by Adam GaΕΔcki
How it works: This workflow automates comprehensive SEO reporting by: Extracting keyword rankings and page performance from Google Search Console. Gathering organic reach metrics from Google Analytics. Analyzing internal and external article links. Tracking keyword position changes (gains and losses). Formatting and importing all data into Google Sheets reports. Set up steps: Connect Google Services: Authenticate Google Search Console, Google Analytics, and Google Sheets OAuth2 credentials. Configure Source Sheet: Set up a data source Google Sheet with article URLs to analyze. Set Report Sheet: Create or specify destination Google Sheets for reports. Update Date Ranges: Modify date parameters in GSC and GA nodes for your reporting period. Customize Filters: Adjust keyword filters and row limits based on your needs. Test Individual Sections: Each reporting section (keywords, pages, articles, position changes) can be tested independently. The workflow includes separate flows for: Keyword ranking (top 1000). Page ranking analysis. Organic reach reporting. Internal article link analysis. External article link analysis. Position gain/loss tracking.
by Kshitij Matta
Stop paying for expensive plugins to recover your valuable revenue from abandoned carts on your WooCommerce store How It Works? When a product is added to a user's cart on your store, it fetches the cart contents via webhook & it utilises the code provided in the red sticky note to fetch the required info. It waits for a specified time to allow the user to place an order. It checks if the order has been placed or not. It creates the HTML with dynamic information fetched from previous nodes. It sends the email to the user via configured SMTP credentials. Setup Steps (20 minutes): Set up your WooCommerce Account Credentials in n8n Set up webhook in n8n & WooCommerce Add the provided code in functions.php or as a PHP snippet via a plugin onto your website Customize the coupon code's phrase according to your needs Customize the email's HTML code according to your needs Requirements WooCommerce Store**: With REST API access enabled. SMTP Credentials**: For sending recovery emails. For any queries, you can ping me on X
by Rahul Joshi
π Description This workflow allows users to ask questions about past meetings using their voice. It converts the voice question into text, searches stored meeting notes using Pinecone, and replies with a spoken answer generated by AI. It helps teams quickly recall decisions, tasks, and discussions without reading long meeting notes. π§ π π What This Template Does 1οΈβ£ Receives a voice question through a webhook endpoint. π 2οΈβ£ Converts the audio question into text using speech transcription. π€β‘οΈπ 3οΈβ£ Cleans and prepares the question for searching. β 4οΈβ£ Converts the question into an embedding for semantic search. π 5οΈβ£ Searches relevant meeting notes from Pinecone using the team namespace. π 6οΈβ£ Combines retrieved meeting context into a single readable format. 𧩠7οΈβ£ Uses AI to answer the question strictly from the meeting context. π€ 8οΈβ£ Converts the AIβs text answer into spoken audio. π 9οΈβ£ Sends the audio response back to the user via webhook. π β Key Benefits β Allows hands-free access to meeting information β Saves time searching through meeting notes β Prevents AI hallucinations using RAG β Supports multiple teams using namespaces β Works with voice-based tools and assistants β Improves meeting recall and clarity 𧩠Features Voice-based question input Speech-to-text transcription Semantic search using Pinecone Team-based data isolation Context-aware AI responses Text-to-speech output Webhook-driven architecture π Requirements OpenAI API key for transcription, embeddings, and speech generation Azure OpenAI credentials for chat responses Pinecone API key with a configured index Matching embedding model for ingest and query Webhook client capable of sending audio files π― Target Audience Teams that conduct frequent meetings Managers needing quick decision recall Remote and distributed teams Product, engineering, and operations teams Automation builders using n8n Organizations adopting voice-based workflows
by RenderIO
