o** for intelligent recommendations Google Sheets** for archiving Slack** for team-wide updates 💡 Result: A recurring, data-driven optimization loop that improves ad performance every month — with zero manual effort.

Analyze food ingredients from Telegram photos using Gemini and Airtable 🛡️ Personal Ingredient Bodyguard Turn your Telegram bot into an intelligent food safety scanner. This workflow analyzes photos of ingredient labels sent via Telegram, extracts the text using AI, and cross-references it against your personal database of "Good" and "Bad" ingredients in Airtable. It solves the problem of manually reading tiny, complex labels for allergies or dietary restrictions. Whether you are Vegan, Halal, allergic to nuts, or just avoiding specific additives, this workflow acts as a strict, personalized bodyguard for your diet. It even features a customizable "Persona" (like a Sarcastic Bodyguard) to make safety checks fun. 🎯 Who is it for? People with specific dietary restrictions (Vegan, Gluten-free, Keto). Individuals with food allergies (Nuts, Dairy, Shellfish). Special dietary observers (Halal, Kosher). Health-conscious shoppers avoiding specific additives (e.g., E120, Aspartame). 🚀 How it works Trigger: You send a photo of a product label to your Telegram Bot. Fetch Rules: The workflow retrieves your active "Watchlist" (Ingredients to avoid/prefer) and "Persona" settings from Airtable. Vision & Logic: It uses an AI Vision model to extract text from the image (OCR) and Google Gemini to analyze the text against your strict veto rules (e.g., "Safe" only if ZERO bad items are found). Response: The bot replies instantly on Telegram with a Safe/Unsafe verdict, highlighting detected ingredients using HTML formatting. Log: The result is saved back to Airtable for your records. ⚙️ How to set up This workflow relies on a specific Airtable structure to function as the "Brain." Set up Airtable Sign up for Airtable: Click here Copy the required Base: Click here to copy the "Ingredients Brain" base Connect Airtable to n8n (5-min guide): Watch Tutorial Set up Telegram Message @BotFather on Telegram to create a new bot and get your API Token. Add your Telegram credentials in n8n. Configure AI Add your Google Gemini API credentials. Note on OCR: This template is configured to use a local LLM for OCR to save costs (via the OpenAI-compatible node). If you do not have a local model running, simply swap the "OpenAI Chat Model" node for a standard GPT-4o or Gemini Vision node. 📋 Requirements n8n** (Cloud or Self-hosted) Airtable** account (Free tier works) Telegram** account Google Gemini** API Key Local LLM* (Optional, for free OCR) OR *OpenAI/Gemini** Key (for standard Cloud Vision) 🎨 How to customize Change the Persona:** Go to the "Preferences" table in Airtable to change the bot's personality (e.g., "Helpful Nutritionist") and output language. Update Ingredients:** Add or remove items in the "Watchlist" table. Mark them as "Good Stuff" or "Bad Stuff" and set Status to "Active". Adjust Sensitivity:** The AI prompt in the "AI Agent" node is set to strict "Veto" mode (Bad overrides Good). You can modify the system prompt to change this logic. ⚠️ Disclaimer This tool is for informational purposes only. Not Medical Advice: Do not rely on this for life-threatening allergies. AI Limitations: OCR can misread text, and AI can hallucinate. Verify: Always double-check the physical product label. Use at your own risk.

