by Jorge Martínez
Lead Enrichment & Email Discovery from Google Sheets What this workflow does This template automates the enrichment of business leads from a Google Sheet by: Triggering when a row is activated Searching for company information with Serper.dev Generating and validating potential contact pages Scraping company pages with ScrapingBee Extracting emails and updating the sheet Marking rows as finished Prerequisites Google Sheet with columns: business type, city, state, activate Copy the ready-to-use template:** Sheet Template Google Sheets API credentials (from Google Cloud) Serper.dev API key (free tier available) ScrapingBee API key (free tier available) Inputs Google Sheet row:** Must include business type, city, state, activate Set Information Node:** country, country_code, language, result_count (can also be provided via columns in the sheet) Outputs Google Sheet update:** Company names, URLs, found email addresses (comma-separated if multiple), and status updates (Running, Missing information, Finished) Configuration Required Connect Google Sheets node with your Google Cloud credentials Add your Serper.dev API key to the HTTP Request node Add your ScrapingBee API key to the scraping node Adjust search and filtering options as needed How to customize the workflow Send country, country_code, and result_count from the sheet:** Add these as columns in your sheet and update the workflow to read their values dynamically, making your search fully configurable per row. Add more blacklist terms:** Update the code node with additional company names or keywords you want to exclude from the search results. Extract more contact details:** Modify the email extraction code to find other contact info (like phone numbers or social profiles) if needed.
by Amjid Ali
Template Guide for Employee Shortlisting AI Agent Automation Overview This template automates the process of shortlisting job applicants using ERPNext, n8n, and AI-powered decision-making tools like Google Gemini and OpenAI. It reduces manual effort, ensures fast evaluations, and provides justifiable decisions about applicants. This is ideal for businesses aiming to streamline their recruitment process while maintaining accuracy and professionalism. YouTube Tutorial:** For a full walkthrough of this template, visit: Integrate AI in ERPNext: Automate Recruitment Job Applicant Shortlisting in Seconds! What Does This Template Do? Webhook Integration with ERPNext: Automatically triggers the workflow when a job application is created in ERPNext. Resume Validation: Ensures resumes are attached and correctly processes various file formats like PDF and DOC. AI-Powered Evaluation: Uses AI to compare resumes against job descriptions and provides a: Fit Level (Strong, Moderate, or Weak) Score (0–100) Justification for the decision. Automated Decision Making: Based on AI-generated scores: Candidates with a score of 80 or higher are Accepted. Candidates below 80 are Rejected. Applications missing required fields or attachments are put On Hold. ERPNext Integration: Updates applicant records in ERPNext, including custom fields such as justification, fit level, and scores. Notifications: Notifies candidates via email, WhatsApp, or SMS about their application status. Step-by-Step Guide Step 1: Set Up ERPNext Webhook Go to Webhooks in ERPNext. Create a webhook for the Job Applicant DocType. Set the trigger to Insert. Pin and test the webhook to ensure proper data flow. Step 2: Import the Template into n8n Open your n8n instance. Import the provided workflow template. Check all nodes for proper configuration. Step 3: Configure Credentials Add your ERPNext API credentials to the ERPNext nodes. Add credentials for AI services like OpenAI or Google Gemini. Configure additional services like WhatsApp or email if you plan to use them for notifications. Step 4: Test Resume Validation Test how the workflow handles different file types (e.g., PDF, DOC, JPG). Ensure resumes without the proper format or attachment are flagged and rejected. Step 5: AI Evaluation The AI model (Google Gemini or OpenAI) will evaluate resumes against job descriptions. Customize the AI prompt to suit your job evaluation needs. The output will include a Fit Level, Score, Rating, and Justification. Step 6: Decision Automation The workflow automatically categorizes applicants: Accepted for scores ≥ 80. Rejected for scores < 80. On Hold if essential fields or attachments are missing. Step 7: Update ERPNext Records The workflow updates the Job Applicant record in ERPNext with: Status (Accepted, Rejected, On Hold) AI-generated Fit Level, Score, Rating, and Justification. Step 8: Notify