by Akshay Chug
Overview Your inbox shouldn't run your day. This workflow checks Gmail every 15 minutes, uses Claude AI to classify every new email into Urgent, Needs Reply, FYI Only, Automated, or Spam — then takes the right action automatically: Slack alert for urgent, draft reply saved for action needed, label and archive for everything else. Every email logged to Google Sheets. How it works Polls Gmail every 15 minutes for new unread emails Claude Sonnet reads each email and classifies it into one of five categories Urgent emails trigger an immediate Slack alert with sender, subject and summary Needs Reply emails get a Claude-written draft saved to Gmail drafts ready for one-click send FYI Only emails get labelled and marked as read automatically Automated emails (newsletters, receipts, notifications) get labelled and archived Spam gets moved to trash Every email processed is logged to Google Sheets with category and reasoning Setup steps Gmail — Connect your Gmail account in Check for New Emails, and all action nodes Gmail labels — Create four labels in Gmail: AI-Urgent, AI-Needs-Reply, AI-FYI, AI-Automated. Copy each label ID into the corresponding label node Claude AI — Add your Anthropic API key to the Claude Sonnet sub-node from console.anthropic.com Slack — Connect your Slack account in Notify Urgent Email and set your channel. Disable this node if you do not use Slack Customise the prompt — Open Classify Email Intent and add your name, role, and any VIP senders that should always route as Urgent Google Sheets — Create a sheet called Email Log with columns: Timestamp, Sender, Subject, Category, Summary, Reasoning, Draft Saved Activate — runs every 15 minutes automatically
by Cheng Siong Chin
How It Works This workflow automates competitive intelligence gathering and market analysis for businesses needing real-time insights on competitors, industry trends, and market positioning. Designed for marketing teams, strategy analysts, and business development professionals, it solves the time-intensive challenge of manually monitoring competitor activities across multiple channels. The system schedules regular data collection, fetches competitor information from various sources, employs multiple AI agents (OpenAI for analysis, sentiment evaluation, and report generation) to process data, validates outputs through structured parsing, and delivers comprehensive reports via email. By automating data aggregation, sentiment analysis, and insight generation, organizations gain actionable intelligence faster, identify market opportunities proactively, and maintain competitive advantage through continuous monitoring—essential for dynamic markets where timing determines success. Setup Steps Connect Schedule Trigger (set monitoring frequency: daily/weekly) Configure Fetch Data node with competitor website URLs/APIs Add OpenAI API keys to all AI agent nodes Link Google Sheets credentials for storing historical analysis data Configure Gmail node with SMTP credentials for report distribution Set up Slack/Discord webhooks for instant critical alert notifications Prerequisites OpenAI API account (GPT-4 recommended), competitor data sources/APIs Use Cases SaaS competitor feature tracking, retail pricing intelligence Customization Modify AI prompts for industry-specific metrics, adjust sentiment thresholds for alert triggers Benefits Reduces research time by 85%, provides 24/7 competitor monitoring, eliminates manual data aggregation
by Harshil Khunt
Quick overview This workflow automates invoicing and payment follow-ups using Google Sheets, PDFShift, Groq (LLM), Gmail, and Telegram, sending initial invoices with PDF attachments, scheduling overdue reminders at 9am, and letting you mark invoices as paid via a Telegram command with automatic thank-you emails and sheet updates. How it works Triggers when a new row is added to a Google Sheets “Client Invoices” spreadsheet to start the invoice-sending flow. Generates an HTML invoice, converts it to a PDF via the PDFShift API, and uses Groq to draft a short invoice email. Sends the invoice email via Gmail with the generated PDF attached, then updates the Google Sheet to set Status to Unpaid and log the send date. Runs every morning at 9am, reads all invoices from Google Sheets, filters for Status = Unpaid, and calculates how many days each invoice is overdue. Routes each unpaid invoice to a 7-day, 14-day, or 30-day reminder track based on overdue days and whether prior reminders were already sent. Uses Groq to write the appropriate reminder email, sends it via Gmail, posts a notification to Telegram, and updates the Google Sheet to flag the reminder as sent. Triggers on incoming Telegram messages, parses commands starting with “paid”, looks up the matching client in Google Sheets, marks the invoice as Paid, emails the client a thank-you via Gmail, and confirms back on Telegram (or sends a “client not found” message). Setup Connect credentials for Google Sheets (read/update and trigger), Gmail, Telegram, and Groq. Add PDFShift credentials as HTTP Basic Auth for the PDF conversion request (or replace the PDF generation step with your preferred PDF service). Create/confirm the Google Sheets columns used by the workflow, including Client Name, Client Email, Service, Amount, Invoice Date, Due Date, Status, Notes, First Reminder Sent, Second Reminder Sent, and Final Notice Sent (and optional Currency). Update the Google Sheets document ID/sheet tab, and set the Telegram chat ID(s) used for owner notifications and bot replies. Adjust the schedule trigger time (9am) and reminder thresholds (7/14/30 days) and email wording/subjects as needed for your billing policy.
