Workflow Templates

🧾 Summary This workflow monitors Kubernetes pod CPU usage using Prometheus, and sends real-time Slack alerts when CPU consumption crosses a threshold (e.g., 0.8 cores). It groups pods by application name to reduce noise and improve clarity, making it ideal for observability across multi-pod deployments like Argo CD, Loki, Promtail, applications etc. 👥 Who’s it for Designed for DevOps and SRE teams and platform teams, this workflow is 100% no-code, plug-and-play, and can be easily extended to support memory, disk, or network spikes. It eliminates the need for Alertmanager by routing critical alerts directly into Slack using native n8n nodes. ⚙️ What it does This n8n workflow polls Prometheus every 5 minutes ⏱️, checks if any pod's CPU usage crosses a defined threshold (e.g., 0.8 cores) 🚨, groups them by app 🧩, and sends structured alerts to a Slack channel 💬. 🛠️ How to set up 🔗 Set your Prometheus URL with required metrics (container_cpu_usage_seconds_total, kube_pod_container_resource_limits) 🔐 Add your Slack bot token with chat:write scope 🧩 Import the workflow, customize: Threshold (e.g., 0.8 cores) Slack channel Cron schedule 📋 Requirements A working Prometheus stack with kube-state-metrics Slack bot credentials n8n instance (self-hosted or cloud) 🧑‍💻 How to customize 🧠 Adjust threshold values or query interval 📈 Add memory/disk/network usage metrics 💡 This is a plug-and-play Kubernetes alerting template for real-time observability. 🏷️ Tags: Prometheus, Slack, Kubernetes, Alert, n8n, DevOps, Observability, CPU Spike, Monitoring Prometheus Spike Alert to Slack

This N8N template makes it easy to extract key YouTube video data - including title, view count, like count, comment count, and many more - and save it directly into a connected Google Sheet. Use cases are many: Whether you're YouTubers, content strategists, growth marketers, and automation engineers, this tool gives you fast, structured access to video-level insights in seconds. How It Works The workflow begins when you click Execute Workflow or Test Workflow manually in N8N. It reads the list of video URLs in the connected Google Sheet. Only the URLs marked with the Ready status will be processed. The tool loops through each video and prepares the necessary data for the YouTube API call later. For each available URL, the tool extracts the video ID and sends a request to the YouTube API to fetch key metrics. The response is checked: If successful: the video’s statistics are written back to the corresponding row in the Google Sheet and the row's status is marked as Finished. If unsuccessful: the row's status is updated to Error for later review. How To Use Download the workflow package. Import the workflow package into your N8N interface. Duplicate the YouTube - Get Video Statistics Google Sheet template into your Google Sheets account. Set up Google Cloud Console credentials in the following nodes in N8N, ensuring enabled access and suitable rights to Google Sheets and YouTube services: For Google Sheets access, ensure each node is properly connected to the correct tab in your connected Google Sheet template: Node Google Sheets - Get Video URLs → connected to Tab Video URLs; Node Google Sheets - Update Data → connected to Tab Video URLs; Node Google Sheets - Update Data - Error → connected to Tab Video URLs. For YouTube access, set up a GET method to connect to YouTube API in the following node: Node HTTP - Find Video Data. In your connected Google Sheet, enter the video URLs that you want to crawl and set the rows' status to Ready. Run the workflow by clicking Execute Workflow or Test Workflow in N8N. View the results in your connected Google Sheet: Successful fetches will update the rows' status in Column A in the Video URLs tab to Finished and the video metrics will populate. If the call fails, the rows' status in Column A in the tab will be marked as Error. Requirements Basic setup in Google Cloud Console (OAuth or API Key method enabled) with enabled access to YouTube and Google Sheets. How To Customize By default, the workflow is manually triggered in N8N. However, you can automate the process by adding a Google Sheets trigger that monitors new entries automatically. If you want to fetch additional video fields or analytics (like tags, category ID, etc.), you can expand the HTTP - Find Video Data node to include those. Need Help? Join our community on different platforms for support, inspiration and tips from others. Website: https://www.agentcircle.ai/ Etsy: https://www.etsy.com/shop/AgentCircle Gumroad: http://agentcircle.gumroad.com/ Discord Global: https://discord.gg/d8SkCzKwnP FB Page Global: https://www.facebook.com/agentcircle/ FB Group Global: https://www.facebook.com/groups/aiagentcircle/ X: https://x.com/agent_circle YouTube: https://www.youtube.com/@agentcircle LinkedIn: https://www.linkedin.com/company/agentcircle

