Email summary agent
Problem Teams often struggle with email overload, leading to missed actions and inefficient meeting preparation. Solution This workflow automates email management using n8n and AI. It fetches emails, summarizes key points and actions, and sends two concise updates—one in the morning and one at night. How It Works Triggers at 7 AM and 9 PM: Automates the process to summarize emails received during specific time blocks. Fetches Emails: Retrieves emails from the last 24 hours or after a specific time. Summarizes with AI: Uses OpenAI to process the email content into actionable summaries. Sends Team Updates: Compiles the summaries into a concise, formatted email and sends it to the team. Expected Results Significant reduction in missed actions and follow-ups. Customizations Adjust timings, filters, and recipients to suit your team’s needs.
By Vishal KumarAI Timesheet Generator with Gmail, Calendar & GitHub to Google Sheets
AI-Powered Automatic Timesheet Generator for Google Sheets Stop wasting billable hours on manual time-tracking. AutoTimesheet Pro uses AI to collect emails, meetings, and GitHub work, then writes a clean timesheet straight into Google Sheets. Perfect for developers, consultants, agencies, and remote teams. Get Started with n8n now! --- 🚀 Key Features Automated Google Sheets time-tracking — zero spreadsheet prep. AI-generated activity summaries (≤ 120 chars) via OpenAI GPT-4o-mini. Gmail integration — logs only important emails, skipping newsletters & no-replies. Google Calendar time logger — captures confirmed events, duration, and attendees. GitHub commit & PR tracker — records your commits plus opened/closed PRs. Daily 7 PM cron trigger (easily adjustable). Month-based sheet creation — new tab spins up on the first run each month. No-code n8n template — just connect credentials and tweak one Set Variables node. 🔌 Easily extensible — drag-and-drop extra n8n nodes to add Slack, Jira, Notion, Asana, Trello, Toggl, or any other data source you need. --- 🔍 How It Works Collect — n8n pulls data from Gmail, Google Calendar, and chosen GitHub repos. Clean — filters remove noise (newsletters, irrelevant commits, etc.). Condense — OpenAI rewrites each item into a concise, SEO-friendly description. Write — workflow appends Date, Type, and Description to your Timesheet Google Sheet. Extend — simply insert new n8n nodes (e.g., Slack, Notion, Jira) and merge them into the same pipeline. --- 📈 Benefits for SEO-Minded Professionals Keyword-rich activity log improves internal search and reporting. Structured data in Sheets simplifies export to accounting or PM tools. Consistent naming (CALENDAR_EVENT, EMAIL, COMMIT, PR) makes analytics easy. --- ✅ Why Choose AutoTimesheet Pro? Zero manual entry — just open the sheet and bill clients. Immediate visibility into where your hours went. Works with any GitHub repo list and any inbox you own. 100 % no-code setup — activate in minutes. Built on n8n, so you can customize and scale without limits. --- 📥 Get Started Ready to replace manual time-tracking with smart automation? https://n8n.partnerlinks.io/ds9podzjls6d Join N8N now, connect your Google & GitHub accounts, and let AI handle your daily log. ---
By Luka ZivkovicAI YouTube analytics agent: Comment analyzer & insights reporter
Transform YouTube comments into actionable insights with automated AI analysis and professional email reports. This intelligent workflow monitors your Google Sheets for YouTube video IDs, fetches comments using YouTube API, performs comprehensive AI sentiment analysis, and delivers formatted email reports with viewer insights - helping content creators understand their audience and improve engagement. 🚀 What It Does Smart Video Monitoring: Watches Google Sheets for new YouTube video IDs marked as "Pending" and triggers automated analysis Complete Comment Collection: Fetches up to 100 top comments per video using YouTube API with relevance-based ordering AI-Powered Analysis: Uses GPT-4 to analyze comments for sentiment, themes, questions, feedback, and actionable insights Professional Email Reports: Generates detailed HTML reports with statistics, sentiment breakdown, and improvement recommendations Automated Status Tracking: Updates spreadsheet status to prevent duplicate processing and maintain organized workflow 🎯 Key Benefits ✅ Deep Audience Insights: Understand what viewers really think about your content ✅ Save Hours of Manual Work: Automated comment analysis vs reading hundreds of comments ✅ Improve Content Strategy: Get actionable feedback for better video performance ✅ Track Sentiment Trends: Monitor positive/negative feedback patterns ✅ Professional Reporting: Receive formatted analysis reports via email ✅ Scalable Analysis: Process multiple videos automatically 🏢 Perfect For Content Creators & YouTubers