Who is this for Content creators, YouTubers, and social media managers who want to repurpose long form videos into short clips without doing it manually. Works on self hosted n8n instances. What it does Monitors a Google Drive folder for new videos. When a video appears, the workflow downloads it, extracts the audio, transcribes it using Whisper, and sends the transcript to OpenAI to identify the best highlight moments. Each selected clip is then rendered in three aspect ratios (9:16 for TikTok, 9:16 for Reels, 1:1 for Square) using cloud based FFmpeg through RenderIO. The finished clips are uploaded back to Google Drive and every run is logged to a Google Sheet. How it works Watch Drive Folder polls your source folder every minute and triggers when a new video file is detected. Set Config holds all tunable settings in one place: clip count, folder IDs, sheet IDs, and LLM model. The video is downloaded from Google Drive and uploaded to RenderIO for processing. Extract Audio runs an FFmpeg command to pull the audio track from the video. The audio is sent to Whisper for transcription. Both TXT and SRT transcript files are saved to Google Drive. Pick Clips sends the transcript to OpenAI, which returns timestamped highlight suggestions. Validate Clips checks that all timestamps and durations are valid before rendering. Each clip is rendered in three formats through RenderIO with separate FFmpeg commands for each aspect ratio. All rendered clips are downloaded and uploaded to a dedicated output folder in Google Drive. Append Clip Row logs each clip to a Google Sheet and Append Run Summary records the overall processing stats. Requirements A self hosted or cloud n8n instance (uses a community node) The n8n-nodes-renderio community node installed via Settings > Community Nodes A free RenderIO account and API key from renderio.dev Google Drive and Google Sheets OAuth credentials An OpenAI API key How to set up Install the n8n-nodes-renderio community node from Settings > Community Nodes. Create credentials for Google Drive (OAuth2), Google Sheets (OAuth2), OpenAI, and RenderIO API. Import the workflow and open the Set Config node. Update the outputParentFolderId with the Google Drive folder ID where output folders should be created. Update the sheetId with your Google Sheet document ID. Set sheetTab and sheetRunsTab to the correct sheet tab IDs for clip logging and run summaries. Configure the Watch Drive Folder trigger node to point at your source video folder. Activate the workflow and drop a test video into the folder. How to customize Change clipCount in Set Config to generate more or fewer clips per video. Swap llmModel from gpt-4o-mini to gpt-4o or another model for different clip selection quality. Modify the FFmpeg commands in Build Commands for Clip to adjust resolution, bitrate, add watermarks, or change output formats. Replace Google Drive with S3 or another storage provider if that fits your stack. Add a Slack or Telegram notification node after the summary step to get alerted when processing finishes.
by vinci-king-01
This workflow processes raw meeting recordings or handwritten notes, automatically transcribes and summarizes them, and then distributes the concise summary to all meeting participants via Microsoft Teams while also creating an action-item task in ClickUp. The goal is to save time, keep everyone aligned, and ensure follow-up tasks are tracked in your project management workspace. Pre-conditions/Requirements Prerequisites n8n instance (self-hosted or n8n.cloud) ScrapeGraphAI community node installed Microsoft Teams tenant with permissions to create Incoming Webhooks or use Bot Framework ClickUp workspace and a target List to hold meeting action items Optional: OpenAI or any LLM API account for high-quality summarization Required Credentials Microsoft Teams Webhook URL** β to post summary messages ClickUp Personal Access Token** β to create tasks OpenAI API Key** (optional but recommended) β for AI-powered summarization ScrapeGraphAI API Key** β placeholder key to satisfy the template requirement Specific Setup Requirements | Item | Description | Example | |------|-------------|---------| | Teams Channel Webhook | Create an Incoming Webhook in the desired Teams channel and copy the URL | https://outlook.office.com/webhook/... | | ClickUp List ID | The numeric ID of the list where tasks will be created | 90123456 | | Summarization Model | The LLM model or API you prefer to use | gpt-3.5-turbo | How it works This workflow transcribes or parses meeting content, leverages an LLM to generate a concise summary and action items, then distributes the results to participants in Microsoft Teams and creates a follow-up task