Jira Software and Microsoft Outlook integration

Description Synchronize OKRs (Objectives and Key Results) between Monday.com and Jira to automatically calculate progress variance, update dashboards, and share variance reports via Slack and Outlook. This workflow ensures teams have accurate, real-time visibility into performance metrics and project alignment — without manual reconciliation. 🎯📈💬 What This Template Does Step 1: Triggers daily at a scheduled time to fetch the latest OKRs from Monday.com. ⏰ Step 2: Extracts Key Results and their linked Jira epic keys from the OKR board. 🔗 Step 3: Fetches corresponding Jira epic details such as status, assignee, and last updated date. 🧩 Step 4: Merges Monday.com KR data with Jira epic progress through SQL-style joins. 📋 Step 5: Calculates real-time progress and variance against target goals. 📊 Step 6: Updates Monday.com KR items with actual progress, variance percentage, and status (“On Track”, “At Risk”, or “Ahead”). 🔄 Step 7: Aggregates all KR data into a consolidated report for communication. 📦 Step 8: Sends formatted variance reports to Slack and Outlook, with summaries of owner, progress, and variance metrics. 📢 Key Benefits ✅ Automates end-to-end OKR and Jira synchronization ✅ Eliminates manual progress tracking errors ✅ Provides daily visibility on team and project health ✅ Enables proactive risk detection via variance thresholds ✅ Keeps all stakeholders updated via Slack and Outlook ✅ Centralizes OKR performance metrics for reporting Features Daily scheduled trigger for automatic OKR sync Monday.com → Jira data integration via API Real-time variance computation logic Automatic updates of OKR fields in Monday.com SQL-style data merging and aggregation Slack notification with variance summaries Outlook email digest with formatted HTML tables Requirements Monday.com API credentials with board access Jira API credentials with permission to view epics Slack Bot token with chat:write permissions Microsoft Outlook OAuth2 credentials for sending emails Environment variables for board, channel, and recipient configuration Target Audience Product and engineering teams managing OKRs across platforms 🎯 Project managers tracking cross-tool performance metrics 📋 Leadership teams needing automated OKR reporting 💼 Operations and strategy teams monitoring execution health 🧭 Step-by-Step Setup Instructions Connect your Monday.com, Jira, Slack, and Outlook credentials in n8n. 🔑 Replace MONDAY_BOARD_ID, GROUP_ID, and column identifiers with your own. 🧩 Set environment variables for SLACK_CHANNEL_ID and REPORT_RECIPIENT_EMAIL. 💬 Adjust the cron expression to define your sync frequency (e.g., daily at 9 AM). ⏰ Test the workflow with a single OKR item to confirm successful synchronization. 🧠 Enable the workflow to automate daily OKR variance tracking and reporting. ✅

This n8n template watches an outlook shared inbox for support messages and creates an equivalent issue item in JIRA. How it works A scheduled trigger fetches recent Outlook messages from an shared inbox which collects support requests. These support requests are filtered to ensure they are only processed once and their HTML body is converted to markdown for easier parsing. Each support request is then triaged via an AI Agent which adds appropriate labels, assesses priority and summarises a title and description of the original request. Finally, the AI generated values are used to create an issue in JIRA to be actioned. How to use Ensure the messages fetched are solely support requests otherwise you'll need to classify messages before processing them. Specify the labels and priorities to use in the system prompt of the AI agent. Requirements Outlook for incoming support OpenAI for LLM JIRA for issue management Customising this workflow Consider automating more steps after the issue is created such as attempting issue resolution or capacity planning.

Analyze & Sort Suspicious Email Contents with ChatGPT and Jira Who is this for? This workflow is tailored for IT security teams, managed service providers (MSPs), and organizations aiming to streamline the detection and reporting of phishing emails. It's especially useful for teams handling high email volumes and requiring quick, automated analysis. What problem is this workflow solving? Phishing emails pose a significant cybersecurity threat, and manual review processes are time-consuming and prone to human error. This workflow automates the identification of malicious emails, provides AI-driven insights, and generates structured reports, enabling faster and more efficient responses to email-based threats. What this workflow does This workflow integrates Gmail or Microsoft Outlook to monitor and capture incoming emails. It processes the email content and headers, converts the email's body to a visual screenshot for clarity, and uses ChatGPT's advanced AI to analyze the email for phishing indicators. Based on the analysis, it categorizes emails as potentially malicious or benign, creating detailed Jira tickets for each case. Attachments, including the email body and screenshots, are automatically uploaded for comprehensive reporting. Key steps include: Email Integration: Captures emails from Gmail or Microsoft Outlook. Content Processing: Extracts and organizes email content and metadata. AI Analysis: Uses ChatGPT to evaluate email content and headers. Classification: Categorizes emails as malicious or benign. Automated Reporting: Creates Jira tickets with detailed analysis and attachments. Setup Authentication: Configure Gmail or Microsoft Outlook credentials in n8n. API Keys: Add credentials for the HTML screenshot service (hcti.io) and OpenAI. Jira Configuration: Set up project and issue types in the Jira nodes. Customization: Update sticky notes and nodes to fit your organizational requirements, such as modifying the AI prompt or Jira ticket fields. How to customize this workflow to your needs Adjust email triggers to include or exclude specific senders or subjects. Refine the AI prompt in the ChatGPT node to tailor phishing detection criteria. Modify Jira ticket content to include additional fields or match specific workflows. This workflow is ideal for automating email threat detection, reducing response times, and enhancing overall cybersecurity processes. By leveraging AI-powered insights, it helps organizations stay ahead of phishing attacks.