by Davide
This workflow automates the creation, assignment, tracking, and monitoring of tasks (issues) inside a Paperclip system using AI and external integrations. View this Youtube Video Tutorial to setup your Paperclip instance for FREE and get API Key (subtitles in English). ✅ Key Advantages 1. ✅ Full Automation of Task Lifecycle The workflow handles everything: Task intake → assignment → tracking → completion notification No manual intervention is required. 2. ✅ AI-Powered Task Assignment Using an LLM: Tasks are assigned intelligently based on context Reduces human decision-making errors Scales easily with more agents 3. ✅ Centralized Tracking with Google Sheets Acts as a lightweight database Easy to audit, monitor, and share Provides historical tracking of tasks 4. ✅ Real-Time Monitoring & Alerts Scheduled checks ensure tasks are constantly monitored Instant email notifications when tasks are completed Improves responsiveness and visibility 5. ✅ Modular & Scalable Architecture Each block (Webhook, AI, API, Sheets, Email) is independent Easy to extend (e.g., Slack alerts, dashboards, analytics) Can integrate with other systems without redesigning everything 6. ✅ Efficient Resource Utilization Batch processing (Split in Batches) avoids overload Scheduled execution reduces unnecessary API calls 7. ✅ Seamless API Integration Connects Paperclip, OpenAI, Google Sheets, and Gmail Demonstrates strong interoperability across services How it works This workflow automates the assignment and tracking of issues/tasks to AI agents (called "Paperclip agents") and monitors their completion. Two main flows: Issue creation WF (triggered via Webhook or Manual): Receives a task with title and issue via webhook Fetches the company ID from the Paperclip API Retrieves all available Paperclip agents for that company Normalizes agent data (id, name, title) Uses GPT-5-mini to intelligently assign the task to the most appropriate agent Creates a new issue in Paperclip with the assigned agent Logs the issue to a Google Sheet with metadata (date, ID, title, issue, assigned agent) Completion monitoring WF (runs every 10 minutes via Schedule Trigger): Fetches all open issues (where COMPLETED column is empty) from Google Sheets Loops through each open issue Checks the current status of each issue in Paperclip API If status is "completed", sends a Gmail alert and updates the COMPLETED column in Sheets with the completion timestamp Set up steps API Credentials: Configure httpBearerAuth credentialwith your Paperclip API key Set up openAiApi credential Configure gmailOAuth2 credential for sending completion alerts Set up googleSheetsOAuth2Api credential for Sheets access Google Sheets Setup: Clone this Sheet Sheet must contain columns: DATE, TITLE, ISSUE, ASSIGN, ID, COMPLETED Share the sheet with the service account or OAuth account used in credentials Paperclip API Configuration: Replace all https://paperclip.xxx.xxx URLs with your actual Paperclip instance URL Verify the /api/agents/me, /api/companies/{id}/agents, and /api/issues/{id} endpoints are accessible Workflow Settings: Webhook path is auto-generated – copy this for external calls Update the Gmail recipient from xxx@xxx.xxx to your target email address Adjust schedule trigger interval (currently 10 minutes) as needed Testing: Activate the workflow Use the Manual Trigger or send a POST request to the webhook URL with payload containing title and issue fields Monitor execution logs to verify agent assignment and issue creation 👉 Subscribe to my new YouTube channel. Here I’ll share videos and Shorts with practical tutorials and FREE templates for n8n. Need help customizing? Contact me for consulting and support or add me on Linkedin.