in ClickUp. Everything runs in a single automated flow triggered manually or on a schedule. Key Steps: Manual Trigger**: Start the workflow after a meeting ends. Sticky Note**: Provides on-canvas documentation for quick reference. Set Node β Upload Metadata**: Define meeting title, date, and participants. HTTP Request β Transcription**: Send audio/video file to a transcription service (e.g., Azure Speech-to-Text). Wait**: Pause until the transcription is complete. Code β Summarize**: Use OpenAI to summarize the transcript and extract action items. IF Node β Validate Output**: Ensure the summary exists; handle errors otherwise. Merge**: Combine summary with participant list. Microsoft Teams Node**: Send the summary to each participant or channel via webhook. ClickUp Node**: Create a task containing the summary and action items. Set up steps Setup Time: 10-15 minutes Create Teams Webhook: In Microsoft Teams, navigate to the target channel β Manage channel β Connectors β Incoming Webhook β give it a name (e.g., βMeetingBotβ) and copy the generated URL. Generate ClickUp Personal Access Token: ClickUp β Settings β Apps β Generate Token β copy and store it securely. Get ClickUp List ID: Open the list in ClickUp and copy the numeric ID from the URL bar. Optional β Obtain OpenAI API Key: Sign in to OpenAI β API Keys β Create new secret key. Add Credentials in n8n: In n8n, go to Credentials β New β add Microsoft Teams, ClickUp, and OpenAI (Generic HTTP). Import Workflow: Paste the JSON workflow into n8n or use βTemplates β Importβ. Configure Nodes: In the Set Node: update meeting_title, date, and participants array. In HTTP Request: set the transcription service endpoint and authentication. In Code β Summarize: paste your OpenAI key or select credential. In Microsoft Teams Node: select the Teams credential and webhook URL. In ClickUp Node: select ClickUp credential and enter the List ID. Test: Click βExecute Workflowβ on the Manual Trigger node. Verify that a message appears in Teams and a task is created in ClickUp. Node Descriptions Core Workflow Nodes: Manual Trigger** β Initiates the workflow manually or on a schedule. Sticky Note** β Documentation block outlining purpose and credential usage. Set** β Stores meeting metadata and participants list. HTTP Request** β Sends meeting recording to a transcription service and fetches results. Wait** β Holds the workflow until transcription is ready. Code** β Summarizes transcript and extracts action items via OpenAI. IF** β Validates summarization success; branches on failure. Merge** β Combines summary text with participant emails/usernames. Microsoft Teams** β Posts summary to Teams channel or direct messages. ClickUp** β Creates a task containing summary and action items. Data Flow: Manual Trigger β Set β HTTP Request β Wait β Code β IF β Merge β Microsoft Teams Merge β ClickUp Customization Examples Change summarization prompt // Inside the Code node const prompt = ` You are an expert meeting assistant. Summarize the following transcript in under 150 words. List action items in bullet points with owners. Transcript: ${items[0].json.transcript} `; Send summary as a PDF attachment // Add Convert & Save node before Teams // Convert markdown summary to PDF and attach in Teams node Data Output Format The workflow outputs structured JSON data: { "meeting_title": "Q3 Strategy Sync", "date": "2024-05-10", "participants": ["john@corp.com", "jane@corp.com"], "summary": "We reviewed Q3 OKRs, decided to ...", "action_items": [ { "owner": "John", "task": "Prepare budget draft", "due": "2024-05-20" }, { "owner": "Jane", "task": "Compile market research", "due": "2024-05-25" } ], "clickup_task_id": "abcd1234", "teams_message_id": "msg7890" } Troubleshooting Common Issues Teams message not sent β Verify the Incoming Webhook URL and that the Teams node uses the correct credential. ClickUp task missing β Ensure the List ID is correct and the ClickUp token has tasks:write scope. Empty summary β Check that the transcription text is populated and the OpenAI prompt is valid. Performance Tips Compress large audio/video files before sending to the transcription service. Use batching in the Teams node if participant list is >20 to avoid rate limits. Pro Tips: Schedule the workflow to auto-run 5 minutes after recurring meeting end-times. Customize the ClickUp task description template to include embedded links. Add a βSend Emailβ node for participants not on Teams.
