Workflow Templates

🚀 AI-Powered Business Performance Reporting Automation Unlock executive-level insights with ZERO manual work! This n8n template empowers you to automate your entire monthly business performance reporting using dynamic SQL queries, AI-driven analysis, and beautiful HTML dashboards — all delivered directly to your inbox. 🎯 What This Automation Does 📆 Triggers automatically every month (5th of each month) 🧮 Fetches financial data from SQL (ERPNext or any database) 🔁 Loops over cost centers to analyze each business unit individually 📊 Generates Profit & Loss reports, WIP, Employee stats, and vertical breakdowns 🤖 Uses Google Gemini 2.5 AI to perform advanced financial analysis 💌 Delivers a polished HTML report to your email inbox 🔧 Fully modular – replace data source with Excel, Google Sheets, or APIs 🧑‍🏫 Step-by-Step Video Tutorial 🎥 Watch the full tutorial on YouTube: 📌 Learn how each node works and see the AI-generated report in action. 🌐 Useful Links 🔗 Sign up for n8n Cloud (recommended for non-tech users): 👉 https://n8n.syncbricks.com 📘 Download the step-by-step Guidebook (Free): 👉 https://lms.syncbricks.com/books/n8n 📚 Explore the full course on n8n (includes templates, workflows, and AI integrations): 👉 https://lms.syncbricks.com/courses/n8n 🛠 Requirements ✅ n8n (Self-hosted or Cloud) ✅ SQL Database (MySQL / PostgreSQL / ERPNext) ✅ Microsoft Outlook or Gmail (to send the report) ✅ Gemini API Key (for AI analysis) ✅ Basic understanding of your data schema 💡 Why Use This Template? ⏱ Saves 2-3 days of manual work every month 📈 Improves financial visibility across business units 🤝 Great for CFOs, COOs, Finance Analysts, and BI teams 🔄 Scales across multiple divisions and companies 🧠 Leverages AI for actionable insights and recommendations 🧩 Customize It Your Way Replace the SQL nodes with: Excel / Google Sheets Airtable / APIs Custom Applications Swap the AI model: OpenAI GPT Claude DeepSeek Adjust the report structure or HTML style 🙌 Get Started Now 🎯 Import the JSON template → Connect your data → Receive business insights via email. Don’t let manual reporting slow down your decision-making. 👉 Sign up for n8n Cloud 👉 Learn n8n with Amjid 👉 Download Guide Created by Amjid Ali | SyncBricks™ – Automation for Everyone

This n8n workflow automates support ticket handling with AI-driven classification, response generation, and safety checks. Responses are based solely on your Mintlify documentation, ensuring accuracy, consistency, and reduced manual effort in customer support. ✅ Trigger: New Ticket Received The workflow is triggered whenever a new support ticket is created. 🔍 Check for Assignee If the ticket is already assigned to a human agent, the bot does nothing and exits. If the ticket is unassigned, the bot continues processing. 🔢 Bot Response Count Check The workflow checks how many times the bot has already responded to this ticket. If the bot has replied more than 3 times, it stops and waits for a human to take over. This prevents endless loops and flags potentially complex cases for review. 🧠 AI-Based Ticket Categorization An AI model analyzes the ticket content and classifies it into one of the following categories: 🧾 Billing → Sends a predefined billing-related message. 📢 Advertising → Automatically deletes the ticket. 🚨 Fraud → Sends a predefined fraud-related message. ❓ Other → Proceeds to generate a dynamic response. 🤖 Mintlify Integration For tickets categorized as "Other", the customer’s question is sent to the Mintlify API, which returns a documentation-based answer. ✍️ AI Response Formatter The raw response from Mintlify is passed to an AI model that: Summarizes and rewrites the answer in a clear, friendly tone Limits the response to 120 words Adds conversational elements like “Hi,” “Thanks,” and a proper closing 🛡️ AI Confidence Filter A second AI model reviews the formatted response to ensure it sounds confident and accurate. It looks for uncertainty phrases like: “I’m not sure” “I don’t have enough information” “It depends…” If the response is flagged as uncertain, the workflow stops and waits for a human agent to respond. 📤 Send Response & Update Ticket If the response passes the confidence check: The reply is sent to the customer The ticket status is updated to “Pending”