Automatically Send Square Summary Report for Yesterday's Sales via Microsoft Outlook What It Does This workflow automatically connects to the Square API and generates a daily sales summary report for all your Square locations. The report matches the figures displayed in Square Dashboard > Reports > Sales Summary. It's designed to run daily and pull the previous day's sales into a CSV file, which is then sent to a manager/finance team for analysis. This workflow builds on my previous template, which allows users to automatically pull data from the Square API into n8n for processing. (See here: https://n8n.io/workflows/6358) Prerequisites To use this workflow, you'll need: A Square API credential (configured as a Header Auth credential) A Microsoft Outlook credential How to Set Up Square Credentials: Go to Credentials > Create New Choose Header Auth Set the Name to Authorization Set the Value to your Square Access Token (e.g., Bearer <your-api-key>) How It Works Trigger: The workflow runs every day at 4:00 AM Fetch Locations: An HTTP request retrieves all Square locations linked to your account Fetch Orders: For each location, an HTTP request pulls completed orders for the specified report_date Filter Empty Locations: Locations with no sales are ignored Aggregate Sales Data: A Code node processes the order data and produces a summary identical to Square’s built-in Sales Summary report Create CSV File: A CSV file is created containing the relevant data Send Email: An email is sent to the chosen third party Example Use Cases Automatically send Square sales data to management to improve the quality of planning and scheduling decisions Automatically send data to an external third party, such as a landlord or agent, who is paid via commission Automatically send data to a bookkeeper for entry into QuickBooks How to Use Configure both HTTP Request nodes to use your Square API credential Set the workflow to Active so it runs automatically Enter the email address of the person you want to send the report to and update the message body If you want to remove the n8n attribution, you can do so in the last node Customization Options Add pagination to handle locations with more than 1,000 orders per day Instead of a daily summary, you can modify this workflow to produce a weekly summary once a week Why It's Useful This workflow saves time, reduces manual report pulling from Square, and enables smarter automation around sales data — whether for operations, finance, or performance monitoring.

What does the workflow do? This workflow is primarily designed to generate animated illustrations for content creators and social media professionals with Midjourney (unoffcial) and Kling (unofficial) API served by PiAPI. PiAPI is an API platform which provides professional API service. With service provided by PiAPI, users could generate a fantastic animated artwork simply using workflow on n8n without complex settings among various AI models. What is animated illustration? An animated illustration is a digitally enhanced artwork that combines traditional illustration styles with subtle, purposeful motion to enrich storytelling while preserving its original artistic essence. Who is this workflow for? Social Media Content Creators: Produces animated illustrations for social media posts. Digital Marketers: Generates marketing materials with motion graphics. Independent Content Producers: Creates animated content without specialized animation skills. Step-by-step Setting Instructions To simplify workflow settings, usually users just need to change basic prompt of the image and the motion of the final video following the instrution below: Sign in your PiAPI account and get your X-API-Key. Fill in your X-API-Key of PiAPI account in Midjourney and Kling nodes. Enter your desired image prompt in the Prompt node. Enter the motion prompt in Kling Video Generator node. For more complex or customization settings, users could also add more nodes to get more output images and generate more videos. Also, they could change the target image to gain a better result. As for recommendation, users could change the video models for which we would recommend live-wallpaper LoRA of Wanx. Users could check API doc to see more use cases of video models and image models for best practice. Use Case Input Prompt A gentle girl and a fluffy rabbit explore a sunlit forest together, playing by a sparkling stream. Butterflies flutter around them as golden sunlight filters through green leaves. Warm and peaceful atmosphere, 4K nature documentary style. --s 500 --sref 4028286908 --niji 6 Output Video When there is troubleshooting Check if the X-API-Key has been filled in nodes needed. Check your task status in Task History in PiAPI to get more details about task status. More Generation Case for Reference