by Dmitrij Zykovic
Personal Expense Tracker Bot π° AI-powered Telegram bot for effortless expense tracking. Send receipts, voice messages, or text - the bot automatically extracts and categorizes your expenses. β¨ Key Features πΈ Receipt & Invoice OCR** - Send photos of receipts or PDF invoices, AI extracts expense data automatically π€ Voice Messages** - Speak your expenses naturally, audio is transcribed and processed π¬ Natural Language** - Just type "spent 50 on groceries" or any text format π Multilingual** - Processes documents in any language (EN, DE, PT, etc.) π Smart Statistics** - Get monthly totals, category breakdowns, multi-month comparisons π Private & Secure** - Single-user authorization, only you can access your data β‘ Zero Confirmation** - Expenses are added instantly, no annoying "confirm?" prompts π― How It Works Send expense data via Telegram: Photo of receipt PDF invoice Voice message Text message AI processes automatically: Extracts amount, date, vendor Categorizes expense Stores in organized format Query your expenses: "Show my expenses for November" "How much did I spend on groceries?" "Compare last 3 months" π Expense Categories Groceries, Transportation, Housing, Utilities, Healthcare, Entertainment, Dining Out, Clothing, Education, Subscriptions, Personal Care, Gifts, Travel, Sports, Other π§ Setup Requirements 1. Telegram Bot Create a Telegram bot via @BotFather and get your API token. Configure credentials for nodes: Input, WelcomeMessage, GetAudioFile, GetAttachedFile, GetAttachedPhoto ReplyText, NotAuthorizedMessage, DeleteProcessing 2. OpenRouter API Get API key from OpenRouter for AI processing. Configure credentials for: Gpt4o (main processing) Sonnet45 (expense assistant) 3. Ainoflow API Get API key from Ainoflow for storage and OCR. Configure Bearer credentials for: GetConfig, SaveConfig ExtractFileText, ExtractImageText TranscribeRecording JsonStorageMcp (MCP tool) ποΈ Workflow Architecture | Section | Description | |---------|-------------| | Message Trigger | Receives all Telegram messages | | Bot Privacy | Locks bot to first user, rejects unauthorized access | | Chat Message / Audio | Routes text and voice messages to AI | | Document / Photo | Extracts text from files via OCR and forwards to AI | | Root Agent | Routes messages to Expense Assistant, validates responses | | Expense Assistant | Core logic: stores expenses, calculates statistics | | Result / Reply | Sends formatted response back to Telegram | | Cleanup / Reset | Manual trigger to delete all data (β οΈ use with caution) | π¬ Usage Examples Adding Expenses πΈ [Send receipt photo] β Added: 45.50 EUR - Groceries (Lidl) π€ "Bought coffee for five euros" β Added: 5.00 EUR - Dining Out (coffee) π¬ "50 uber" β Added: 50.00 EUR - Transportation (uber) Querying Expenses "Show my expenses" β November 2025: 1,250.50 EUR (23 expenses) Top: Groceries 450β¬, Transportation 280β¬, Dining 220β¬ "How much on entertainment this month?" β Entertainment: 85.00 EUR (3 expenses) "Compare October and November" β Oct: 980β¬ | Nov: 1,250β¬ (+27%) π¦ Data Storage Expenses are stored in JSON format organized by month (YYYY-MM): { "id": "uuid", "amount": 45.50, "currency": "EUR", "category": "Groceries", "description": "Store name", "date": "2025-11-10T14:30:00Z", "created_at": "2025-11-10T14:35:22Z" } β οΈ Important Notes First user locks the bot** - Run /start to claim ownership Default currency is EUR** - AI auto-detects other currencies Cleanup deletes ALL data** - Use manual trigger with caution No confirmation for adding** - Only delete operations ask for confirmation π οΈ Customization Change default currency in