Automated Meeting Minutes from Video Recordings This workflow automatically transforms video recordings of meetings into structured, professional meeting minutes in Notion. It uses local AI models (Whisper for transcription and Ollama for summarization) to ensure privacy and cost efficiency, while uploading the original video to Google Drive for safekeeping. Ideal for creative teams, production reviews, or any scenario where visual context is as important as the spoken word. 🔄 How It Works Wait & Detect: The workflow monitors a local folder. When a new .mkv video file is added, it waits until the file has finished copying. Prepare Audio: The video is converted into a .wav audio file optimized for transcription (under 25 MB with high clarity). Transcribe Locally: The local Whisper model generates a timestamped text transcript. Generate Smart Minutes: The transcript is sent to a local Ollama LLM, which produces structured, summarized meeting notes. Store & Share: The original video is uploaded to Google Drive, a new page is created in Notion with the notes and a link to the video, and a completion notification is sent via Discord. ⏱️ Setup Steps Estimated Time**: 10–15 minutes (for technically experienced users). Prerequisites**: Install Python, FFmpeg, and required packages (openai-whisper, ffmpeg-python). Run Ollama locally with a compatible model (e.g., gpt-oss:20b, llama3, mistral). Configure n8n credentials for Google Drive, Notion, and Discord. Workflow Configuration**: Update the file paths for the helper scripts (wait-for-file.ps1, create_wav.py, transcribe_return.py) in the respective "Execute Command" nodes. Change the input folder path (G:\OBS\videos) in the "File" node to your own recording directory. Replace the Google Drive folder ID and Notion database/page ID in their respective nodes. > 💡 Note: Detailed instructions for each step, including error handling and variable setup, are documented in the Sticky Notes within the workflow itself. 📁 Helper Scripts Documentation wait-for-file.ps1 A PowerShell script that checks if a file is still being written to (i.e., locked by another process). It returns 0 if the file is free and 1 if it is still locked. Usage: .\wait-for-file.ps1 -FilePath "C:\path\to\your\file.mkv" create_wav.py A Python script that converts a video file into a .wav audio file. It automatically calculates the necessary audio bitrate to keep the output file under 25 MB—a common requirement for many transcription services. Usage: python create_wav.py "C:\path\to\your\file.mkv" transcribe_return.py A Python script that uses a local Whisper model to transcribe an audio file. It can auto-detect the language or use a language code specified in the filename (e.g., meeting.en.mkv for English, meeting.es.mkv for Spanish). The transcript is printed directly to stdout with timestamps, which is then captured by the n8n workflow. Usage: Auto-detect language python transcribe_return.py "C:\path\to\your\file.mkv" Force language via filename python transcribe_return.py "C:\path\to\your\file.es.mkv" `

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.

Explorium Agent for Slack AI-powered Slack bot for business intelligence queries using Explorium API through MCP. Prerequisites Slack workspace with admin access Anthropic API key (You can replace with other LLM Chat) Explorium API Key 1. Create Slack App Create App Go to api.slack.com/apps Click Create New App → From scratch Give it name (e.g., "Explorium Agent") and select workspace Bot Permissions (OAuth & Permissions) Add these Bot Token Scopes: app_mentions:read channels:history channels:read chat:write emoji:read groups:history groups:read im:history im:read mpim:history mpim:read reactions:read users:read Enable Events Event Subscriptions → Enable Add Request URL (from n8n Slack Trigger node) Subscribe to bot events: app_mention message.channels message.groups message.im message.mpim reaction_added Install App Install App → Install to Workspace Copy Bot User OAuth Token (xoxb-...) 2. Configure n8n Import & Setup Import this JSON template Slack Trigger node: Add Slack credential with Bot Token Copy webhook URL Paste in Slack Event Subscriptions Request URL Anthropic Chat Model node: Add Anthropic API credential Model: claude-haiku-4-5-20251001 (You can replace it with other chat models) MCP Client node: Endpoint: https://mcp.explorium.ai/mcp Header Auth: Add Explorium API key Usage Examples @ExploriumAgent find tech companies in SF with 50-200 employees @ExploriumAgent show Microsoft's technology stack @ExploriumAgent get CMO contacts at healthcare companies `