Candidates Configure notification nodes (email, WhatsApp, or SMS). Inform candidates about their application status and include feedback if required. How It Works Trigger: The workflow starts when a job application is submitted in ERPNext. Validation: Checks if the resume is attached and in the correct format. AI Evaluation: Compares the resume with the job description and generates a decision. ERPNext Update: Updates the applicant's record with the decision and justification. Notification: Sends a personalized notification to the candidate. Dos and Don’ts Dos: Customize Prompts:** Tailor the AI prompt to match your specific job evaluation requirements. Test the Workflow:** Run sample data to ensure the process works as intended. Secure Your Credentials:** Keep your API credentials safe and do not share them publicly. Optimize for Different Formats:** Ensure the workflow can handle all types of resumes you expect. Don’ts: Avoid Manual Intervention:** Let the workflow handle most of the tasks to ensure efficiency. Do Not Skip Testing:** Always test the workflow with various scenarios to avoid errors. Do Not Overlook Notifications:** Ensure candidates are notified promptly to maintain professionalism. Customization Options Add logic for more file types (e.g., scanned images using OCR). Enhance the AI prompts to analyze more complex resume data. Integrate additional tools like Slack or Trello for recruitment tracking. Resources GET n8n Now N8N COURSE n8n Book YouTube Tutorial:** For a full walkthrough of this template, visit: SyncBricks YouTube Channel Detailed Guides and Courses:** Learn more about ERPNext and AI-driven automation at: SyncBricks LMS Support If you encounter issues or want to explore more possibilities with AI-driven automation, feel free to reach out: Email:** amjid@amjidali.com Website:** ERPNext and Other Courses LinkedIn:** Amjid Ali Let me know if you'd like further details or modifications to the guide!
by Zacharia Kimotho
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This workflow is a gem for all PPC managers and experts out there looking to keep track of competitor ads and the campaigns they are running and generate an email report How does it work We use Bright Data API to scrap Google for a given keyword that can trigger an ad. We then extract and analyse different components of the ads to get insights and data rekevant for our processes Setting it up Make a copy of this workflow to your canvas Make a copy of this google sheet Add high intent commercial keywords to your google sheet. These are relevant to trigger ads Set your Bright Data API credentials and update the zone to your respective zone as set on your Bright Data account We filter only if ads are found and if true extract the top and botton ads This routes the results via different paths Store raw Ad results Process the Ads to get new insights and data Map the raw data to match your account You can adjust the prompt to provide any data as needed Connect your emailing platform or tool and update the to email Setting up Bright Data serp API and Zone On Bright Data, go to the Proxies & Scraping tab Under SERP API, create a new zone Give it a suitable name and description. The default is serp_api Add this to your account If you have any questions, feel free to reach out via linkedin
by Cognitive Creators
Microsoft Outlook AI Email Assistant Prerequisites 1. Microsoft 365 Login Credentials Provide your Office 365 credentials to connect Outlook. 2. Monday.com Generate an API token and have a board with your contact details. 3. Airtable Obtain an API key (or personal access token) and set up a base to store: Contacts (populated by the Monday.com sync). Rules & Categories (used by the AI Email Assistant). Use this Airtable base as the template: Airtable AI Email Assistant Template. Define your own rules, categories, and delete rules. 4. OpenAI API Key Sign up for OpenAI if you don’t already have an account. Generate a new API key at OpenAI API Keys. What the System Does 1. Daily Contact Sync (Monday.com → Airtable) Runs once a day to pull the latest contacts from Monday.com and store or update them in Airtable. 