Watch on Youtube▶️ Welcome to this complete step-by-step guide on how to build your own newsletter automation system using n8n, Bolt.new, and RapidAPI. Whether you're a solo founder, indie hacker, or community builder, this setup will allow you to collect subscribers, send them curated job updates, and manage unsubscriptions — all with full control and zero reliance on third-party newsletter tools. 🚀 Goal of This Guide By the end of this guide, you will have a fully working system that allows you to: Collect user subscriptions from a modern frontend interface Send welcome or rejection emails (using your own SMTP) Automatically scrape jobs via an API and send them to subscribers weekly or daily Manage unsubscriptions with confirmation and webhook logic Customize and manage all this using n8n workflows with no-code/low-code skills This system is perfect for niche job boards, community newsletters, or any project that needs automated content delivery to subscribers. 🧱 Tools You'll Be Using n8n** – for automation workflows and acting as your backend Bolt.new** – to build your newsletter landing page and subscription interface Google Sheets** – to act as your lightweight subscriber/job database RapidAPI** – to pull job listings from the Jobs Search API Custom SMTP Email (Optional)** – to send branded emails using your own domain 📄 Step 1: Set Up Your Google Sheets Database Make a copy of this Google Sheets template that will serve as your database: 🔗 Click here to copy the Google Sheet template](https://docs.google.com/spreadsheets/d/11vxYkjfwIrnNHN6PIdAOa_HZdTvMXI0lm_Jecac4YO0/edit?gid=0#gid=0) This includes: A Subscribers sheet to store new signups An Unsubscribers sheet to prevent duplicates A Jobs sheet to store scraped job listings ⚙ Step 2: Get Your API Key for Jobs Scraping We use this API from RapidAPI to pull job listings programmatically: 🔗 Jobs Search API on RapidAPI Sign up or log into RapidAPI Subscribe to the Jobs Search API Copy your API key — you'll need this in n8n ⚙ Step 3: Get Your API Key for Email Validation We use this API from Mails.so to confirm email's validity before adding them to our database: 🔗 Mails.so API Sign up or log into mails dot so Visit the dashboard, then click on API Copy the cURL command and import on http request node 🌐 Step 4: Set Up Your Frontend with Bolt.new You'll be building a beautiful, modern newsletter landing page using Bolt.new. Use this link for prompts to generate: Your landing page Email templates (welcome, already subscribed, unsubscribe confirmation) Terms & Privacy Policy pages Unsubscribe confirmation page 🔗 Access the Bolt.new Prompt Document This includes: A homepage form with input fields (Name, Email) and consent checkbox Logic to send data to n8n webhook using fetch() UI logic for showing webhook response (Success, Already Exists, Invalid Email) Unsubscribe page handling (Make your own copy so that you can edit it while we format the prompts) 📤 Step 5: Set Up Email Sending With Your Custom Domain (Optional but Recommended) To send branded HTML emails from your own domain, follow this tutorial to configure SMTP properly on n8n with your cPanel email account: 🔗 Guide: How to Set Up SMTP with cPanel Email on n8n This setup helps: Improve deliverability Avoid Gmail spam filters Send beautiful HTML emails you can customize fully 🔄 Step 6: Create n8n Workflows for Subscription Management In n8n, you'll need to build these workflows: ✅ 1. Handle Subscriptions Receives webhook from frontend with name and email Validates email (using mails.so) Checks if already subscribed Sends appropriate HTML email (Welcome, Already Exists, Invalid Email) Adds to Google Sheet database ✅ 2. Scrape Jobs and Email Subscribers Use Cron node to run daily/weekly Use RapidAPI to fetch new jobs Format jobs into readable HTML Send jobs to all active subscribers via SMTP ✅ 3. Handle Unsubscriptions Expose a webhook for /unsubscribe Confirm email, show a button On confirmation, add email to Unsubscribers sheet Show feedback and redirect user back to homepage after 2 seconds 🧠 What You're Learning Along the Way How to use n8n as a backend service (reliable, scalable, visual) How to use webhooks to connect frontend and backend logic How to scrape APIs, format JSON data, and convert it to HTML emails How to use Function nodes for data processing How to build logic with IF and Switch nodes How to design a minimal, clean frontend with Bolt.new How to control the entire newsletter system without external platforms Follow me on twitter @juppfy | or check out my agency website.