Individual creators tracking audience engagement Educational channels analyzing learning feedback Entertainment creators understanding viewer preferences Business channels monitoring brand sentiment Marketing & Business Applications Brand Monitoring: Track sentiment on branded content and partnerships Audience Research: Understand viewer demographics and preferences Content Optimization: Identify what resonates with your audience Competitor Analysis: Analyze comments on competitor videos (where allowed) ⚙️ What's Included Complete Analytics Workflow: Ready-to-deploy YouTube comment analysis system Google Sheets Integration: Simple spreadsheet-based video management YouTube API Integration: Automated comment fetching with proper authentication AI Analysis Engine: GPT-4 powered sentiment and insight generation Email Reporting System: Professional HTML-formatted reports Status Management: Automatic processing tracking and duplicate prevention 🔧 Setup Requirements n8n Platform: Cloud or self-hosted instance YouTube API Credentials: Google Cloud Console API access OpenAI API: GPT-4 access for comment analysis Google Sheets: Video ID management and status tracking Gmail Account: For receiving analysis reports 📊 Required Google Sheets Structure | ID | Video Title | YouTube Video ID | Status | |----|-------------|------------------|---------| | 1 | My Tutorial | dQw4w9WgXcQ | Pending | | 2 | Product Demo| abc123def456 | Mail Sent | | 3 | Weekly Vlog | xyz789uvw012 | Draft | Status Options: Draft → Pending → Mail Sent 📧 Sample Analysis Report 📺 YouTube Comments Analysis Report Video: "How to Build Your First Website" 📊 Quick Statistics: • Total Comments Analyzed: 87 • Average Likes per Comment: 3.2 • Total Replies: 156 • Sentiment Summary: Positive: 65%, Negative: 10%, Neutral: 25% ❓ Common Questions: • "What hosting service do you recommend?" • "Can I do this without coding experience?" • "How much does domain registration cost?" 💡 Key Feedback Points: • Tutorial pace is perfect for beginners • More examples of finished websites requested • Viewers want follow-up video on advanced features 🎯 Actionable Insights: • Create hosting comparison video • Add timestamps for different skill levels • Consider beginner-friendly series expansion 🎨 Customization Options Analysis Depth: Adjust AI prompts for different analysis focuses (engagement, education, entertainment) Comment Limits: Modify maximum comments processed (default: 100, AI analysis: 50) Report Recipients: Send reports to multiple team members or clients Custom Metrics: Add specific analysis criteria for your content niche Multi-Channel: Process videos from multiple YouTube channels Scheduling: Set up regular analysis of your latest videos 🏷️ Tags & Categories youtube-analytics comment-analysis content-creator-tools ai-sentiment-analysis video-insights audience-research youtube-api content-optimization social-media-analytics creator-economy video-marketing engagement-analysis content-strategy ai-reporting youtube-automation 💡 Use Case Examples Educational Channel: Analyze tutorial comments to identify confusing concepts and improve teaching methods Product Reviews: Monitor sentiment on review videos to understand customer satisfaction trends Entertainment Creator: Track audience reactions to different content formats and optimize future videos
By Yaron BeenKB tool - Confluence knowledge base
Enhance Query Resolution with the Knowledge Base Tool! Our KB Tool - Confluence KB is crafted to seamlessly integrate into the IT Ops AI SlackBot Workflow, enhancing the IT support process by enabling sophisticated search and response capabilities via Slack. Workflow Functionality: Receive Queries: Directly accepts user queries from the main workflow, initiating a dynamic search process. AI-Powered Query Transformation: Utilizes OpenAI's models or local ai to refine user queries into searchable keywords that are most likely to retrieve relevant information from the Knowledge Base. Confluence Integration: Executes searches within Confluence using the refined keywords to find the most applicable articles and information. Deliver Accurate Responses: Gathers essential details from the Confluence results, including article titles, links, and summaries, preparing them to be sent back to the parent workflow for final user response. To view a demo video of this workflow in action, click here. Quick Setup Guide: Ensure correct configurations are set for OpenAI and Confluence API integrations. Customize query transformation logic as per your specific Knowledge Base structure to improve search accuracy. Need Help? Dive into our Documentation or get support from the Community Forum! Deploy this tool to provide precise and informative responses, significantly boosting the efficiency and reliability of your IT support workflow.