2. AI Email Categorisation & Prioritisation Fetches Outlook emails with filters. Cleans and processes email content. Matches emails with known contacts from Airtable. Uses an AI agent to classify, categorise, and prioritise emails. Updates Outlook categories and importance based on AI results. Runs in parallel with Airtable rules & categories retrieval for real-time decision-making. Workflow 1: Daily Contact Sync (Monday.com → Airtable) Purpose Keep Airtable’s Contacts table up to date by pulling new or updated contact data from Monday.com daily. Steps Schedule Trigger Runs at a set interval (daily) to initiate contact syncing. Monday.com: Get Contacts Reads the specified board/columns from Monday.com where you store contact details. Airtable - Contacts Upserts (adds or updates) the fetched Monday.com data into Airtable’s Contacts table. Ensures daily updates reflect changes from Monday.com. Result A consolidated contact list in Airtable, ready for AI email categorisation. Workflow 2: Categorise & Prioritise Outlook Emails Purpose Fetches Outlook emails, cleans and processes their content, matches senders with known contacts, and uses AI to categorise and prioritise them. Steps 1. Get Outlook Emails with Filters Trigger**: Either scheduled (Check Mail Schedule Trigger) or manual (Test Workflow). Outlook Filters**: Not flagged (flag/flagStatus == 'notFlagged'). Not categorised (not categories/any()). 🔹 Result: A batch of fresh, unprocessed emails ready for processing. 2. Sanitise Email Convert to Markdown: Strips **HTML tags and normalises formatting. Email Messages Processing: Allows manual removal of **signatures, disclaimers, or extra content. 🔹 Result: A clean, AI-friendly email for categorisation. 3. Match Contact Loop Over Emails**: Iterates over each email. Contact Lookup: Checks Airtable’s **Contacts table (updated daily). Merge Data: Enriches emails with known **client, supplier, or internal team info. 🔹 Result: Enhanced email context for AI processing. 4. AI Agent to Categorise & Prioritise Retrieve Rules & Categories** Reads Rules, Categories, and Delete Rules from Airtable in parallel. AI: Analyse Email (Tools Agent)** Uses email text, sender info, and rules to build a structured AI prompt. OpenAI Chat Model** Processes the AI prompt and outputs: Category Subcategory (optional) Priority level Short rationale Structured Output Parser** Ensures AI response is valid JSON format. 🔹 Result: Each email is labelled, categorised, and prioritised with AI-driven logic. 5. Set Outlook Category & Importance Set Category: Updates Outlook with the assigned **category. Check Priority Conditions** (If Node): If Action Required or from a VIP, mark as High Priority. Set Importance: Updates the email's **importance flag in Outlook. 🔹 Result: Outlook is updated with categories & importance based on AI recommendations. Parallel Processing: Retrieve Rules & Categories Runs alongside the email categorisation workflow. Ensures Airtable-based rules are available before AI processing. Steps Airtable: Get Rules & Categories Fetches Rules, Categories, and Delete Rules from Airtable. Delete Rules (Optional) If a delete rule matches, the email is removed. 🔹 Result: A dynamic, updatable rule system ensuring emails are handled properly. Final Outcome Daily Contact Sync** keeps contacts up to date. AI-driven email workflow** ensures smart categorisation. Outlook automatically updated** with AI-generated categories and importance. This automated system saves time, ensures efficient inbox management, and allows for customisable rules via Airtable.
by Jay Emp0
AI Email Classifier 📬 Automate Email Classification, Prioritization, and Spam Detection Across Multiple Accounts Created by: Jayant Kumar (@jharilela) 🛠 Powered by: Gmail, Google Sheets, OpenAI, Discord, and n8n Sample Discord labelling as Spam Sample Discord labelling as Legit Why I Built This Focus is Expensive. Managing multiple email inboxes every day—personal, business, partnerships, invoices. Logging into each, skimming through noise, flagging important stuff, and deleting spam started eating up hours of my week. I needed a system that helped me focus only on what matters without building an entire helpdesk dashboard. I already live in Discord. It made sense to push my emails there—but in a fun, digestible, and actionable way. I built AI Email Classifier 📬 to summarize emails, detect spam, assign priority, and make everything skimmable with pictures and links. And it works across multiple Gmail accounts. Key Features ✅ Works with multiple Gmail inboxes 🧠 Uses AI to classify spam vs legit 🎯 Assigns priority levels: High / Medium / Low 🗂 Appends everything to a central Google Sheet 📸 Sends visual summaries to Discord (with image + action links) 🛠 Powered by open-source: n8n_discord_trigger_bot How It Works Here’s the high-level flow: New Email in any inbox triggers the worfklow to start The AI Agent reads the raw content, subject, sender, Gmail labels. It calls a Google Sheet that acts as our feedback memory: Emails and domains manually marked as spam or legit. AI classifies the incoming email using logic: Spam if sender or domain is blacklisted, or