agent prompts Add/modify expense categories in ExpenseAssistant Extend Root Agent with additional assistants Adjust AI models (swap GPT-4o/Sonnet as needed) π Related Resources Create Telegram Bot OpenRouter Credentials Ainoflow Platform πΌ Need Customization? Want to adapt this template for your specific needs? Custom integrations, additional features, or enterprise deployment? Contact us at Ainova Systems - We build AI automation solutions for businesses. Tags: telegram, expense-tracker, ai-agent, ocr, voice-to-text, openrouter, mcp-tools, personal-finance
by Ranjan Dailata
This n8n workflow automates domain level keyword ranking analysis and enriches raw SEO metrics with AI-generated summaries. It combines structured keyword data from SE Ranking with natural-language insights produced by OpenAI, turning complex SERP datasets into actionable SEO intelligence. Who this is for? This workflow is designed for: SEO engineers and technical marketers Growth teams running programmatic SEO Agencies managing multi-domain keyword analysis Product teams building SEO analytics pipelines Developers using n8n for data enrichment and reporting If you work with keyword data and need machine-readable output plus human-readable insights, this workflow is for you. What this workflow does Accepts a target domain or URL, region, keyword type (organic/paid), and filters Fetches keyword ranking data from the SE Ranking Domain Keywords API Extracts metrics such as: Keyword positions Search volume & CPC Competition & difficulty SERP features & search intent Traffic estimates Uses OpenAI GPT-4.1-mini to generate: A comprehensive narrative summary A concise abstract overview Merges raw data and AI insights into a single enriched dataset Exports the final output as structured JSON for downstream use Setup Prerequisites Active SE Ranking API access OpenAI API key with GPT-4.1-mini enabled Running n8n instance (self-hosted or cloud) Basic understanding of keyword ranking metrics Configuration steps If you are new to SE Ranking, please signup on seranking.com Import the workflow JSON into n8n Configure credentials: SE Ranking using HTTP Header Authentication. Please make sure to set the header authentication as below. The value should contain a Token followed by a space with the SE Ranking API Key. OpenAI API (GPT-4.1-mini model) Open the Set the Input Fields node and define: target_site (domain or URL) source (region, e.g. us) type (organic or paid) limit, filters, and requested columns Verify the output as per the export data handling. Converts enriched SEO results into structured JSON output Creates binary data to support file-based exports Converts processed data into CSV format for easy analysis Inserts or updates records in Google Sheets for reporting Ensures data consistency across all export destinations Enables downstream automation, dashboards, and audits Click Execute Workflow How to customize this workflow to your needs You can easily adapt this workflow by: Switching between organic and paid keyword analysis Changing regions for international SEO tracking Modifying requested keyword columns and SERP filters Customizing the OpenAI prompt to generate: SEO action items Competitive insights Executive summaries Replacing file export with: Databases Dashboards Slack/Email alerts Data warehouses Summary This n8n template delivers a production ready SEO analytics pipeline that bridges structured SERP data with AI powered interpretation. By combining SE Rankingβs keyword intelligence with OpenAI driven summarization, it enables faster insights, better reporting, and scalable SEO decision making without manual analysis.