by Bernhard Zindel
Summarize Google Alerts with Gemini Turn your noisy Google Alerts folder into a concise, AI-curated executive briefing. This workflow replaces dozens of individual notification emails with a single, structured daily digest. How it works Ingest:** Fetches unread Google Alerts emails from your Gmail inbox. Clean:** Extracts article links, scrapes the website content, and strips away ads and clutter to ensure high-quality AI processing. Analyze:** Uses Google Gemini to summarize each article into a concise 2-4 sentence overview. Deliver:** Compiles a professional HTML email report sorted by topic, sends it to you, and automatically marks the original alerts as read. Set up steps Connect Gmail:** Authenticate your Gmail account to allow reading alerts and sending the digest. Connect Gemini:** Add your Google Gemini API key. Configure Recipient:* Update the *Send Email Digest** node with your desired destination email address. Schedule:* (Optional) Replace the Manual Trigger with a *Schedule Trigger** (e.g., every morning at 7 AM) to fully automate the process.
by Cheng Siong Chin
How It Works Automates daily learner engagement monitoring, progress analysis, and personalized feedback delivery for training programs. Target audience: learning and development teams, corporate training managers, and online education platforms scaling instructor workload. Problem solved: manual progress tracking consumes instructor time; AI analysis identifies struggling learners early for intervention. Workflow runs daily checks on learner activity, retrieves course data and progress, analyzes engagement with OpenAI models, evaluates quiz scores, generates performance summaries, sends progress reports to learners, emails instructors on at-risk cases, generates learning paths, and triggers manager notifications. Setup Steps Configure daily schedule trigger. Connect learning management system APIs (LMS). Set OpenAI keys for progress analysis. Enable Gmail for multi-recipient notifications. Map learner risk thresholds and escalation rules. Prerequisites LMS platform credentials, OpenAI API key, learner database, email service for notifications, manager contact lists. Use Cases Corporate onboarding programs tracking employee progress, online learning platforms identifying struggling students Customization Adjust AI analysis criteria for your curriculum. Integrate Slack for instructor alerts. Benefits Reduces instructor workload by 70%, identifies at-risk learners 2 weeks early
by WeblineIndia
AI-Powered Risk Monitor: Negative News Tracker This workflow acts as an automated early-warning system for corporate risk. It pulls a list of companies from a Google Sheet, uses SerpAPI to scout the latest global news and employs Groq-powered AI to detect negative sentiment (such as lawsuits, layoffs or financial declines). New risks are archived in a master database and immediate Gmail alerts are sent for any confirmed negative news, ensuring you never miss a critical market signal. Quick Implementation Steps Import: Upload the JSON file into your n8n workflow editor. Authenticate**: Connect your Google Sheets, SerpAPI, Groq and Gmail credentials. Prepare Watchlist: Create a Google Sheet with a column named **Companies and add the entities you want to monitor. Set Database: Create a second sheet (or tab) with headers: **ID, Company, Title, Date, Reason, Severity, Link. Activate: Click **Start Workflow to run a manual check or add a Schedule Trigger for 24/7 monitoring. What It Does This workflow automates the tedious process of manual "reputation monitoring." It starts by reading a list of target companies from your Watchlist. For every company found, it performs a real-time Google News search via SerpAPI. To handle high volumes of data efficiently, it aggregates all found articles into a single stream, standardizes the formatting and generates a unique digital fingerprint (ID) for every story. The "intelligence" of the workflow lies in its deduplication and AI analysis. It cross-references every new article ID against your Processed News spreadsheet; if an article has been seen before, it is discarded. Only 100% new content reaches the Groq AI engine. The AI then acts as a financial analyst, reading the headline to determine if the news is truly negative and assigning a severity level (Low, Medium or High). Finally, the workflow acts on these insights. If the AI flags