Phishing Email Detection and Reporting with n8n Who is this for? This workflow is designed for IT teams, security professionals, and managed service providers (MSPs) looking to automate the process of detecting, analyzing, and reporting phishing emails. What problem is this workflow solving? Phishing emails are a significant cybersecurity threat, and manually detecting and reporting them is time-consuming and prone to errors. This workflow streamlines the process by automating email analysis, generating detailed reports, and logging incidents in a centralized system like Jira. What this workflow does This workflow automates phishing email detection and reporting by integrating Gmail and Microsoft Outlook email triggers, analyzing the content and headers of incoming emails, and generating Jira tickets for flagged phishing emails. Here’s what happens: Email Triggers: Captures incoming emails from Gmail or Microsoft Outlook. Email Analysis: Extracts email content, headers, and metadata for analysis. HTML Screenshot: Converts the email’s HTML body into a visual screenshot. AI Phishing Detection: Leverages ChatGPT to analyze the email and detect potential phishing indicators. Jira Integration: Automatically creates a Jira ticket with detailed analysis and attaches the email screenshot for review by the security team. Customizable Reports: Includes options to customize ticket descriptions and adapt the workflow to organizational needs. Setup Authentication: Set up Gmail and Microsoft Outlook OAuth credentials in n8n to access your email accounts securely. API Keys: Add API credentials for the HTML screenshot service (hcti.io) and ChatGPT. Jira Integration: Configure your Jira project and issue types in the workflow. Workflow Configuration: Update sticky notes and nodes to include any additional setup or configuration details unique to your system. How to customize this workflow to your needs Email Filters**: Modify email triggers to filter specific subjects or sender addresses. Analysis Scope**: Adjust the ChatGPT prompt to refine phishing detection logic. Integration**: Replace Jira with your preferred ticketing system or modify the ticket fields to include additional information. This workflow provides an end-to-end automated solution for phishing email management, enhancing efficiency and reducing security risks. It’s perfect for teams looking to minimize manual effort and improve incident response times.

Description Automate customer feedback analysis and action planning by integrating Monday.com, Azure OpenAI, Jira, Google Sheets, and Outlook. This workflow classifies customer feedback with AI, calculates business impact, creates Jira tasks for high-priority issues, and sends weekly performance summaries — turning raw feedback into actionable insights. 💬📈🤖 What This Template Does Step 1: Triggers automatically every Monday at 9:00 AM to fetch new customer feedback from Monday.com. ⏰ Step 2: Normalizes and structures data into consistent fields (title, account, ARR, NPS, etc.). 🧩 Step 3: Uses Azure OpenAI GPT-4 to classify sentiment and identify feedback themes (e.g., “UI Design,” “App Crash”). 🧠 Step 4: Calculates a business impact score based on ARR, NPS delta, and sentiment weightings. ⚙️ Step 5: Creates Jira tasks for high-impact feedback items for product or engineering follow-up. 🎫 Step 6: Logs all feedback and impact scores into Google Sheets for analytics dashboards. 📊 Step 7: Generates a professional HTML report summarizing metrics, wins, and risks, then emails it via Outlook. 📧 Step 8: Sends automated error-alert emails if any node fails during execution. 🚨 Key Benefits ✅ Converts qualitative feedback into measurable business intelligence ✅ Identifies critical customer issues automatically using AI ✅ Reduces manual effort in triaging and prioritizing feedback ✅ Creates real-time visibility for product and CX teams ✅ Provides weekly executive summaries and performance insights Features Weekly scheduled trigger (every Monday 9 AM) Monday.com data fetching and field normalization Azure OpenAI GPT-4-based sentiment and theme detection Impact scoring combining ARR + NPS + sentiment weighting Jira issue creation with context-rich descriptions Google Sheets logging for dashboards and historical records Outlook HTML email reports for leadership visibility Automated Gmail error-notification system Requirements Monday.com API credentials with board access Azure OpenAI GPT-4 API credentials Jira Software Cloud API credentials Google Sheets OAuth2 credentials with edit permissions Microsoft Outlook OAuth2 credentials for email delivery Gmail OAuth2 credentials for error alerting Target Audience Product and CX teams analyzing customer sentiment SaaS businesses tracking post-implementation feedback Customer-success and support operations teams Product managers prioritizing improvements based on impact Leadership teams monitoring customer health and satisfaction Step-by-Step Setup Instructions 1️⃣ Connect Monday.com API and update your boardId and groupId. 2️⃣ Configure Azure OpenAI GPT-4 credentials for the AI classifier. 3️⃣ Set Jira project ID and issue type for ticket creation. 4️⃣ Link Google Sheets and replace YOUR_SHEET_ID. 5️⃣ Connect Outlook OAuth2 and add recipient email for reports. 6️⃣ Configure Gmail OAuth2 for error alerts. 7️⃣ Adjust the cron expression (0 9 * * 1) to fit your timezone. 8️⃣ Test the workflow end-to-end with sample data. 9️⃣ Enable automation for seamless weekly feedback intelligence. ✅

This workflow automatically processes customer support requests from emails and web forms, uses AI to classify and either auto-resolve simple issues or intelligently route complex ones to the right team members with proper JIRA tickets and SLA tracking. Key Benefits Multi-channel support (email + web forms) Smart routing to qualified agents based on expertise Consistent ticket creation with full context in JIRA Perfect For Support teams handling 50+ requests/day SaaS companies with tiered customer support Organizations wanting to scale support without hiring Teams needing consistent ticket classification Requirements Microsoft Outlook (email monitoring) OpenAI API (AI classification) JIRA Cloud (ticket management) n8n instance with AI nodes