content matches patterns like: "promotions, phishing, ads, mass emails, cold offers" Priority is assigned by: High: deadlines, legal, payments, clients, CEO emails Medium: team updates, meetings, project notifications Low: newsletters, FYIs, casual threads It produces a compact JSON output with: Sender, recipient, subject, summary, priority, priority color, image URL, action URL The message is formatted visually and posted back to Discord as an embed with: Summary text Actionable links Priority color code Thumbnail (if any) Google Sheet Training Table The system uses this sheet as live memory to label spam and legit senders: ╔════════════════════╦══════════════╦═════════════════╦══════════════╦════════════════╗ ║ Email ║ Domain ║ Classification ║ Labelled By ║ Labelled Date ║ ╠════════════════════╬══════════════╬═════════════════╬══════════════╬════════════════╣ ║ offers@badsite.com ║ badsite.com ║ Spam ║ Jayant ║ 08/07/2025 ║ ║ ceo@trusted.com ║ trusted.com ║ Legit ║ Jayant ║ 08/07/2025 ║ ╚════════════════════╩══════════════╩═════════════════╩══════════════╩════════════════╝ This allows manual control to teach the AI which senders to trust or ignore. Every time I see something marked wrong, I just reply in Discord with "spam" or "legit" on that message thread. That triggers an update to the Sheet via AI parsing and n8n. Why Manual Input Still Matters AI isn’t perfect. Some spam emails are cleverly disguised. And some senders are contextually important only to you. That’s why I kept a simple feedback loop: You tell the bot "spam" or "legit" on any Discord email message. Or anything along that line The AI agent detects the intent and updates the Sheet. The AI improves its judgment next time as it now remembers your preference Why Discord? Because Slack charges per seat and email feels lonely. I run most of my operations inside Discord community chats, client rooms, bot alerts. Instead of making a full email UI, I turned each email into a Discord card with a thumbnail, summary, and quick actions. It’s fun. It’s visual. It doesn’t feel like work. Email becomes more like a game feed. Tech Stack Gmail → Discord via Gmail trigger node Discord → n8n Webhook via n8n_discord_trigger_bot OpenAI GPT-4o (classification + summarization) Google Sheets (feedback memory) Discord Node (embed output with JSON + images) Try It Yourself Clone the workflow JSON, set up your Gmail integrations, and install the n8n Discord Trigger Bot. I made this workaround because i couldnt find a discord trigger on n8n. Now I just scroll my Discord DMs and know what to reply to, and ignore everything else.Dont let Email spam your brain. Let your AI do the thinking.
by Club de Inteligencia Artificial Politécnico CIAP
📰 LinkedIn News Auto-Publisher Overview 📋 This project is an automated news publisher for LinkedIn. It uses RSS feeds to fetch news, processes the content with the Gemini API to generate precise summaries, and automatically publishes to LinkedIn via its API. How It Works Architecture and Workflow ⚙️ n8n**: Efficient orchestration of workflow with automation. RSS**: News sources such as TechCrunch and MIT Technology Review. Gemini API**: Dynamic generation of content and precise summaries. LinkedIn API**: Automatic publication on profiles and corporate pages. Content Processing 🧠 Fetching news through RSS feeds. Processing and generating summaries with the Gemini API. Automatic publication on LinkedIn. Key Benefits ✅ Complete automation of the news publishing process. Dynamic generation of precise and relevant content. Integration with reliable news sources and publication on a professional platform. Use Cases 💼 Automation of news publishing for businesses and professionals. Keeping corporate profiles and pages updated with relevant content. Saving time in managing content on social networks. Requirements 👨💻 n8n instance (self-hosted or cloud). Gemini API credentials. LinkedIn bot setup and API credentials. Configured RSS feeds to fetch news. Authors 👥 Joel Choez Alan Bajaña Jaren Pazmiño David Sandoval Members of CIAP
by Davide