By Angel MenendezTranscribe voice messages from Telegram using OpenAI Whisper-1
This n8n workflow processes incoming Telegram messages, differentiating between text and voice messages. How it works: Message Trigger: The workflow initiates when a new message is received via the Telegram "Message Trigger" node. Switch Node: This node acts as a router. It examines the incoming message: If the message is text, it directs the flow along the "text" branch. If the message contains voice, it directs the flow along the "voice" branch. Get Audio File: For audio messages, this node downloads the audio file from Telegram. Transcribe Audio: The downloaded audio file is then sent to an "OpenAI Transcribe Recording" node, which uses OpenAI's whisper-1 speech-to-text model to convert the audio into a text transcript. Send Transcription Message: Regardless of whether the original message was text or transcribed audio, the final text content is then passed to a "Send transcription message" node. Setup Requirements: Telegram Bot Token: You will need a Telegram bot token configured in the "Message Trigger" node to receive messages. OpenAI API Key: An OpenAI API key is required for the "Transcribe audio" node to perform speech transcription. Additional Notes: This workflow provides a foundational step for building more complex AI-driven applications. The transcribed text or original text message can be easily piped into an AI agent (e.g., a large language model) for analysis, response generation, or interaction with other tools, extending the bot's capabilities beyond simple message reception and transcription. 👉 Need Help? Feel free to contact us at 1 Node. Get instant access to a library of free resources we created.
By Aitor | 1NodeReceive updates for events in Jira
Companion workflow for Jira Trigger node docs
By amudhanParse email body message
Who we are We are Aprende n8n, the first n8n Spanish course for all n8n lovers. If you want to learn more, you can find out more at Aprende n8n. Task goal This task allows extracting data from any email body with a NoCode snippet. An small explanation You receive an email when a user submits a form from your website. All those emails usually have the same structure as the next one: Name: Miquel Email: miquel@aprenden8n.com Subject: Welcome aboard Message: Hi Miquel! Thank you for your signup! This task allows to parse any email body and assign all values to the defined labels, getting an output like this: { "Name": "Miquel", "Email": "miquel@aprenden8n.com", "Subject": "Welcome aboard", "Message" "Hi Miquel! Thank you for your signup!" } After importing it When you import the import, you get the next task in your n8n: We recommend importing this workflow into your current task and adapting it. You define a couple of variables in the "Set values" SET: body: the email body you want to parse. You can add this as an expression from previous variables. labels: the keywords you want to detect and parse. Labels are case insensitive. We define the next values: Body Name: Miquel Email: miquel@aprenden8n.com Subject: Welcome aboard Message: Hi Miquel! Thank you for your signup! Labels Name,Email,Subject,Message A screenshot of the Set output is the next one If we check the "Function item" Node, we get the next content after executing the task: Capabilities The task has the next features: You can detect as many labels as you want. Label detection is case insensitive. You can use the snippet as an independent workflow to call it generically, adding the Function item to the workflow and passing body and labels as paremeters. Limitations This task has limitations: The parser only accepts the multiline values at the end of the email. Help and comments If you have any doubt about this snippet, please, contact us at miquel@aprenden8n.com. You can contact us at Aprende n8n or in the Spanish n8n community
By Miquel ColomerCreate an event file and send it as an email attachment
This workflow allows you to create an event file and send it as an attachment via email. iCalendar node: This node will create an event file. Send Email: This node will send the event file as an attachment.