Water Reminder Workflow This workflow demonstrates how to use n8n and Slack to build an intelligent water drinking reminder system, combined with Google Sheets for data recording and OpenAI for generating personalized reminder messages. Google Sheet Template The iOS shortcut template: The result in iOS health: The template demo in Youtube Key Features Scheduled Reminders: Automatically sends water reminders at random times every hour. Intelligent Scheduling: Delays the next reminder if you've recently had water. AI-Generated Messages: Uses OpenAI to generate friendly and non-repetitive reminder messages. Data Tracking: Records daily water intake and calculates percentage of goal achievement. Quick Response: Easily record water intake through Slack buttons. iOS Integration: Provides iOS shortcut links to sync data with the Health app. Pre-Configuration Requirements To use this workflow, you need to set up the following: Google Sheets: Create a Google spreadsheet with log and setting sheets The log sheet should include date, time, and value columns The setting sheet is used to store daily water intake goals Slack: Create a Slack app and obtain an API token Configure permissions for interactive buttons OpenAI: Obtain an OpenAI API key iOS Shortcut (optional): Create an iOS shortcut named darrell_water for recording health data Node Configurations 1. Scheduled Triggers and Data Collection 1.1. Schedule Trigger Purpose**: Triggers water reminders on schedule Configuration**: Cron Expression: 0 {{ Math.floor(Math.random() * 11) }} 8-23 * * * Triggers at a random minute every hour, only between 8 AM and 11 PM 1.2. Google Sheets - Get Target Purpose**: Retrieves daily water intake goal Configuration**: Document ID: Your Google spreadsheet ID Sheet Name: setting 1.3. Google Sheets - Get Log Purpose**: Retrieves today's water intake records Configuration**: Document ID: Your Google spreadsheet ID Sheet Name: log Filter Condition: date equals today's date {{ $now.format('yyyy-MM-dd') }} 1.4. Summarize Purpose**: Calculates total water intake for today Configuration**: Fields to Summarize: value (sum) 1.5. Limit Purpose**: Gets the most recent water intake record Configuration**: Keep: Last items 2. Intelligent Reminder Logic 2.1. Combine Data Purpose**: Merges target and actual water intake data Configuration**: Combine By: Combine by position Number of Inputs: 3 2.2. If Purpose**: Checks if water was consumed recently Configuration**: Condition: {{ DateTime.fromISO($json.date+"T"+$json.time).format('yyyy-MM-dd HH:mm:ss') }} is after {{ $now.minus(30, "minutes") }} 2.3. Wait Purpose**: Randomly delays the reminder if water was consumed recently Configuration**: Wait Time: {{ Math.floor(Math.random() * 1) + 1 }} minutes 3. AI Message Generation and Sending 3.1. OpenAI Purpose**: Generates personalized water reminder messages Configuration**: Model: gpt-4o-mini Messages: System prompt: Requests responses in Traditional Chinese and in JSON format User prompt: Includes information about last water time, current time, goal, and progress Temperature: 1 3.2. Slack Send Drink Notification Purpose**: Sends water reminders to Slack channel Configuration**: Channel: Your Slack channel ID Message Type: Block Block UI: Contains AI-generated reminder message and water amount buttons (100ml, 150ml, 200ml, 250ml, 300ml) 4. User Interaction and Data Recording 4.1. Slack Drink Webhook Purpose**: Receives user interactions when water buttons are clicked Configuration**: HTTP Method: POST Path: slack-water-webhook 4.2. Slack Action Payload Purpose**: Parses Slack interaction data Configuration**: Mode: Raw JSON Output: {{ $json.body.payload }} 4.3. Slack Action Drink Data Purpose**: Extracts water amount and message information Configuration**: Assignments: value: {{ $json.actions[0].value }} message_text: {{ $json.message.text }} shortcut_url: shortcuts://run-shortcut?name=darrell_water&input= shortcut_url_data: JSON containing water amount and time message_ts: {{ $json.container.message_ts }} 4.4. Google Sheets Purpose**: Records water intake data to spreadsheet Configuration**: Operation: Append Document ID: Your Google spreadsheet ID Sheet Name: log Column Mapping: date: {{ $now.format('yyyy-MM-dd') }} time: {{ $now.format('HH:mm:ss') }} value: {{ $json.value }} 4.5. Send to Slack with Confirm Purpose**: Sends confirmation message and provides iOS shortcut link Configuration**: Channel: Your Slack channel ID Message Type: Block Block UI: Contains confirmation message and iOS Health app button Reply Settings: Reply to the thread of the original message Author Information This workflow was created by darrell_tw_, an engineer focused on AI and Automation. Contact: X Threads Instagram Website