Instantly access live OKX Spot Market data directly in Telegram! This workflow integrates the OKX REST v5 API with Telegram and optional GPT-4.1-mini formatting, delivering real-time insights such as latest prices, order book depth, candlesticks, trades, and mark prices — all in clean, structured reports. 🔎 How It Works A Telegram Trigger node listens for incoming user commands. The User Authentication node validates the Telegram ID to allow only authorized users. The workflow creates a Session ID from chat.id to manage session memory. The OKX AI Agent orchestrates data retrieval via HTTP requests to OKX endpoints: Latest Price (/api/v5/market/ticker?instId=BTC-USDT) 24h Stats (/api/v5/market/ticker?instId=BTC-USDT) Order Book Depth (/api/v5/market/books?instId=BTC-USDT&sz=50) Best Bid/Ask (book ticker snapshot) Candlesticks / Klines (/api/v5/market/candles?instId=BTC-USDT&bar=15m) Average / Mark Price (/api/v5/market/mark-price?instType=SPOT&instId=BTC-USDT) Recent Trades (/api/v5/market/trades?instId=BTC-USDT&limit=100) Utility tools refine the data: Calculator → spreads, % change, normalized volumes. Think → reshapes raw JSON into clean text. Simple Memory → stores sessionId, symbol, and state for multi-turn interactions. A message splitter ensures Telegram output stays under 4000 characters. Final results are sent to Telegram in structured, human-readable format. ✅ What You Can Do with This Agent Get latest price and 24h stats for any Spot instrument. Retrieve order book depth with configurable size (up to 400 levels). View best bid/ask snapshots instantly. Fetch candlestick OHLCV data across intervals (1m → 1M). Monitor recent trades (up to 100). Check the mark price as a fair average reference. Receive clean, Telegram-ready reports (auto-split if too long). 🛠️ Setup Steps Create a Telegram Bot Use @BotFather to generate a bot token. Configure in n8n Import OKX AI Agent v1.02.json. Replace the placeholder in User Authentication node with your Telegram ID. Add Telegram API credentials (bot token). Add your OpenAI API key for GPT-4.1-mini. Add your OKX API key optional. Deploy and Test Activate the workflow in n8n. Send a query like BTC-USDT to your bot. Instantly get structured OKX Spot data back in Telegram. 📺 Setup Video Tutorial Watch the full setup guide on YouTube: ⚡ Unlock real-time OKX Spot Market insights directly in Telegram — no private API keys required! 🧾 Licensing & Attribution © 2025 Treasurium Capital Limited Company Architecture, prompts, and trade report structure are IP-protected. No unauthorized rebranding permitted. 🔗 For support: Don Jayamaha – LinkedIn

N8N UGC Video Generator - Setup Instructions Transform Product Images into Professional UGC Videos with AI This powerful n8n workflow automatically converts product images into professional User-Generated Content (UGC) videos using cutting-edge AI technologies including Gemini 2.5 Flash, Claude 4 Sonnet, and VEO3 Fast. Who's it for Content creators** looking to scale video production E-commerce businesses** needing authentic product videos Marketing agencies** creating UGC campaigns for clients Social media managers** requiring quick video content How it works The workflow operates in 4 distinct phases: Phase 0: Setup - Configure all required API credentials and services Phase 1: Image Enhancement - AI analyzes and optimizes your product image Phase 2: Script Generation - Creates authentic dialogue scripts based on your input Phase 3: Video Production - Generates and merges professional video segments Requirements Essential Services & APIs Telegram Bot Token** (create via @BotFather) OpenRouter API** with Gemini 2.5 Flash access Anthropic API** for Claude 4 Sonnet KIE.AI Account** with VEO3 Fast access N8N Instance** (cloud or self-hosted) Technical Prerequisites Basic understanding of n8n workflows API key management experience Telegram bot creation knowledge How to set up Step 1: Service Configuration Create Telegram Bot Message @BotFather on Telegram Use /newbot command and follow instructions Save the bot token for later use OpenRouter Setup Sign up at openrouter.ai Purchase credits for Gemini 2.5 Flash access Generate and save API key Anthropic Configuration Create account at console.anthropic.com Add credits to your account Generate Claude API key KIE.AI Access Register at kie.ai Subscribe to VEO3 Fast plan Obtain bearer token Step 2: N8N Credential Setup Configure these credentials in your n8n instance: Telegram API Credential Name: telegramApi Bot Token: Your Telegram bot token OpenRouter API Credential Name: openRouterApi API Key: Your OpenRouter key Anthropic API Credential Name: anthropicApi API Key: Your Anthropic key HTTP Bearer Auth Credential Name: httpBearerAuth Token: Your KIE.AI bearer token Step 3: Workflow Configuration Import the Workflow Copy the provided JSON workflow Import into your n8n instance Update