by isaWOW
Submit a screen recording URL, customer name, and bug type through a simple web form. The workflow automatically scans the recording using WayinVideo AI to pinpoint the exact moment the bug occurs, then uses GPT-4o-mini to write a structured support ticket with priority, steps to reproduce, and a fix suggestion. The completed ticket is saved instantly as a new row in your Google Sheet β ready for your dev team. Built for support agents, QA teams, and SaaS companies who want to triage bugs faster without manual video scrubbing. What This Workflow Does AI bug detection** β Sends the screen recording to WayinVideo, which scans the video and finds the exact timestamp where the bug occurs Smart polling loop** β Automatically waits 45 seconds then checks for results, retrying until WayinVideo returns the bug moments Structured ticket generation** β GPT-4o-mini reads the bug moment data and writes a full support ticket with priority level, steps to reproduce, expected vs actual behaviour, and a suggested fix Auto-triage and assignment** β The AI decides severity (Critical to Low) and which team should own it (Backend, Frontend, QA, DevOps, or Product) Google Sheets logging** β Every ticket is saved with customer name, bug type, recording URL, timestamp, ticket content, status, and submission date Web form trigger** β A built-in form lets any support agent submit a bug report without touching n8n directly Setup Requirements Tools you'll need Active n8n instance (self-hosted or n8n Cloud) WayinVideo account + API key (for AI video bug detection) OpenAI API key (GPT-4o-mini for ticket generation) Google account with Google Sheets OAuth access Estimated Setup Time: 10β15 minutes Step-by-Step Setup Get your WayinVideo API key β Sign in to your WayinVideo account at WayinVideo, go to your API settings, and copy your key. Add the WayinVideo key to the Find Bug Moments step β Open the node called 2. WayinVideo β Find Bug Moments and replace YOUR_WAYINVIDEO_API_KEY in the Authorization header with your actual key. Add the WayinVideo key to the Get Bug Moments step β Open the node called 4. WayinVideo β Get Bug Moments and replace YOUR_WAYINVIDEO_API_KEY in the Authorization header with your actual key. > β οΈ Your WayinVideo API key appears in two nodes β replace it in both 2. WayinVideo β Find Bug Moments and 4. WayinVideo β Get Bug Moments or the workflow will fail. Add your OpenAI API key β In n8n, go to Credentials and create a new OpenAI credential. Paste your API key there. Then connect that credential to the node called 6a. OpenAI β Chat Model (GPT-4o-mini). Create your Google Sheet β Make a new Google Sheet with a tab named exactly Bug Tickets. Add these column headers in row 1: | Customer Name | Bug Type | Recording URL | Bug Moments Found | Top Bug Timestamp | Bug Ticket | Status | Date Submitted | Connect your Google account β In n8n, create a Google Sheets OAuth2 credential and connect your Google account. Apply that credential to the node called 7. Google Sheets β Save Bug Ticket. Add your Google Sheet ID β Open the node 7. Google Sheets β Save Bug Ticket and replace YOUR_GOOGLE_SHEET_ID with your actual Sheet ID. You can find this in the Google Sheet URL β it is the long string of characters between /d/ and /edit. Activate the workflow β Toggle the workflow to Active. Open the form URL from the 1. Form β Bug Recording + Details node and submit a test bug report to confirm everything is working. How It Works (Step by Step) Step 1 β Web Form (Bug Recording + Details) A support agent opens a web form and fills in three fields: the screen recording URL, the customer's name, and the type of bug (for example: Login Error, Payment Failure, or App Crash). Submitting the form kicks off the entire workflow automatically. Step 2 β WayinVideo β Find Bug Moments The recording URL is sent to the WayinVideo API with an instruction to search for moments matching the reported bug type. WayinVideo scans the video using AI and starts building a list of the most relevant bug moments, including timestamps and relevance scores. The API returns a job ID that is used in the next steps. Step 3 β Wait 45 Seconds The workflow pauses for 45 seconds to give WayinVideo time to process the video before checking for results. Step 4 β WayinVideo β Get Bug Moments Using the job ID from Step 2, the workflow requests the results from WayinVideo. This returns a list of clips, each with a title, description, start and end timestamp, and a relevance score. Step 5 β Check: Bug Moments Found? The workflow checks whether WayinVideo has returned any bug moment clips yet. If yes** β it moves forward to generate the ticket. If no** β it loops back to Step 3, waits another 45 seconds, and checks again. > β οΈ If WayinVideo never returns results (for example, if the URL is broken or the video format is unsupported), this loop will repeat indefinitely. Consider adding