This workflow extends n8n and uses R language graphic capabilities. This is a Telegram bot which fetches weather data via the openweathermap.org API, plots an image using ggoplot2 package from R and sends the image to the Telegram user.

This n8n workflow serves as a powerful cybersecurity and threat intelligence tool to look up URLs or IP addresses through industry standard threat intelligence vendors. It starts with either a form submission or a webhook trigger, allowing users to input data, URLs or IPs that require analysis. The workflow then splits into two paths depending on whether the input data is an IP or URL. If an IP was given, it sets the ip variable to the IP; however if a URL was given the workflow will perform a DNS lookup using Google Public DNS and sets the ip variable based on the results from Google. The workflow then checks the obtained IP addresses against GreyNoise services, with one branch utilizing GreyNoise RIOT IP Lookup to assess IP reputation and association with known benign services, and the other using GreyNoise IP Context to evaluate potential threats. The results from both GreyNoise services are merged to create a comprehensive analysis which includes the IP, classification (benign, malicious, or unknown), IP location, tags to identify activity or malware, category, and trust level. In parallel, a VirusTotal scan is initiated for the URL/IP to identify if it is malicious. A 5-second wait ensures proper processing, and the workflow subsequently polls the scan result to determine when the analysis is complete. The workflow then summarizes the analysis including the overall security vendor analysis results, blockList analysis, OpenPhish analysis, the URL, and the IP. Finally, the workflow combines the summarized intelligence from both GreyNoise and VirusTotal to provide a thorough analysis of the URL/IP. This summarized intelligence can then be emailed to the user that filled out the form via Gmail or it can be sent to the user via a Slack message. Setting up this workflow may require proper configuration of the form submission or webhook trigger, and ensuring that the GreyNoise and VirusTotal API credentials are correctly integrated. Users should also consider the potential volume of data and API rate limits, as excessive requests could lead to issues. Proper documentation and validation of input data are crucial to ensure accurate and meaningful results in the final report.

This n8n workflow is designed for security monitoring and incident response when suspicious login events are detected. It can be initiated either manually from within the n8n UI for testing or automatically triggered by a webhook when a new login event occurs. The workflow first extracts relevant data from the incoming webhook payload, including the IP address, user agent, timestamp, URL, and user ID. It then splits into three parallel processing paths. In the first path, it queries GreyNoise's Community API to retrieve information about the investigated IP address. Depending on the classification and trust level received from GreyNoise, the alert is given a High, Medium, or Low priority. This priority is assigned based on the best practices documentation from GreyNoise on how to apply their data to analysis. Once a priority is assigned, a message is sent to a Slack channel to notify users about the alert. The second path involves fetching geolocation data about the IP address using IP-API's Geolocation API and merging it with data from the UserParser node. This data is then combined with the data obtained from GreyNoise. In the third path, the UserParser node queries the Userparser IP address and user agent lookup API to obtain information about the user's IP and user agent. This data is merged with the IP-API data and GreyNoise data. The workflow then checks if the IP address is considered an unknown threat by examining both the noise and riot fields from GreyNoise. If it is considered an unknown threat, the workflow proceeds to retrieve the last 10 login records for the same user from a Postgres database. If there are any discrepancies in the login information, indicating a new location or device/browser, the user is informed via email. Potential issues when setting up this workflow include ensuring that credentials are correctly entered for GreyNoise and UserParser nodes, and addressing any discrepancies in the data sources that could lead to false positives or negatives in threat detection. Additionally, the usage of hardcoded API keys should be replaced with credentials for security and flexibility. Thorough testing and validation with sample data are crucial to ensure the workflow performs as expected and aligns with security incident response procedures.