Telegram Token Locate the "Edit Fields" node Replace "Your Telegram Token" with your actual bot token Configure Webhook URLs Ensure all Telegram nodes have proper webhook configurations Test webhook connectivity Step 4: Testing & Validation Test Individual Nodes Verify each API connection Check credential configurations Confirm node responses End-to-End Testing Send a test image to your Telegram bot Follow the complete workflow process Verify final video output How to customize the workflow Modify Image Enhancement Prompts Edit the HTTP Request node for Gemini Adjust the prompt text to match your style preferences Test different aspect ratios (current: 1:1 square format) Customize Script Generation Modify the Basic LLM Chain node prompt Adjust video segment duration (current: 7-8 seconds each) Change dialogue style and tone requirements Video Generation Settings Update VEO3 API parameters in HTTP Request1 node Modify aspect ratio (current: 16:9) Adjust model settings and seeds for consistency Output Customization Change final video format in MediaFX node Modify Telegram message templates Add additional processing steps before delivery Workflow Operation Phase 1: Image Reception and Enhancement User sends product image via Telegram System prompts for enhancement instructions Gemini AI analyzes and optimizes image Enhanced square-format image returned Phase 2: Analysis and Script Creation System requests dialogue concept from user AI analyzes image details and environment Claude generates realistic 2-segment script Scripts respect physical constraints of original image Phase 3: Video Generation Two separate videos generated using VEO3 System monitors generation status Videos merged into single flowing sequence Final video delivered via Telegram Troubleshooting Common Issues API Rate Limits**: Implement delays between requests Webhook Failures**: Verify URL configurations and SSL certificates Video Generation Timeouts**: Increase wait node duration Credential Errors**: Double-check all API keys and permissions Error Handling The workflow includes automatic error detection: Failed video generation triggers error message Status checking prevents infinite loops Alternative outputs for different scenarios Advanced Features Batch Processing Modify trigger to handle multiple images Add queue management for high-volume usage Implement user session tracking Custom Branding Add watermarks or logos to generated videos Customize color schemes and styling Include brand-specific dialogue templates Analytics Integration Track usage metrics and success rates Monitor API costs and optimization opportunities Implement user behavior analytics Cost Optimization API Usage Management Monitor token consumption across services Implement caching for repeated requests Use lower-cost models for testing phases Efficiency Improvements Optimize image sizes before processing Implement smart retry mechanisms Use batch processing where possible This workflow transforms static product images into engaging, professional UGC videos automatically, saving hours of manual video creation while maintaining high quality output perfect for social media platforms.

This n8n template from Intuz provides a complete solution to automate the extraction of critical information from PDF documents like faxes, or any PDFs. It uses the power of Google Gemini's multimodal capabilities to read the document, identify key fields, and organize the data into a structured format, saving it directly to a Google Sheet. Who's this workflow for? Healthcare Administrators Medical Billing Teams Legal Assistants Data Entry Professionals Office Managers How it works 1. Upload via Web Form: The process starts when a user uploads a fax (as a PDF file) through a simple, secure web form generated by n8n. 2. AI Document Analysis: The PDF is sent directly to Google Gemini's advanced multimodal model, which reads the entire document—including text, tables, and form fields. It extracts all relevant information based on a detailed prompt. 3. AI Data Structuring: The raw extracted text is then passed to a second AI step. This step cleans the information and strictly structures it into a predictable JSON format (e.g., Patient ID, Name, DOB, etc.). 4. Save to Google Sheets: The final, structured data is automatically appended as a new, clean row in your designated Google Sheet, creating an organized and usable dataset from the unstructured fax. Key Requirements to Use This Template 1. n8n Instance & Required Nodes: An active n8n account (Cloud or self-hosted). This workflow uses the official n8n LangChain integration (@n8n/n8n-nodes-langchain). If you are using a self-hosted version of n8n, please ensure this package is installed. 