an article as negative, the data is appended to your tracking sheet for long-term auditing and a formatted HTML email is sent via Gmail to your team, containing the reasoning, severity and a direct link to the source article. Who It's For Investment Analysts** needing to track portfolio companies for "black swan" events. PR & Communications Teams** monitoring brand reputation and crisis management. Legal & Compliance Officers** tracking litigation or regulatory investigations involving partners. Sales Professionals** looking for "trigger events" (like management changes or losses) to adjust their strategy. Requirements to use this workflow n8n account: (Self-hosted or Cloud). Google Account**: For accessing Watchlists and sending Gmail alerts. SerpAPI Key**: To fetch live Google News results. Groq API Key**: To power the high-speed sentiment analysis. How It Works & Setup Guide 1. Watchlist & Credentials Ensure your Google Sheets account is connected. Your Read Watchlist node should point to a sheet where company names are listed under a header named Companies. 2. Search API Configuration Open the Fetch News node and ensure your SerpAPI key is entered in the query parameters. This node is configured to search Google News (tbm=nws) dynamically based on the company names from your list. 3. Deduplication Logic The Process Articles node uses a JavaScript snippet to create a unique ID based on the title and link. This prevents you from receiving the same alert twice if a news story stays on the front page for multiple days. 4. AI Analysis & Throttling The Analyze News node uses the Groq Chat Model. Because AI APIs can sometimes be overwhelmed by rapid requests, a Throttle API Calls node is included to pause for 2 seconds between articles, ensuring stability. 5. Filtering & Alerting The Filter Negative News node is the gatekeeper. It only allows items where the AI has explicitly set is_negative to true. These items are then saved to your database and emailed to you. How To Customize Nodes Adjust Severity: While the workflow currently alerts on all negative news, you can modify the **Filter Negative News node to only allow severity == 'high' if you only want to see major crises. Refine AI Prompt: Edit the **Analyze News node to add specific keywords relevant to your industry (e.g., "clinical trial failure" for Biotech or "data breach" for Tech). Email Branding: Open the **Send Alert node to change the HTML styling or to add your company logo to the notifications. Add‑ons Slack/Teams Integration**: Add a Slack node alongside Gmail to post risk alerts into a specific "Crisis-Monitor" channel. AI Summary**: Add a second AI step to summarize the full article content if the headline analysis suggests high severity. Automated Scheduling: Replace the Manual Trigger with a **Schedule Trigger to run the tracker every hour or at the start of every business day. Use Case Examples Competitor Intelligence**: Tracking when competitors face lawsuits or product recalls. Vendor Risk Management**: Monitoring key suppliers for signs of financial distress or strikes. E-Commerce Monitoring**: Tracking news about major shipping partners or payment processors. M&A Due Diligence**: Automating the "bad news" search for companies currently under acquisition review. Public Figure Tracking**: Monitoring news for specific high-profile individuals or executives. Troubleshooting Guide | Issue | Possible Cause | Solution | | :--- | :--- | :--- | | No news being fetched | SerpAPI key missing or expired | Check the Fetch News node execution logs for a 401 or 403 error code. | | Duplicate alerts received | Sheet ID column mismatch | Ensure the Lookup Existing Articles node is looking at the correct column (ID) in your Google Sheet. | | AI fails to parse JSON | Prompt deviation | Ensure the Structured Output Parser is connected to the Analyze News node to enforce JSON formatting. | | Workflow is too slow | Throttle settings | If you have a high-tier Groq account, you can reduce the Throttle API Calls timer from 2 seconds to 0.5 seconds. | Need Help? Configuring real-time AI monitors requires a balance of speed and accuracy. If you need help tailoring the deduplication logic, expanding your watchlist or connecting these alerts to a professional CRM like Salesforce or HubSpot, we are here to assist. Contact WeblineIndia to help you build, customize or scale your business automation today!