This workflow is designed to manage the assignment and validation of unique QR code coupons within a lead generation system with SuiteCRM. How it Works This workflow automates the process of assigning unique QR code coupons to leads generated through a form submission, ensuring no duplicates are created, and validating the usage of coupons. Here's how it operates: Webhook Trigger: The workflow starts with a Webhook node that listens for incoming requests containing QR code data. A Set coupon node extracts the QR code value from the request parameters. Validation of QR Code: An If node checks if the QR code exists in the incoming data. If it does, the process proceeds; otherwise, a "No coupon" response is sent back. Coupon Lookup: The Get Lead node queries a Google Sheets document to check if the QR code corresponds to an existing lead. A subsequent Not used? node verifies whether the coupon has already been used by checking the "USED COUPON?" field in the sheet. Lead Duplication Check: When a new lead submits the form (On form submission), the Duplicate Lead? node checks if the email already exists in the system to prevent duplicates. Coupon Assignment: If the lead is not a duplicate, the Get Coupon node retrieves an available unassigned coupon from the Google Sheets document. The Token SuiteCRM node generates an access token for SuiteCRM, and the Create Lead SuiteCRM node creates a new lead entry in SuiteCRM, associating it with the assigned coupon. QR Code Generation and Email Notification: The Get QR node generates a QR code image URL for the assigned coupon. The Send Email node sends an email to the lead with the QR code attached. Response Handling: Depending on the validation results, the workflow responds with appropriate messages: "Coupon OK" if the coupon is valid and unused. "Coupon KO" if the coupon has already been used. "Coupon not valid" if the QR code does not exist. Set Up Steps To replicate this workflow in your own n8n environment, follow these steps: Configuration: Set up an n8n instance either locally or via cloud services. Import the provided JSON configuration file into your workspace. Configure all required credentials, such as: Google Sheets OAuth2 API for accessing the spreadsheet. SuiteCRM API credentials (e.g., SUITECRMURL, CLIENTID, CLIENTSECRET). SMTP credentials for sending emails. Customization: Adjust the Webhook URL to match your deployment environment. Modify the Google Sheets document ID and sheet name in nodes like Duplicate Lead?, Get Coupon, Update Sheet, and Update coupon used. Update the SuiteCRM API endpoint and credentials in nodes like Token SuiteCRM and Create Lead SuiteCRM. Customize the email template in the Send Email node to match your branding and messaging requirements. Ensure the QR code generation URL in the Get QR node points to a valid QR code generator service. By following these steps, you can effectively implement and customize this workflow to manage lead generation and coupon assignments in your organization.
by Angel Menendez
CallForge - AI-Powered Sales Call Data Processor Automate sales call analysis and store structured insights in Notion with AI-powered intelligence. Who is This For? This workflow is ideal for: ✅ Sales teams looking to automate call insight processing. ✅ Sales operations managers managing AI-driven call analysis. ✅ Revenue teams using Gong, Fireflies.ai, Otter.ai, or similar transcription tools. It streamlines sales call intelligence, ensuring that insights such as competitor mentions, objections, and customer pain points are efficiently categorized and stored in Notion for easy access. 🔍 What Problem Does This Workflow Solve? Manually reviewing and documenting sales call takeaways is time-consuming and error-prone. With CallForge, you can: ✔ Identify competitors mentioned in sales calls. ✔ Capture objections and customer pain points for follow-up. ✔ Track sales call outcomes and categorize insights automatically. ✔ Store structured sales intelligence in Notion for future reference. ✔ Improve sales strategy with AI-driven, automated call analysis. 📌 Key Features & Workflow Steps 🎙️ AI-Powered Call Data Processing This workflow processes AI-generated sales call insights and structures them in Notion databases: Triggers automatically when AI call analysis data is received. Extracts competitor mentions from the call transcript and logs them in Notion. Identifies and categorizes sales objections for better follow-ups. Processes integration mentions, capturing tools or platforms referenced in the call. Extracts customer use cases, categorizing pain points and feature requests. Aggregates all extracted insights and updates relevant Notion databases. 📊 Notion Database Integration Competitors → Logs mentioned competitors for sales intelligence. Objections → Tracks and categorizes common objections from prospects. Integrations → Captures third-party tools & platforms discussed in calls. Use Cases → Stores customer challenges & product feature requests. 🛠 How to Set Up This Workflow 1. Prepare Your AI Call Analysis Data Ensure AI-generated sales call data is passed into the workflow. Compatible with Gong, Fireflies.ai, Otter.ai, and other AI transcription tools. 