2. Google Accounts: Google Drive Account: For temporarily storing the uploaded file. Google Gemini AI Account: A Google Cloud account with the Vertex AI API (for Gemini models) enabled and an associated API Key. Google Sheets Account: A pre-made Google Sheet with columns that match the data you want to extract. Customer Setup Guide: Here is a detailed, step-by-step guide to help you configure and run this workflow. 1. Before You Begin: Prerequisites Please ensure you have the following ready: The FAX-Content-Extraction.json file we provided. Active accounts for n8n, Google Drive, Google Cloud (for Gemini AI), and Google Sheets. A Google Sheet created with header columns that match the data you want to extract (e.g., Patient ID, Patient Name, Date of Birth, etc.). 2. Step-by-Step Configuration Step 1: Import the Workflow Open your n8n canvas. Click "Import from File" and select the FAX-Content-Extraction.json file. The workflow will appear on your canvas. Step 2: Set Up the Form Trigger The workflow starts with the "On form submission" node. Click on this node. In the settings panel, you will see a "Form URL". Copy this URL. This is the link to the web form where you will upload your fax files. Step 3: Configure the Google Drive Node Click on the "Upload file" (Google Drive) node. Credentials: Select your Google Drive account from the "Credentials" dropdown or click "Create New" to connect your account. Folder ID: In the "Folder ID" field, choose the specific Google Drive folder where you want the uploaded faxes to be saved. Step 4: Configure the Google Gemini AI Nodes (Very Important) This workflow uses AI in two places, and both need to be connected. First AI Call (PDF Reading): Click on the "Call Gemini 2.0 Flash with PDF Capabilities" (HTTP Request) node. Under "Authentication", make sure "Predefined Credential Type" is selected. For "Credential Type", choose "Google Palm API". In the "Credentials" dropdown, select your Google Gemini API key or click "Create New" to add it. Second AI Call (Data Structuring): Click on the "Google Gemini Chat Model" node (it's connected below the "Basic LLM Chain" node). In the "Credentials" dropdown, select the same Google Gemini API key you used before. Step 5: (Optional) Customize What Data is Extracted You have full control over what information the AI looks for. To change the extraction rules: Click on the "Define Prompt" node. You can edit the text in the "Value" field to tell the AI what to look for (e.g., "Extract only the patient's name and medication list"). To change the final output columns: Click on the "Basic LLM Chain" node. In the "Text" field, you can edit the JSON schema to add, remove, or rename the fields you want in your final output. The keys here MUST match the column headers in your Google Sheet. Step 6: Configure the Final Google Sheets Node Click on the "Append row in sheet" node. Credentials: Select your Google Sheets account from the "Credentials" dropdown. Document ID: Select your target spreadsheet from the "Document" dropdown list. Sheet Name: Select the specific sheet within that document. Columns: Ensure that the fields listed here match the columns in your sheet and the schema from the "Basic LLM Chain" node. 4. Running the Workflow Save and Activate: Click "Save" and then toggle the workflow to "Active". Open the Form: Open the Form URL you copied in Step 2 in a new browser tab. Upload a File: Upload a sample fax PDF and submit the form. Check Your Sheet: After a minute, a new row with the extracted data should appear in your Google Sheet. Connect with us Website: https://www.intuz.com/services Email: getstarted@intuz.com LinkedIn: https://www.linkedin.com/company/intuz Get Started: https://n8n.partnerlinks.io/intuz For Custom Worflow Automation Click here- Get Started

How it works Multi-modal AI Image Generator powered by Google's Nano Banana (Gemini 2.5 Flash Image) - the latest state-of-the-art image generation model Accepts text, images, voice messages, and PDFs via Telegram for maximum flexibility Uses OpenAI GPT models for conversation and image analysis, then Nano Banana for stunning image generation Features conversation memory for iterative image modifications ("make it darker", "change to blue") Processes different input types: analyzes uploaded images, transcribes voice messages, extracts PDF text All inputs are converted to optimized prompts specifically tuned for Nano Banana's capabilities Set up steps Create Telegram bot via @BotFather and get API token Set up Google Gemini API key from Google AI Studio for Nano Banana image generation (~$0.04/image) Configure OpenAI API key for GPT models (conversation, image analysis, voice transcription) Import workflow and configure all three API credentials in n8n Update bot tokens in HTTP request nodes for file downloads Test with text prompts, image uploads, voice messages, and PDF documents