by Cheng Siong Chin
How It Works This workflow automates athlete performance monitoring through two parallel pipelines: real-time session analysis triggered by training form submissions, and scheduled weekly performance summaries. Designed for sports coaches, athletic trainers, and performance analysts, it eliminates manual data aggregation and ensures threshold breaches and weekly trends are communicated instantly. A training session form submission stores the record to Google Sheets, fetches historical data, and combines both inputs for a Performance Analysis Agent. OpenAI analyses the combined data, updates the sheet with insights, then checks performance thresholds—triggering Slack alerts or email notifications on breach. In parallel, a weekly schedule fetches all athlete data, groups by athlete, and passes to a Weekly Summary Agent that distributes summaries via both Slack and email. Setup Steps Configure Training Session Form fields to match athlete and session data schema. Connect Google Sheets credentials to Store, Fetch, and Update Record nodes. Add OpenAI API credentials to Performance Analysis and Weekly Summary Agent nodes. Configure Slack credentials and set coaching team alert and summary channels. Add Gmail/SMTP credentials to Send Email Alert and Weekly Summary Email nodes. Define performance threshold values in the Check Performance Threshold node. Prerequisites Google Sheets with service account credentials Slack workspace with bot token Gmail or SMTP credentials Use Cases Real-time performance threshold alerts for elite athlete training programmes Customization Replace OpenAI with Anthropic Claude for analysis and summary agents Benefits Automates session analysis and insight storage immediately after each training entry
by Unfenced Group
Quick Overview This workflow runs a SEEK.com.au job search via Apify on a daily schedule or on-demand form submission, deduplicates new listings, and routes results to Google Sheets, Airtable, a webhook endpoint, and digest notifications to Slack, Telegram, Discord, and Gmail. How it works Runs daily at 7 AM or starts when you submit the built-in n8n form with your SEEK search parameters. Sends the search criteria to the Apify “unfenced-group/seek-com-au-scraper” actor and retrieves the job results. Normalises each job into consistent fields (including an annualised salary estimate) and removes duplicates within the run and across previous executions. Aggregates all newly found jobs and formats a single digest message for Slack, Telegram, Discord, and email. Sends the digest to the enabled channels (Slack, Telegram, Discord webhook, and/or Gmail) based on the destination values you provided. Splits the new jobs back into individual items and, if enabled, appends/updates rows in Google Sheets, creates records in Airtable, and/or POSTs each job to your webhook URL. If the scraper returns no data and a notify URL is set, POSTs a “seek_no_results” alert to that endpoint. Setup Add an Apify credential with an API token and ensure the workflow can run the “unfenced-group/seek-com-au-scraper” actor. For scheduled runs, edit the “Scheduled Defaults” values (search query, location, days back, max results) and set any destination fields you want to use (leave as YOUR_XXX or blank to skip). If using Google Sheets, add a Google Sheets OAuth2 credential, set your spreadsheet ID and tab name, and ensure there is a URL column for matching updates. If using Airtable, add an Airtable personal access token, set the base/table IDs, and create fields that match the mapped column names (Title, Company, Location, URL, Salary Annual, etc.). If using Slack, Gmail, or Telegram, add the respective OAuth/bot credentials and set the Slack channel name, recipient email address, and Telegram chat ID. If using webhooks (generic webhook, Discord, or failure notifications), paste the target webhook URLs into webhookUrl, discordWebhookUrl, and/or notifyUrl.