By Harshil AgrawalTime logging on Clockify using Slack
Time Logging on Clockify Using Slack How it works This workflow simplifies time tracking for teams and agencies by integrating Slack with Clockify. It enables users to log, update, or delete time entries directly within Slack, leveraging an AI-powered assistant for seamless and conversational interactions. Key features include: Effortless Time Logging: Create and manage time entries in Clockify without leaving Slack. AI-Powered Assistant: Get step-by-step guidance to ensure accurate and efficient time logging. Project and Client Management: Retrieve project and client information from Clockify effortlessly. Overlap Prevention: Avoid overlapping entries with built-in time validation. Automated Descriptions: Generate ethical, grammatically correct descriptions for time logs. Set up steps Prepare your integrations Ensure you have active accounts for both Slack and Clockify. Generate your Clockify API credentials for integration. Import the workflow Download and import the workflow template into your n8n instance. Configure the workflow to connect with your Slack and Clockify accounts. Configure the workflow Add your Clockify API credentials in the workflow settings. Set up the Slack Trigger to listen for app mentions or specific commands. Test the workflow Use Slack to create a time entry and verify it in Clockify. Test updating and deleting existing entries to ensure smooth functionality. Check for any overlapping time logs or incorrect data entries. Why use this workflow? Efficiency: Eliminate the need to switch between tools for time tracking. Accuracy: AI-driven validation ensures error-free entries. Automation: Simplify repetitive tasks like updating or deleting time logs. Proactive Guidance: Conversational assistant ensures smooth operations.
By Blockia LabsAI research agents to automate PDF analysis with Mistral’s best-in-class OCR
Overview Mistral OCR is a cutting-edge document understanding API that improves how businesses extract and process information from complex documents. With top scores in benchmarks for accuracy and comprehension capabilities, Mistral OCR handles multi-column text, charts, diagrams, and multiple languages. This workflow uses Mistral's Document understanding OCR API to automatically turns dense PDFs (such as financial reports) into either deep research reports or concise newsletters [](https://youtu.be/Z9Lym6AZdVM) Key Features Superior Document Understanding: Processes complex documents with high-fidelity rendering Multi-Format Support: Handles PDFs containing text, images, charts, and diagrams Multilingual Capabilities: Accurately processes documents in various languages Seamless API Integration: Easy implementation through cloud-based API Customizable Research Depth: Generate comprehensive 8-page reports or concise 1,750-word newsletters How It Works Document Upload: Submit your PDF through an n8n form interface. Output Format Selection: Choose between comprehensive deep research (3,500 words) or Concise newsletter (1,750 words) Custom Instructions: Tailor the analysis by adding specific focus areas (e.g., quantitative data, growth catalysts). AI Processing: The document undergoes multi-stage AI analysis: OCR and text extraction using Mistral AI and Content structuring and summarization using GPT models Agents: Research Leader: Plans and conducts initial research, creating a table of contents. Project Planner: Breaks down the table of contents into manageable sections. Research Assistants: Multiple agents that conduct in-depth research on assigned sections. Editor: Compiles and refines the final article, ensuring coherence and proper citations. Setup API Key Acquisition: Obtain an API key from OpenRouter.ai Get an API key from Mistral.ai n8n Configuration: In your n8n instance, navigate to the credentials section. Create new credentials for OpenRouter and Mistral, inputting the respective API keys. Form Configuration: Customize the input form fields if needed (e.g., adding company-specific options). Output Customization: Adjust the word count parameters in the Project Planner node to change output length.
By Derek CheungitemMatching() usage example
This workflow provides a simple example of how to use itemMatching(itemIndex: Number) in the Code node to retrieve linked items from earlier in the workflow.
By n8n TeamSend Instagram statistics to Mattermost
This worflow let us know main stat on our Instagram : this is the first i share with community as i am a beginner :) Every morning i know how many follower we have, how many posts have been made. I use a fantastic tool which is : https://socialblade.com and also : https://martechwithme.com/monitoring-youtube-channels-subscribers-with-google-sheets/ to send them to Google Sheets Hope this could help :) This can be improved for sure, so i will be very pleased to have your comments thanks --------------------------- French version : :) Ce schéma permet d'avoir les statistiques de notre Instagram : combien de followers et combien de posts ont été réalisés. Ces données sont publiées sur MAttermost. J'utilise un outil génial pour récupérer les données de instagram : https://socialblade.com puis https://martechwithme.com/monitoring-youtube-channels-subscribers-with-google-sheets/ pour les récupérer sur Google Sheets
By damien