Product Price Monitor with Pushover and Baserow ⚠️ COMMUNITY TEMPLATE DISCLAIMER: This is a community-contributed template that uses ScrapeGraphAI (a community node). Please ensure you have the ScrapeGraphAI community node installed in your n8n instance before using this template. This workflow automatically scrapes multiple e-commerce sites for selected products, analyzes weekly pricing trends, stores historical data in Baserow, and sends an instant Pushover notification when significant price changes occur. It is ideal for retailers who need to track seasonal fluctuations and optimize inventory or pricing strategies. Pre-conditions/Requirements Prerequisites An active n8n instance (self-hosted or n8n.cloud) ScrapeGraphAI community node installed At least one publicly accessible webhook URL (for on-demand runs) A Baserow database with a table prepared for product data Pushover account and registered application Required Credentials ScrapeGraphAI API Key** – Enables web-scraping capabilities Baserow: Personal API Token** – Allows read/write access to your table Pushover: User Key & API Token** – Sends mobile/desktop push notifications (Optional) HTTP Basic Token or API Keys for any private e-commerce endpoints you plan to monitor Baserow Table Specification | Field Name | Type | Description | |------------|-----------|--------------------------| | Product ID | Number | Internal or SKU | | Name | Text | Product title | | URL | URL | Product page | | Price | Number | Current price (float) | | Currency | Single select (USD, EUR, etc.) | | Last Seen | Date/Time | Last price check | | Trend | Number | 7-day % change | How it works This workflow automatically scrapes multiple e-commerce sites for selected products, analyzes weekly pricing trends, stores historical data in Baserow, and sends an instant Pushover notification when significant price changes occur. It is ideal for retailers who need to track seasonal fluctuations and optimize inventory or pricing strategies. Key Steps: Webhook Trigger**: Manually or externally trigger the weekly price-check run. Set Node**: Define an array of product URLs and metadata. Split In Batches**: Process products one at a time to avoid rate limits. ScrapeGraphAI Node**: Extract current price, title, and availability from each URL. If Node**: Determine if price has changed > ±5 % since last entry. HTTP Request (Trend API)**: Retrieve seasonal trend scores (optional). Merge Node**: Combine scrape data with trend analysis. Baserow Nodes**: Upsert latest record and fetch historical data for comparison. Pushover Node**: Send alert when significant price movement detected. Sticky Notes**: Documentation and inline comments for maintainability. Set up steps Setup Time: 15-25 minutes Install Community Node: In n8n, go to “Settings → Community Nodes” and install ScrapeGraphAI. Create Baserow Table: Match the field structure shown above. Obtain Credentials: ScrapeGraphAI API key from your dashboard Baserow personal token (/account/settings) Pushover user key & API token Clone Workflow: Import this template into n8n. Configure Credentials in Nodes: Open each ScrapeGraphAI, Baserow, and Pushover node and select/enter the appropriate credential. Add Product URLs: Open the first Set node and replace the example array with your actual product list. Adjust Thresholds: In the If node, change the 5 value if you want a higher/lower alert threshold. Test Run: Execute the workflow manually; verify Baserow rows and the Pushover notification. Schedule: Add a Cron trigger or external scheduler to run weekly. Node Descriptions Core Workflow Nodes: Webhook** – Entry point for manual or API-based triggers. Set** – Holds the array of product URLs and meta fields. SplitInBatches** – Iterates through each product to prevent request spikes. ScrapeGraphAI** – Scrapes price, title, and currency from product pages. If** – Compares new price vs. previous price in Baserow. HTTP Request** – Calls a trend API (e.g., Google Trends) to get seasonal score. Merge** – Combines scraping results with trend data. Baserow (Upsert & Read)** – Writes fresh data and fetches historical price for comparison. Pushover** – Sends formatted push notification with price delta. StickyNote** – Documents purpose and hints within the workflow. Data Flow: Webhook → Set → SplitInBatches → ScrapeGraphAI ScrapeGraphAI → If True branch → HTTP Request → Merge → Baserow Upsert → Pushover False branch → Baserow Upsert Customization Examples Change Notification Channel to Slack // Replace the Pushover node with Slack { "channel": "#pricing-alerts", "text": 🚨 ${$json["Name"]} changed by ${$json["delta"]}% – now ${$json["Price"]} ${$json["Currency"]} } Additional Data Enrichment (Stock Status) // Add to ScrapeGraphAI's selector map { "stock": { "selector": ".availability span", "type": "text" } } Data Output Format The workflow outputs structured JSON data: { "ProductID": 12345, "Name": "Winter Jacket", "URL": "https://shop.example.com/winter-jacket", "Price": 79.99, "Currency": "USD", "LastSeen": "2024-11-20T10:34:18.000Z", "Trend": 12, "delta": -7.5 } Troubleshooting Common Issues Empty scrape result – Check if the product page changed its HTML structure; update CSS selectors in ScrapeGraphAI. Baserow “Row not found” errors – Ensure Product ID or another unique field is set as the primary key for upsert. Performance Tips Limit batch size to 5-10 URLs to avoid IP blocking. Use n8n’s built-in proxy settings if scraping sites with geo-restrictions. Pro Tips: Store historical JSON responses in a separate Baserow table for deeper analytics. Standardize currency symbols to avoid false change detections. Couple this workflow with an n8n Dashboard to visualize price trends in real-time.