by Cheng Siong Chin
How It Works This workflow automates quality event risk assessment through AI-powered multi-agent analysis with mandatory human oversight for critical decisions. Designed for quality managers, compliance officers, and risk analysts in manufacturing, healthcare, or service industries, it solves the challenge of consistent, transparent risk evaluation while maintaining human accountability. When quality events are detected, the system orchestrates specialized AI agents (traceability, risk assessment, and recall evaluation) to analyze different risk dimensions simultaneously. Results are synthesized, routed through human approval gates based on risk severity, and distributed via automated notifications. This ensures high-risk decisions receive proper scrutiny while low-risk events flow efficiently through automated channels. Setup Steps Configure NVIDIA NIM API credentials with Llama-3.1-70B-Instruct model access Set up routing logic thresholds Connect Gmail SMTP for executive alerts and Slack webhook for team notifications Configure human approval nodes with designated approver email addresses Customize AI agent prompts for industry-specific risk criteria Prerequisites NVIDIA NIM API key, Gmail account with app password Use Cases Manufacturing defect escalation, food safety incident management Customization Modify risk scoring thresholds, add industry-specific compliance agents Benefits Reduces risk assessment time by 75%, ensures consistent evaluation methodology
by Avkash Kakdiya
Quick overview This workflow triggers on HubSpot dealstage changes, pulls full deal, contact, and owner details, uses OpenAI to generate a concise Slack-ready update with next steps, notifies the right Slack channel or emails the owner for ClosedWon, logs the event to Google Sheets, and writes a note back to HubSpot. How it works Triggers in HubSpot whenever a deal property changes and continues only when the changed property is the deal stage. Retrieves the full deal record from HubSpot, formats key fields (stage label, value, close date, won/lost flags), and builds an AI prompt. Sends the prompt to OpenAI to generate a 3–4 sentence stage-change summary with two actionable next steps. Posts the AI summary to Slack, routing high-value deals to a leadership channel and other deals to the sales team channel. Appends a structured log entry (deal, stage, owner/contact, value, close date, AI summary, timestamp) to Google Sheets. Fetches the HubSpot owner and contact details to enrich downstream messages, then sends a Gmail congratulations email for Closed Won deals or a Slack loss alert with the loss reason for Closed Lost deals. Creates a note in HubSpot containing the stage-change notification and AI summary, and associates the note with the deal. Setup Connect your HubSpot Trigger credentials and add an HTTP header auth credential for HubSpot API calls to owners, contacts, notes creation, and note-to-deal association endpoints. Connect your OpenAI credential and select a model in the OpenAI node. Connect your Slack OAuth2 credential and update the target channels/messages for leadership, sales, loss alerts, and error alerts. Connect your Gmail credential for sending Closed Won emails and ensure deal owners in HubSpot have an email address. Connect your Google Sheets credential and replace the document ID with your spreadsheet ID (and confirm the target sheet name and columns).
by Yassin Zehar
Description This workflow turns scattered user feedback into a structured product backlog pipeline. It collects feedback from three channels (Telegram bot, Google Form/Sheets, and Gmail), normalizes it, and sends it to an AI model that: Classifies the feedback (bug, feature request, question, etc.) Extracts sentiment and pain level Estimates business impact and implementation effort Generates a short summary Then a custom RICE-style priority score is computed, a Jira ticket is created automatically, a Notion page is generated for documentation, and a monthly product report is sent by email to stakeholders. It helps product & support teams move from “random feedback in multiple tools” to a repeatable, data-driven product intake process with zero manual triage. Context In most teams, feedback is: spread across emails, forms, and chat messages manually copy–pasted into Jira (when someone remembers) hard to prioritize objectively nearly impossible to review at the end of the month This workflow solves that by: Centralizing feedback from Telegram, Google Forms/Sheets, and Gmail Automatically normalizing all inputs into the same JSON structure Using AI to categorize, tag, summarize, and score each request Calculating a RICE-based priority adapted to your tiers (free / pro / enterprise) Creating a Jira issue with all the context and acceptance criteria Generating a Notion page for each feedback+ticket pair Sending a monthly “Product Intelligence Report” by email with insights & recommendations The result: less manual work, better prioritization, and a clear story of what users are asking