a retry limit to avoid runaway executions. Step 6 β AI Agent β Generate Bug Ticket GPT-4o-mini receives the customer details from the form and the bug moment data from WayinVideo. It writes a complete structured support ticket covering: a one-sentence bug summary, priority level, bug category, exact video timestamp, steps to reproduce, expected vs actual behaviour, which team to assign it to, and a suggested fix. Step 7 β Google Sheets β Save Bug Ticket The completed ticket is appended as a new row in your Google Sheet. The row includes the customer name, bug type, recording URL, number of bug moments found, the top bug timestamp, the full ticket text, a status of "Open", and the submission date and time. Key Features β Exact bug timestamp detection β WayinVideo pinpoints the precise moment in the recording where the bug occurs, so your dev team doesn't have to watch the whole video β Auto-priority assignment β GPT-4o-mini assigns Critical, High, Medium, or Low priority based on the type of bug reported β Auto-team routing β The AI decides whether the ticket belongs to Backend Dev, Frontend Dev, QA, DevOps, or Product β no manual triage needed β Smart retry loop β The workflow polls WayinVideo automatically every 45 seconds until results are ready, with no manual intervention required β Structured ticket format β Every ticket follows the same format with all required fields, making it consistent and ready to import into any project management tool β Zero-code form β Support agents submit bug reports through a hosted web form β no n8n access needed β Full audit trail in Sheets β Every ticket is logged with submission date, recording URL, and status so nothing falls through the cracks Customisation Options Capture more bug moments β In the node 2. WayinVideo β Find Bug Moments, change "limit": 3 to "limit": 5 to detect up to five bug moments per recording instead of three. Use a more powerful AI model β In the node 6a. OpenAI β Chat Model (GPT-4o-mini), switch from gpt-4o-mini to gpt-4o for higher-quality ticket writing on complex or ambiguous bugs. Send instant Slack alerts β Add a Slack node after 7. Google Sheets β Save Bug Ticket to notify your dev channel as soon as a new ticket is saved, including the priority level and timestamp. Add a max-retry counter β To prevent the polling loop from running forever, add a counter variable that increments each loop and an extra condition in 5. If β Bug Moments Found? to stop after a set number of attempts (for example, 10 retries). Push tickets to Jira or Linear β Replace or add after the Google Sheets node an HTTP Request node that calls the Jira or Linear API to create an issue automatically from the generated ticket content. Support multiple languages β Change "target_lang": "en" in 2. WayinVideo β Find Bug Moments to another language code (for example "fr" or "de") to handle recordings in other languages. Support Need help setting this up or want a custom version built for your team or agency? π§ Email: info@isawow.com π Website: https://isawow.com/
by Stefan Joulien
Who this template is for This workflow is for users who want to turn Telegram into a personal AI-powered assistant capable of handling everyday tasks through natural language. It's ideal for solo founders, operators, or professionals who want to manage communication, scheduling, calculations, and information retrieval from a single chat interface. No advanced n8n knowledge is required, and the workflow is designed to be easily extended with additional tools. What this workflow does This workflow creates a Telegram-based AI assistant that can receive text or voice messages, understand user intent, and respond with text or audio. The assistant can reason about requests and use multiple tools such as contacts lookup, email drafting, calendar management, research, messaging, and calculations. Voice messages are automatically transcribed, processed like text input, and answered accordingly. How it works The workflow listens for incoming Telegram messages and validates the sender It detects whether the message is text or voice β voice messages are transcribed using OpenAI before being passed to the AI agent The AI agent processes the request using a chat model, short-term memory, and a set of productivity tools (contacts, email, calendar, research, messaging, calculator) The response is cleaned and formatted, then split into multiple chat bubbles with natural delays for a more human-like delivery Depending on the output type, the response is sent as plain text or converted into audio and returned to the user in Telegram How to set up Create a Telegram bot and connect it to the Telegram Trigger node Add your Telegram user ID to the authorization fields Connect your OpenAI credentials for chat, transcription, and text-to-speech Activate the workflow and start chatting with your assistant Requirements Telegram account and bot token OpenAI API credentials n8n instance (cloud or self-hosted)