Description This workflow is an n8n-based automation that allows users to download TikTok/Reels videos without watermarks simply by sending the video link through a Telegram Bot. It uses a Telegram Trigger to receive the link from the user, then makes an HTTP request to a third-party API (tiktokio.com) to process and retrieve the download link. The workflow filters the results to find the Download without watermark link, downloads the video in MP4 format, and sends it back to the user directly in their Telegram chat. Key features: Supports the best available video quality (bestvideo+bestaudio). Automatically removes watermarks. Instant response directly in Telegram chat. Fully automated — no manual downloads required. How It Works Telegram Trigger The user sends a TikTok or Reels link to the Telegram bot. The workflow captures and stores the link for processing. HTTP Request – MediaDL API The link is sent via POST method to https://mediadl.app/api/download. The API processes the link and returns video file data. Wait Delay The workflow waits a few seconds to ensure the API response is fully ready. Edit Fields Extracts the video file URL from the API response. Additional Wait Delay Adds a short pause to avoid connection errors during the download process. HTTP Request – Proxy Download Downloads the MP4 video file directly from the filtered URL. Send Video via Telegram The downloaded video is sent back to the user in their Telegram chat. How to Set Up Create & Configure a Telegram Bot Open Telegram and search for BotFather. Send /newbot → choose a name & username for your bot. Copy the Bot Token provided — you’ll need it in n8n. Prepare Your n8n Environment Log in to your n8n instance (self-hosted or n8n Cloud). Go to Credentials → create new Telegram API credentials using your Bot Token. Import the Workflow In n8n, click Import and select the PROJECT_DOWNLOAD_TIKTOK_REELS.json file. Configure the Telegram Nodes In the Telegram Trigger and Send Video nodes, connect your Telegram API credentials. Configure the HTTP Request Nodes Ensure the Download2 and HTTP Request nodes have the correct URL and headers (pre-configured for mediadl.app). Make sure the responseFormat is set to file in the final download node. Activate the Workflow Toggle Activate in the top right corner of n8n. Test by sending a TikTok or Reels link to your bot — you should receive the no-watermark video in return.

Lead Scoring Pipeline with Mattermost and Trello This workflow automatically enriches incoming form-based leads, calculates a lead-score from multiple data points, and then routes high-value prospects to a Mattermost alert channel while adding all leads to Trello for further handling. It centralizes lead intelligence and streamlines sales team triage—no manual spreadsheet work required. Pre-conditions/Requirements Prerequisites n8n instance (self-hosted or n8n cloud) ScrapeGraphAI community node installed Active Trello and Mattermost workspaces Lead-capture form or webhook that delivers JSON payloads Required Credentials Trello API Key & Token** – Access to the board/list where cards will be created Mattermost Access Token** – Permission to post messages in the target channel (Optional) Clearbit / Apollo / 3rd-party enrichment keys** – If you replace the sample enrichment HTTP requests Specific Setup Requirements | Variable | Purpose | Example Value | |-------------------------|-------------------------------------------|------------------------| | MM_CHANNEL_ID | Mattermost channel to post high-score leads | leads-alerts | | TRELLO_BOARD_ID | Board where new cards are added | 62f1d… | | TRELLO_LIST_ID_HOT | Trello list for hot leads | Hot Deals | | TRELLO_LIST_ID_BACKLOG| Trello list for all other leads | New Leads | | LEAD_SCORE_THRESHOLD | Score above which a lead is considered hot| 70 | How it works This workflow grabs new leads at a defined interval, enriches each lead with external data, computes a custom score, and routes the lead: high-scorers trigger a Mattermost alert and are placed in a “Hot Deals” list, while the rest are stored in a “Backlog” list