for. Target Users This template is designed for: Product Managers and Product Owners SaaS teams with multiple feedback channels Support / CS teams that need a structured escalation path Project Managers who want objective, data-driven prioritization Any team that wants “feedback → backlog” automation without building a custom platform Technical Requirements You’ll need: Google Sheets credential Gmail credential Telegram Bot + Chat ID Google Form connected to a Google Sheet Jira credential (Jira Cloud) Notion credential OpenAI/ Anthropic credential for the AI analysis node An existing Jira project where tickets will be created A Notion database or parent page where feedback pages will be stored Workflow Steps The workflow is organized into four main sections: 1) Triggers (Multi-channel Intake) Telegram Trigger – Listens for new messages sent to your bot Google Form / Sheet Trigger – Listens for new form responses / rows Gmail Trigger – Listens for new emails matching your filter (e.g. [Feedback] in subject) All three paths send their payloads into a “Data Normalizer” node that outputs a unified structure: 2) Request Treated and Enriched (AI Analysis) Instant Reply (Telegram only) – Sends a quick “Thanks, we’re analysing your feedback” message User Enrichment – Enriches user tier based on mapping Message a Model (AI) classifies the feedback extracts tags scores sentiment, pain, business impact, effort generates a short summary & acceptance criteria JSON Parse / Merge – Merges AI output back into the original feedback object 3) Priority Calculation & Jira Ticket Creation Priority Calculator applies a RICE-style formula using: pain level business impact implementation effort user tier weight assigns internal priority: P0 / P1 / P2 / P3 maps to Jira priority: Highest / High / Medium / Low Create Jira Issue – Creates a ticket with: summary from AI description including raw feedback, AI analysis, and RICE breakdown labels based on tags priority based on the calculator Post-processing – Prepares a clean payload for notifications & logging IF (Source = Telegram) – Sends a rich Telegram message back to the user with: Jira key + URL category, priority, RICE score, tags, and estimated handling time Append to Google Sheet (Analytics Log) – Logs each feedback with: source, user, category, sentiment, RICE score, priority, Jira key, Jira URL Create Notion Page – Creates a documentation page linking: the feedback the Jira ticket AI analysis acceptance criteria 4) Monthly Reporting (Product Intelligence Report) Monthly Trigger – Runs once a month Query Google Sheet – Fetches all feedback logs for the previous month Aggregate Monthly Stats – Computes: feedback volume breakdown by category / sentiment / source / tier / priority average RICE, pain, and impact top P0/P1 issues and top feature requests Message a Model (AI) – Generates a written “Product Intelligence Report” with: executive summary key insights & trends top pain points strategic recommendations Parse Response: Extracts structured insights + short summary Create Notion Report Page with: metrics, charts-ready tables, insights, and recommendations Append Monthly Log to Google Sheet – Stores high-level stats for historical tracking Send Email with a formatted HTML report to stakeholders with: key metrics top issues recommendations link to the full Notion report Key Features Multi-channel intake: Telegram + Google Forms/Sheets + Gmail AI-powered triage: automatic category, sentiment, tags, and summary RICE-style priority scoring with tier weighting Automatic Jira ticket creation with full context Notion documentation for each feedback and for monthly reports Google Sheets analytics log for exploration and dashboards Monthly “Product Intelligence Report” sent automatically by email Designed to be adaptable: you can plug in your own labels, tiers, and scoring rules Expected Output When the workflow is running, you can expect: A Jira issue created automatically for each relevant feedback A confirmation email A Telegram confirmation message when the feedback comes from Telegram A Google Sheet filled with normalized feedback and scoring data A Notion page per feedback/ticket with AI analysis and acceptance criteria Every month: a Notion “Monthly Product Intelligence Report” page a summary email with key metrics and insights for your stakeholders How it works Trigger – Listens to Telegram / Google Forms / Gmail Normalize – Converts all inputs to a unified feedback format Enrich with AI – Category, sentiment, pain, impact, effort, tags, summary Score – Computes RICE-style priority and maps to Jira priority Create Ticket – Opens a Jira issue + Notion page + logs to Google Sheets Notify – Sends Telegram confirmation (if source is Telegram) Report – Once a month, aggregates everything and sends a Product Intelligence Report Tutorial Video Tutorial video: Watch the Youtube Tutorial video About me I’m Yassin a Project & Product Manager Scaling tech products with data-driven project management. 📬 Feel free to connect with me on Linkedin