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!

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.

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.

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. 🚀

How it Works This workflow automates the handling of incoming emails, summarizes their content, generates appropriate responses using a retrieval-augmented generation (RAG) approach, and obtains approval or suggestions before sending replies. Below is an explanation of its functionality divided into two main sections: Email Handling and Summarization: The process begins with the Email Trigger (IMAP) node which listens for new emails in a specified inbox. Once an email is received, the Markdown node converts its HTML content into plain text if necessary, followed by the Email Summarization Chain that uses AI to create a concise summary of up to 100 words. Response Generation and Approval: A Write email node generates a professional response based on the summarized content, ensuring brevity and professionalism while keeping within the word limit. Before sending out any automated replies, the system sends these drafts via Gmail for human review and approval through the Gmail node configured with free-text response options. If approved, the finalized email is sent back to the original sender using the Send Email node; otherwise, it loops back for further edits or manual intervention. Additionally, there's a Text Classifier node designed to categorize feedback from humans as either "Approved" or "Declined", guiding whether the email should proceed directly to being sent or require additional editing. Set Up Steps To replicate this workflow within your own n8n environment, follow these essential configuration steps: Configuration: Begin by setting up an n8n instance either locally or via cloud services offered directly from their official site. Import the provided JSON configuration file into your workspace, making sure all required credentials such as IMAP, SMTP, OpenAI API keys, etc., are properly set up under Credentials since multiple nodes rely heavily on external integrations for functionalities like reading emails, generating summaries, crafting replies, and managing approvals. Customization: Adjust parameters according to specific business needs, including but not limited to adjusting the conditions used during conditional checks performed by nodes like Approve?. Modify the template messages given to AI models so they align closely with organizational tone & style preferences while maintaining professionalism expected in business communications. Ensure correct mappings between fields when appending data to external systems where records might need tracking post-interaction completion, such as Google Sheets or similar platforms.

What this workflow does This workflow retrieves Online Marketing data (Google Analytics for several domains, Google Ads, Meta Ads) from the last 7 days and the same period in the previous year. The data is then prepared by AI as a table, analyzed and provided with a small summary. The summary is then sent by email to a desired address and, shortened and summarized again, sent to a Telegram account. This workflow has the following sequence: time trigger (e.g. every Monday at 7 a.m.) retrieval of Online Marketing data from the last 7 days (via sub workflows) assignment and summary of the data retrieval of Online Marketing data from the same time period of the previous year allocation and summary of the data preparation in tabular form and brief analysis by AI. sending the report as an email preparation in short form by AI for Telegram (optional) sending as Telegram message. Requirements The following accesses are required for the workflow: Google Analytics (via Google Analytics API): Documentation Google Ads (via HTTP Request -> Google Ads API):Documentation Meta Ads (via Facebook Graph API): Documentation AI API access (e.g. via OpenAI, Anthropic, Google or Ollama) SMTP access data (for sending the mail) Telegram access data (optional for sending as Telegram message): Documentation You must set up the individual sub-workflows as separate workflows. Then set the “Execute workflow trigger” here. Then select the corresponding sub-workflow in the AI Agent Tools. You can select the number of domains yourself. If the data queries are not required, simply delete the corresponding tool (e.g. “Analytics_Domain_5). Feel free to contact me via LinkedIn, if you have any questions!