on Trello. All actions are fully automated and run unattended once configured. Key Steps: Schedule Trigger**: Runs every 15 minutes to poll for new form submissions. HTTP Request – Fetch Leads**: Retrieves the latest unprocessed leads from your form backend or CRM API. Split In Batches**: Processes leads 20 at a time to respect API rate limits. HTTP Request – Enrich Lead**: Calls external enrichment (e.g., Clearbit) to append company and person data. Code – Calculate Score**: JavaScript that applies weightings to enriched attributes and outputs a numeric score. IF – Score Threshold**: Branches flow based on LEAD_SCORE_THRESHOLD. Mattermost Node**: Sends a rich-text message with lead details for high-score prospects. Trello Node (Hot List)**: Creates a Trello card in the “Hot Deals” list for high-value leads. Trello Node (Backlog)**: Creates a Trello card in the “New Leads” list for everyone else. Merge & Flag Processed**: Marks leads as processed to avoid re-processing in future runs. Set up steps Setup Time: 10–15 minutes Import the Workflow: Download the JSON template and import it into n8n. Create / Select Credentials: Add your Trello API key & token under Trello API credentials. Add your Mattermost personal access token under Mattermost API credentials. Configure Environment Variables: Set MM_CHANNEL_ID, TRELLO_BOARD_ID, TRELLO_LIST_ID_HOT, TRELLO_LIST_ID_BACKLOG, and LEAD_SCORE_THRESHOLD in n8n → Settings → Environment. Form Backend Endpoint: Update the first HTTP Request node with the correct URL and authentication for your form or CRM. (Optional) Enrichment Provider: Replace the sample enrichment HTTP Request with your chosen provider’s endpoint and credentials. Test Run: Execute the workflow manually with a sample payload to ensure Trello cards and Mattermost messages are produced. Activate: Enable the workflow; it will now run on the defined schedule. Node Descriptions Core Workflow Nodes: Schedule Trigger** – Triggers workflow every 15 minutes. HTTP Request (Fetch Leads)** – Pulls unprocessed leads. SplitInBatches** – Limits processing to 20 leads per batch. HTTP Request (Enrich Lead)** – Adds firmographic & technographic data. Code (Calculate Score)** – JavaScript scoring algorithm; outputs score field. IF (Score ≥ Threshold)** – Determines routing path. Mattermost** – Sends formatted message with lead summary & score. Trello (Create Card)** – Adds lead as a card to the appropriate list. Merge (Flag Processed)** – Updates source system to mark lead as processed. Data Flow: Schedule Trigger → HTTP Request (Fetch Leads) → SplitInBatches → HTTP Request (Enrich Lead) → Code (Calculate Score) → IF IF (Yes) → Mattermost → Trello (Hot List) IF (No) → Trello (Backlog) Both branches → Merge (Flag Processed) Customization Examples Adjust Scoring Weights // Code node: adjust weights to change scoring logic const weights = { industry: 15, companySize: 25, jobTitle: 20, intentSignals: 40 }; Dynamic Trello List Mapping // Use a Lookup table instead of IF node const mapping = { hot: 'TRELLO_LIST_ID_HOT', cold: 'TRELLO_LIST_ID_BACKLOG' }; items[0].json.listId = mapping[items[0].json.segment]; return items; Data Output Format The workflow outputs structured JSON data: { "leadId": "12345", "email": "jane.doe@example.com", "score": 82, "priority": "hot", "trelloCardUrl": "https://trello.com/c/abc123", "mattermostPostId": "78yzk9n8ppgkkp" } Troubleshooting Common Issues Trello authentication fails – Ensure the token has write access and that the API key & token pair belong to the same Trello account. Mattermost message not sent – Confirm the token can post in the target channel and that MM_CHANNEL_ID is correct. Performance Tips Batch leads in groups of 20–50 to avoid enrichment API rate-limit errors. Cache enrichment responses for repeat domains to reduce API calls. Pro Tips: Add a second IF node to send ultra-high (>90) scores directly to an account executive via email. Store raw enrichment responses in a database for future analytics. Use n8n’s built-in Execution Data Save to debug edge-cases without rerunning external API calls.