by David Olusola
π₯ Auto-Save Zoom Recordings to Google Drive + Log Meetings in Airtable This workflow automatically saves Zoom meeting recordings to Google Drive and logs all important details into Airtable for easy tracking. Perfect for teams that want a searchable meeting archive. βοΈ How It Works Zoom Recording Webhook Listens for recording.completed events from Zoom. Captures metadata (Meeting ID, Topic, Host, File Type, File Size, etc.). Normalize Recording Data A Code node extracts and formats Zoom payload into clean JSON. Download Recording Uses HTTP Request to download the recording file. Upload to Google Drive Saves the recording into your chosen Google Drive folder. Returns the file ID and share link. Log Result Combines Zoom metadata with Google Drive file info. Save to Airtable Logs all details into your Meeting Logs table: Meeting ID Topic Host File Type File Size Google Drive Saved (Yes/No) Drive Link Timestamp π οΈ Setup Steps 1. Zoom Create a Zoom App β enable recording.completed event. Add the workflowβs Webhook URL as your Zoom Event Subscription endpoint. 2. Google Drive Connect OAuth in n8n. Replace YOUR_FOLDER_ID with your destination Drive folder. 3. Airtable Create a base with table Meeting Logs. Add columns: Meeting ID Topic Host File Type File Size Google Drive Saved Drive Link Timestamp Replace YOUR_AIRTABLE_BASE_ID in the node. π Example Airtable Output | Meeting ID | Topic | Host | File Type | File Size | Google Drive Saved | Drive Link | Timestamp | |------------|-------------|-------------------|-----------|-----------|--------------------|------------|---------------------| | 987654321 | Team Sync | host@email.com | MP4 | 104 MB | Yes | π Link | 2025-08-30 15:02:10 | β‘ With this workflow, every Zoom recording is safely archived in Google Drive and logged in Airtable for quick search, reporting, and compliance tracking.
by Anna Bui
Automatically analyze n8n workflow errors with AI, create support tickets, and send detailed Slack notifications Perfect for development teams and businesses that need intelligent error handling with automated support workflows. Never miss critical workflow failures again! How it works Error Trigger captures any workflow failure in your n8n instance AI Debugger analyzes the error using structured reasoning to identify root causes Clean Data transforms AI analysis into organized, actionable information Create Support Ticket automatically generates a detailed ticket in FreshDesk Merge combines ticket data with AI analysis for comprehensive reporting Generate Slack Alert creates rich, formatted notifications with all context Send to Team delivers instant alerts to your designated Slack channel How to use Replace FreshDesk credentials with your helpdesk system API Configure Slack channel for your team notifications Customize AI analysis prompts for your specific error types Set up as global error handler for all your critical workflows Requirements FreshDesk account (or compatible ticketing system) Slack workspace with bot permissions OpenAI API access for AI analysis n8n Cloud or self-hosted with AI nodes enabled Good to know OpenAI API calls cost approximately $0.01-0.03 per error analysis Works with any ticketing system that supports REST API Can be triggered by webhooks from external monitoring tools Slack messages use rich formatting for mobile-friendly alerts Need Help? Join the Discord or ask in the Forum! Happy Monitoring!
by Shayan Ali Bakhsh
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Try It Out! Automatically generate Linkedin Carousal and Upload to Linkedin Use case : Linkedin Content Creation, specifically carousal. But could be adjusted for many other creations as well. How it works It will run automatically every 6:00 AM Get latest News from TechRadar Parse it into readable JSON AI will decide, which news resonates with your profile Then give the title and description of that news to generate the final linkedin carousal content. This step is also trigerred by Form trigger After carousal generation, it will give it to Post Nitro to create images on that content. Post Nitro provides the PDF file. We Upload the PDf file to Linkedin and get the file ID, in next step, it will be used. Finally create the Post description and Post it to Linkedin How to use It will run every 6:00 AM automatically. Just make it Live Submit the form, with correct title and description ( i did not added tests for that so must give that correct π ) Requirements Install Post Nitro community Node @postnitro/n8n-nodes-postnitro-ai We need the following API keys to make it work Google Gemini ( for Gemini 2.5-Flash Usage ) Docs Google Gemini Key Post Nitro credentials ( API key + Template id + Brand id ) Docs Post Nitro Linkedin API key Docs Linkedin API Need Help? Message on Linkedin the Linkedin Happy Automation!