2. Connect Your Notion Database Set up Notion databases for: 🔹 Competitors (tracks competing products) 🔹 Objections (logs customer objections & concerns) 🔹 Integrations (captures mentioned platforms & tools) 🔹 Use Cases (categorizes customer pain points & feature requests) 3. Configure n8n API Integrations Connect your Notion API key** in n8n under “Notion API Credentials.” Set up webhook triggers** to receive data from your AI transcription tool. Test the workflow** using a sample AI-generated call transcript. CallForge - 01 - Filter Gong Calls Synced to Salesforce by Opportunity Stage CallForge - 02 - Prep Gong Calls with Sheets & Notion for AI Summarization CallForge - 03 - Gong Transcript Processor and Salesforce Enricher CallForge - 04 - AI Workflow for Gong.io Sales Calls CallForge - 05 - Gong.io Call Analysis with Azure AI & CRM Sync CallForge - 06 - Automate Sales Insights with Gong.io, Notion & AI CallForge - 07 - AI Marketing Data Processing with Gong & Notion CallForge - 08 - AI Product Insights from Sales Calls with Notion 🔧 How to Customize This Workflow 💡 Modify Notion Data Structure – Adjust fields to match your company’s CRM setup. 💡 Enhance AI Data Processing – Align fields with different AI transcription providers. 💡 Expand with CRM Integration – Sync insights with HubSpot, Salesforce, or Pipedrive. 💡 Add Notifications – Send alerts via Slack, email, or webhook when key competitor mentions or objections are detected. ⚙️ Key Nodes Used in This Workflow 🔹 If Nodes – Checks if AI-generated data includes competitors, integrations, objections, or use cases. 🔹 Notion Nodes – Creates or updates entries in Notion databases. 🔹 Split Out & Aggregate Nodes – Processes multiple insights and consolidates AI outputs. 🔹 Wait Nodes – Ensures smooth sequencing of API calls and database updates. 🔹 HTTP Request Node – Sends AI-extracted insights to Notion for structured storage. 🚀 Why Use This Workflow? ✔ Eliminates manual data entry and speeds up sales intelligence processing. ✔ Ensures structured and categorized sales insights for decision-making. ✔ Improves team collaboration with AI-powered competitor tracking & objections logging. ✔ Seamlessly integrates with Notion to centralize and manage sales call insights. ✔ Scalable for teams using n8n Cloud or self-hosted deployments. This workflow empowers sales teams with automated AI insights, streamlining sales strategy and follow-ups with minimal effort. 🚀
by Davide
This workflow automates the process of analyzing emails and their attachments (PDFs and images) using AI models (DeepSeek, Gemini, and OpenRouter). It extracts and summarizes the content of emails and attachments, saves the summaries to Google Sheets, and sends a final consolidated summary via Telegram. This is a powerful tool for automating email analysis and summarization, saving time and ensuring that important information is easily accessible and actionable. Below is a breakdown of the workflow: 1. How It Works The workflow is designed to process incoming emails, analyze their content and attachments, and generate summaries. Here's how it works: Email Trigger: The workflow starts with the Email Trigger (IMAP) node, which monitors an email inbox for new emails. If an email contains attachments, the workflow processes them. Check for Attachments: The Contain Attachments? node checks if the email has attachments. If attachments are present, the workflow proceeds to process them. Process Attachments: The Get PDF and Images Attachments node extracts PDF and image attachments from the email. The Switch node separates PDFs and images for further processing: PDFs: The Extract from PDF node extracts text from PDFs, and the PDF Analyzer node summarizes the content. Images: The Analyze Image node uses AI to describe the content of images. Summarize Email Content: The Convert Text node converts the email's HTML content to plain text. The Email Summarization Chain node uses AI to generate a summary of the email's text content. Save Summaries: The Save Summary PDF, Save Summary Image, and Save Summary Text nodes save the summaries of PDFs, images, and email text, respectively, to Google Sheets. Consolidate Summaries: The All Summaries node aggregates the summaries of the email text, PDFs, and images. The Create Final Summary node uses AI to generate a unified summary of all the content. Send Final Summary: The Send Final Summary node sends the consolidated summary via Telegram to a specified chat ID. 2. Set Up Steps To set up and use this workflow in n8n, follow these steps: IMAP Configuration: Set up IMAP credentials in n8n for the Email Trigger (IMAP) node. Ensure the email account is accessible via IMAP. AI Model Configuration: Configure