Description This workflow builds a Tamil voice AI assistant for real estate inquiries. It handles incoming calls or messages, converts speech to text, generates AI responses, converts them back to speech, and logs lead data into Google Sheets. What this template demonstrates Voice-based AI assistant using STT and TTS Conversation handling with memory AI response generation with structured prompts Lead capture and logging Escalation to human agents Use cases Real estate enquiry automation Voice-based customer support Lead qualification systems AI call assistant for small businesses How it works • Receives input via webhook • Converts audio to text using STT • Detects intent and escalation conditions • Generates response using AI • Converts response to speech and returns it • Logs lead data into Google Sheets How to use Deploy the workflow Configure webhook endpoint Connect OpenAI, Sarvam STT/TTS, and Google Sheets Send audio or text requests to the webhook Requirements OpenAI API access Sarvam STT and TTS API access Google Sheets account Public webhook endpoint Customising this workflow Modify AI prompt for different industries Add CRM integration instead of Google Sheets Adjust escalation rules Support multiple languages Use this Voice Call HTML File For Testing, Download it and test the agent by live conversation. Good to know Handles both audio and text input Includes fallback for failed speech recognition Maintains conversation history Supports real-time response generation Who this is for Automation engineers Real estate agencies AI chatbot builders Businesses needing voice assistants

Important: This workflow uses the Autype and SerpAPI Official community nodes and requires a self-hosted n8n instance. Submit a simple form with your product name, industry, and description. The workflow automatically researches your market via Google Trends and Google Search (SerpAPI), conducts deep analysis with Perplexity AI (via OpenRouter), writes a structured report with Anthropic Claude (via OpenRouter), and renders a professionally styled PDF using Autype Extended Markdown. No manual competitor input required -- everything is discovered automatically. Who is this for? Product managers, startup founders, strategists, and consultants who need quick market research reports for investor decks, board meetings, competitive positioning, or strategic planning. Instead of spending hours compiling data from multiple sources, this workflow automates the entire research-to-PDF pipeline from a single form submission. Concrete example: A SaaS startup preparing for a Series A fundraise needs a market research report on the document automation space. They fill in their product name and industry, describe their product, and submit the form. In under two minutes they get a polished PDF with current market trends, auto-discovered competitor comparisons, SWOT analysis, and strategic recommendations -- ready to attach to their pitch deck. What this workflow does When a user submits the form, the workflow sends parallel requests to Google Trends (12-month interest data) and Google Search (competitor discovery) via SerpAPI, and downloads Autype's extended markdown syntax reference. All data is merged and passed to an AI Research Agent powered by Perplexity Sonar Pro (via OpenRouter) for deep market and competitor analysis with real-time web citations. The research output is then handed to an AI Report Writer (Anthropic Claude via OpenRouter) that writes a structured market research report in Autype Extended Markdown. The markdown is rendered to a styled PDF via Autype's Render from Markdown operation, and the final report is saved to Google Drive. How it works Market Research Form -- An n8n Form Trigger collects product name, industry, product description, and report language. Google Trends -- SerpAPI Official node fetches 12 months of search interest data for the industry. Search Competitors -- SerpAPI Google Search automatically discovers competitors and market leaders. Download Markdown Syntax -- Fetches Autype's extended markdown syntax reference so the report writer knows all formatting options. Prepare Research Context -- A Code node merges trends data, competitor search results, and syntax reference into a single context. AI Research Agent -- An AI Agent with OpenRouter (Perplexity Sonar Pro) conducts deep market research: market overview, competitor profiles, trends, and product positioning. Prepare Report Input -- A Code node combines the research output with the markdown syntax reference and form data. AI Report Writer -- An AI Agent (Anthropic Claude via OpenRouter) writes the final report in Autype Extended Markdown. The prompt includes a title page template. Prepare Render Payload -- A Code node cleans the AI output and sets title/filename. Render Report PDF -- Autype renders the extended markdown to a professionally styled PDF with Open Sans font, heading hierarchy (28/22/18pt), automatic page breaks before h1/h2, chart color palette, header with company name and logo, footer with page numbers, and generous spacing. Save Report to Drive -- The PDF is uploaded to Google Drive. Setup Install community nodes via Settings > Community Nodes: n8n-nodes-autype and n8n-nodes-serpapi. Create an Autype API credential with your API key from app.autype.com. See API Keys in Settings. Create a SerpAPI credential with your API key from serpapi.com (free tier: 250 searches/month). Create two OpenRouter API credentials with your key(s) from openrouter.ai. One is used for Perplexity Sonar Pro (research), the other for Anthropic Claude (report writing). You can use the same API key for both. Create a Google Drive OAuth2 credential and connect your Google account. Import this workflow and assign your credentials to each node. Set YOUR_FOLDER_ID in the "Save Report to Drive" node to your target Google Drive folder. Activate the workflow and open the form URL to generate a report. Note: You need a self-hosted n8n instance to use the Community Nodes. Requirements Self-hosted n8n instance (community nodes are not available on n8n Cloud) Autype account with API key (free tier available) n8n-nodes-autype community node installed n8n-nodes-serpapi community node installed (verified) OpenRouter API key (for Perplexity Sonar Pro and Anthropic Claude models) SerpAPI account (free tier: 100 searches/month) Google Drive account with OAuth2 credentials (optional, can replace with other output) How to customize Add more data sources:** Insert additional HTTP Request or SerpAPI nodes before the merge to pull from Google News, Google Scholar, or other engines. Use a different research model:** Swap the OpenRouter Perplexity model for any other OpenRouter model (e.g. Gemini) or replace the sub-node entirely. Use a different report writer:** Swap the Anthropic Claude model for OpenAI, Google Gemini, or any other OpenRouter-compatible model. Customize header/footer:** Edit the defaults JSON in the Render Report PDF node to change the company name, logo URL, or footer text. Customize title page:** Edit the title page template in the AI Report Writer's user prompt to change the logo, layout, or metadata fields. Change report structure:** Edit the system prompt in the AI Report Writer node to add or remove sections, change the tone, or adjust the word count. Customize PDF styling:** Edit the defaults JSON in the Render Report PDF node to change fonts, colors, spacing, and heading styles. See the Autype defaults schema for all options. Generate DOCX instead of PDF:** Change the output format in the Render Report PDF node from PDF to DOCX. Schedule automatic reports:** Add a Schedule Trigger alongside the Form Trigger for recurring market monitoring. Change output destination:** Replace the Google Drive node with Email (SMTP), S3, Slack, or any other n8n output node. Add more languages:** Edit the dropdown options in the Market Research Form node.

