Field Sync
Copy field values between work items
Copy Field Values Between Work Items Automate real-time data synchronization between linked Jira issues, subtasks, and epics.
Available for Jira Data Center
Atlassian Marketplace Bug Bounty Program Participant
Sync Across Issue Hierarchy
Automatically propagate field values across your entire Jira hierarchy. Sync data between Parents and Sub-tasks, Epics and Stories, or Roadmaps parents and children. Ensure data consistency from high-level planning down to execution without manual entry.
Sync Linked Issues
Turn standard links into data connections. Automatically copy field values between any issues connected by Jira Issue Links. Keep related items in sync (e.g., Blockers, Duplicates) regardless of their project or issue type.
Precise JQL Configuration
Avoid "automation spam" with granular control. Use JQL (Jira Query Language) to define exactly which issues act as sources and which act as targets. Configure distinct listeners for different projects, issue types, and events to match your exact workflow.
Transitive Sync Chains
Use Transitive Syncs to create deep automation cascades. Configure the system so that one listener's update triggers another, allowing data to flow through complex chains of related issues automatically.
Bulk Sync Existing Data
Don't just fix the future; repair the past. Use the Sync Existing Issues tool to filter a group of Jira issues and trigger updates in bulk. Instantly align historical data with your new synchronization rules.
System & Custom Field Support
Comprehensive data coverage. Field Sync supports copying values for both System Fields (like Priority, Status, Assignee) and Custom Fields, ensuring your unique business data is always replicated accurately.
Tracking Jira Issue History Faster with the Historian AI Assistant
Tired of scrolling through endless Jira changelogs? Meet the Historian AI Assistant! Use natural language to quickly find specific issue updates, filter by user, and reconstruct past project states effortlessly.
Jira Performance Analytics: Measure Throughput, Cycle Time, and Rework
Jira Performance Analytics 101: Measure throughput, cycle time, and lead time to optimize delivery. Identify rework loops and bottlenecks using AI insights
How to Optimize SLA Reporting in Jira: Metrics, JQL, and Contracts
Optimize SLA reporting in JSM with key metrics, JQL functions, and contract management tips. Learn how to track performance, avoid reporting gaps, and scale across projects.