the DeepSeek, Gemini, and OpenRouter credentials in n8n for the Email Summarization Chain, PDF Analyzer, and Create Final Summary nodes. Ensure the AI models are set up to generate summaries. Google Sheets Integration: Set up Google Sheets credentials in n8n for the Save Summary PDF, Save Summary Image, and Save Summary Text nodes. Specify the Google Sheet and worksheet where the summaries will be saved. Telegram Integration: Set up Telegram credentials in n8n for the Send Final Summary node. Insert your Chat ID in the Telegram node to receive the final summary. Test the Workflow: Send an email with attachments (PDFs and images) to the monitored email account. The workflow will: Extract and summarize the email content and attachments. Save the summaries to Google Sheets. Send a consolidated summary via Telegram. Optional Customization: replace IMAP trigger with Gmail or Outlook trigger Modify the workflow to include additional features, such as: Adding more AI models for different types of analysis. Sending notifications via other channels (e.g., Slack, email). Integrating with other storage services (e.g., Dropbox, AWS S3). Need help customizing? Contact me for consulting and support or add me on Linkedin.
by WeblineIndia
This n8n workflow automates the process of capturing and storing incoming email details in a structured spreadsheet format, such as Google Sheets or Excel. Whenever a new email is received, the workflow extracts key details—including the sender’s email, subject, email body, and optional attachments—and logs them as a new row in the spreadsheet. You can customise this workflow to extract additional details, filter emails based on specific criteria, or send notifications when new entries are added. Pre-conditions & Requirements Before setting up this workflow, ensure that: You have access to the email provider (e.g., Gmail, Outlook, or IMAP-supported email services). The Gmail Node must be enabled in n8n. You must authenticate n8n with Google OAuth2 to access your inbox. Ensure that the Gmail API is enabled in the Google Cloud Console. You have an existing Google Sheet where data will be stored. The Google Sheets API is enabled. You authenticate n8n with your Google account. Steps Step 1: Add the Gmail Trigger Node Click on "Add Node" and search for "Gmail". Select "Gmail Trigger" and click to add it. Under Authentication, click "Create New" and authenticate with your Google account. (If you have already connected your Google account, simply select it.) In the Trigger Event field, select "Message Received". Under Filters, you can specify: Label/Mailbox: If you want to listen to emails from a specific folder (optional). From Address: If you only want to receive emails from specific senders (optional). Click "Execute Node" to test the connection. Click "Save". What This Does: This node listens for new incoming emails in your Gmail inbox. Step 2: Store Email Data in Google Sheets Click on "Add Node" and search for "Google Sheets" (or Microsoft Excel, if applicable) Under Authentication, connect your Google account Select the target Spreadsheet and Sheet Name where the data will be stored Set the Operation to "Append Row" Map the extracted email data to the correct columns. Click "Execute Node" to test and verify data storage Click "Save" What This Does: This node automatically adds a new row for each incoming email, ensuring a structured and searchable email log. Final Step Attach both node and execute the workflow. Who’s behind this? WeblineIndia’s AI development team. We've delivered 3500+ software projects across 25+ countries since 1999. From no-code automations to complex AI systems — our AI team builds tools that drive results. Looking to hire AI developers? Start with us.
by Jonathan
This is the fourth workflow for the Mattermost Standup Bot. This workflow sends the team a message every morning to ask them three standup questions. What have you accomplished since your last report? What do you want to accomplish until your next report? Is anything blocking your progress? Once answered, the answers are sent to a Mattermost channel. The "Read Config" nodes will need to be updated to point to the ID of the "Standup Bot - Read Config" workflow and the "Override Config" node will need to point to "Standup Bot - Override Config"
by Eduard
An example workflow for a multilanguage Telegram bot. It allows adding many new languages to the bot without editing the workflow. Important note! Due to some breaking API changes in NocoDB some of its node options are not working at the moment (MAY 2022). These two nodes were replaced by HTTP request nodes. Functionality is still the same.