Description Who's it for This workflow is designed for developers, entrepreneurs, and startup enthusiasts who want personalized, AI-driven startup idea generation and analysis. Perfect for solo developers seeking side project inspiration, startup accelerators evaluating concepts, or anyone looking to validate business ideas with professional-grade analysis. How it works The workflow uses a three-stage Claude AI agent pipeline to create comprehensive startup analyses. The first agent generates innovative startup ideas based on your technical skills and preferences. The second agent acts as a venture capitalist, critically analyzing market viability, competition, and execution challenges. The third agent performs sentiment analysis and synthesizes a final recommendation with actionable next steps. How to set up Configure Anthropic API credentials for all three Claude AI model nodes Set up Gmail OAuth2 for email delivery Fill out the "My Information" node with your developer profile Update the recipient email address in the Gmail node Test with the manual trigger before enabling daily automation Requirements n8n account Anthropic API account for Claude AI access Gmail account with OAuth2 configured Basic understanding of developer skills and market preferences How to customize the workflow Modify the AI agent prompts to focus on specific industries or business models. Adjust temperature settings for different creativity levels. Add database storage to track idea history. Configure the form trigger for team-wide idea generation or integrate with Slack for automated sharing. Got a good idea? Visit my site https://techpoweredgrowth.com to get help getting to the next level Or reach out to luka.zivkovic@techpoweredgrowth.com

Screen and Score Investment Deals with AI using OpenAI, Gmail, and Telegram Automatically screens incoming deal submissions using AI, scores them against investment criteria, and routes to the right action. Who is this for? VC firms, PE funds, angel investors, or M&A advisors who receive deal flow via email or form submissions. What problem does this solve? Manually reviewing every pitch deck and deal memo is time-consuming. Most deals don't meet investment criteria. This agent screens, scores, and prioritizes deals so your team focuses on the best opportunities. How it works: New Email Received / Deal Submission Webhook - captures deals from email or form Normalize Email/Webhook Data - standardizes fields from either source Build Deal Text - combines email body + attachment info into screening text Has Deal Content? - validates there is enough content to screen Extract Deal Info - OpenAI - AI extracts company, industry, revenue, ask, team, highlights, red flags Score Deal - OpenAI - AI scores on 5 criteria (industry fit, revenue, growth, team, clarity) Is PASS? / Is REVIEW? - routes by verdict (PASS/REVIEW/REJECT) Telegram Alerts - notifies with deal summary and scores Log Deal to Pipeline Sheet - tracks all deals in a pipeline spreadsheet Setup: Add credentials: Gmail, OpenAI, Telegram Bot, Google Sheets Replace YOUR_TELEGRAM_CHAT_ID with your chat ID Create a Google Sheet with columns: received_at, company_name, industry, stage, revenue, ask_amount, overall_score, verdict, one_line_summary, recommendation, key_highlights, red_flags, sender_name, sender_email, source, industry_fit, revenue_stage, growth_trajectory, team_strength, deal_clarity Replace YOUR_GOOGLE_SHEET_ID with your sheet ID Customization: Edit the scoring criteria in the Score Deal OpenAI prompt Adjust score thresholds for PASS/REVIEW/REJECT Add Slack notifications instead of Telegram Add auto-decline email for REJECT deals Connect to a CRM instead of Google Sheets