Cash Reconciliation with AI This template automates daily cash reconciliation by comparing your open invoices against bank statement transactions. Instead of manually scanning statements line by line, the workflow uses AI to: Match transactions to invoices and assign confidence scores Flag unapplied or review-needed payments Produce a reconciliation table with clear metrics (match %, unmatched count, etc.) The end result: faster cash application, fewer errors, and better visibility into your cash flow. Good to know Each AI transaction match call will consume credits from your OpenAI account. Check OpenAI pricing for costs. OCR is used to extract data from PDF bank statements, so you’ll need a Mistral OCR API key. This workflow assumes invoices are stored in an Excel or CSV file. You may need to tweak column names to match your file headers. How it works Import files:The workflow pulls your invoice file (Excel/CSV) and daily bank statement (from OneDrive, Google Drive, or local storage). Extract and normalize data: OCR is applied to bank statements if needed. Both data sources are cleaned and aligned into comparable formats. AI matching: The AI agent compares statement transactions against invoice records, assigns a confidence score, and flags items that require manual review. Reconciliation output:A ready-made table shows matched invoices (with amounts and confidence), unmatched items, and summary stats. How to use Start with the manual trigger node to test the flow. Once validated, replace it with a schedule trigger to run daily. Adjust thresholds (like date tolerances or amount variances) in the code nodes to fit your business rules. Review the reconciliation table each day most of the work is automated, you just handle exceptions. Requirements OpenAI API key Mistral OCR API key (for PDF bank statements) Microsoft OneDrive API key and Microsoft Excel API key Access to your invoice file (Excel/CSV) and daily bank statement source Setup steps Connect accounts: Enter your API keys (OpenAI, Mistral OCR, OneDrive, Excel). Configure input nodes: Point the Excel/CSV node to your invoice file. Connect the Get Bank Statement node to your statement storage. Configure AI agent: Add your OpenAI API credentials to the AI node. Customize if needed Update column mappings if your file uses different headers. Adjust matching thresholds and tolerance logic.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Multi Platform Content Generator from YouTube using AI & RSS This workflow automates content generation by monitoring YouTube channels, extracting transcripts via AI, and creating platform-optimized content for LinkedIn, X/Twitter, Threads, and Instagram. Ideal for creators, marketers, and social media managers aiming to scale content production with minimal effort. ✨ Key Features 🔔 Automated YouTube Monitoring** via RSS feed 🧠 AI-Powered Transcript Extraction** using Supadata API ✍️ Multi-Platform Content Generation** with OpenRouter AI 🎯 Platform Optimization** based on tone and character limits 📬 Telegram Notification** for easy preview 📊 Centralized Data Management via Google Sheets** > 🗂️ All video data, summaries, and generated content are tracked and stored in a single, centralized Google Sheets template > This ensures full visibility, easy access, and smooth collaboration across your team. ⚙️ Workflow Components 1. 🧭 Channel Monitoring Schedule Trigger**: Initiates workflow periodically Google Sheets (Read)**: Pulls YouTube channel URLs HTTP Request + HTML Parser**: Extracts channel IDs from URLs RSS Reader**: Fetches latest video metadata 2. 🧾 Content Processing Supadata API**: Extracts transcript from YouTube video OpenRouter AI**: Summarizes transcript + generates content per platform Conditional Check**: Prevents duplicate content by checking existing records 3. 📤 Multi-Platform Output LinkedIn**: Story-driven format (≤ 1300 characters) X/Twitter**: Short, punchy copy (≤ 280 characters) Threads**: Friendly, conversational Instagram**: Short captions for visual posts 4. 🗃️ Data Management Google Sheets (Write)**: Stores video metadata + generated posts Telegram Bot**: Sends content preview ID Tracking**: Avoids reprocessing using video ID 🔐 Required Credentials Google Sheets OAuth2** Supadata API** OpenRouter API** Telegram Bot Token & Chat ID** 🎁 Benefits ⌛ Save Time**: Automates transcript + content generation 🔊 Consistent Tone**: Adjust AI prompts for brand voice 📡 Multi-Platform Ready**: One video → multiple formats 📂 Centralized Logs via Google Sheets**: Easily track, audit, and collaborate 🚀 Scalable**: Handle many channels with ease