# AtomicWork + Atlassian integration > Stop losing requests in the handoff between your service desk and engineering. Connect AtomicWork with Jira, Confluence, and the rest of the Atlassian ecosystem. **Canonical page:** https://tray.ai/connectors/atomicwork-atlassian-integrations/ **AtomicWork connector:** https://tray.ai/connectors/atomicwork-integrations/ **AtomicWork documentation:** https://tray.ai/documentation/connectors/service/atomicwork **Atlassian connector:** https://tray.ai/connectors/atlassian-integrations/ **Atlassian documentation:** https://tray.ai/documentation/connectors/service/atlassian ## Overview AtomicWork is an AI-powered IT service management platform that handles employee requests, incidents, and support workflows. Atlassian's suite — Jira Software, Jira Service Management, and Confluence — covers engineering planning, project tracking, and documentation. Both do important work, but without an integration, they do it in isolation. Employee requests don't automatically become engineering tickets, status updates don't cross the divide, and someone on your team ends up copy-pasting between systems and chasing down updates. Connecting AtomicWork with Atlassian through tray.ai closes that gap. When IT service management and engineering project tracking run in separate silos, incidents take longer to resolve, priorities get miscommunicated, and neither team can see what the other is doing. With AtomicWork connected to Atlassian via tray.ai, service requests escalate into Jira issues automatically, incident severity and status stay in sync in real time, and employees get updates through AtomicWork while engineers stay in Jira. Confluence knowledge base articles can also stay current with what's actually been resolved in AtomicWork, cutting down repeat support requests. The whole cycle gets faster, accountability improves, and the employee experience gets better — without anyone manually coordinating between IT and development. ## Use cases ### Automatic Escalation of AtomicWork Tickets to Jira Issues When an employee submits a service request or incident in AtomicWork that needs engineering involvement, tray.ai creates a corresponding Jira issue and links it back to the original AtomicWork ticket. Engineers work in Jira. IT agents and employees stay updated in AtomicWork. No manual duplication, no requests slipping through during the handoff. - Eliminates manual copy-pasting of ticket details between AtomicWork and Jira - Maintains a real-time audit trail linking service requests to engineering work items - Routes escalations instantly, cutting mean time to resolution ### Real-Time Incident Sync Between AtomicWork and Jira Service Management When a critical incident is raised in AtomicWork, the integration mirrors it in Jira Service Management with mapped severity, priority, and affected-user data. Status updates from engineers in Jira flow back into AtomicWork, so employees always have a current view of resolution progress. IT agents don't have to manually toggle between systems during high-pressure incidents. - Bidirectional status updates keep all stakeholders informed without manual effort - Reduces incident resolution time by centralizing cross-team coordination - Keeps severity classification consistent across both platforms ### Confluence Knowledge Base Enrichment from Resolved AtomicWork Tickets Once a ticket in AtomicWork is resolved, tray.ai can trigger a workflow that drafts or updates a Confluence knowledge base article with the resolution steps, root cause, and any relevant workarounds. Every solved problem becomes reusable documentation. IT teams review and publish the draft with minimal effort, and the self-service knowledge base grows without anyone having to run documentation sprints. - Converts resolved tickets into structured Confluence documentation automatically - Reduces repeat support volume by getting self-service content in front of employees faster - Keeps the knowledge base current without manual documentation work ### Employee Onboarding Workflow Coordination Across AtomicWork and Jira When a new employee onboarding request is created in AtomicWork, tray.ai automatically generates a set of linked Jira tasks for the IT, HR, and engineering provisioning work that needs to happen. Each task completion reports back into AtomicWork, giving HR and IT managers a unified progress view. No more fragmented checklists slowing down someone's first week. - Automatically creates structured Jira task sets from a single AtomicWork onboarding request - Gives HR and IT a unified onboarding progress view without double entry - Speeds up cross-team provisioning so new employees hit the ground running ### SLA Breach Alerting with Jira and AtomicWork Data When an AtomicWork ticket is approaching or has breached its SLA threshold, tray.ai creates a high-priority Jira issue — or adds a comment to an existing linked issue — to flag the urgency to the engineering team. AtomicWork gets updated with an escalation note and reassigned to a senior agent. No manual monitoring, no ad hoc Slack messages, and a documented trail for post-incident reporting. - Surfaces SLA risks to engineering teams inside Jira before breaches happen - Automates escalation routing in AtomicWork to the right senior resource - Creates a documented escalation trail for post-incident SLA reporting ### Change Request Approval Workflow Between AtomicWork and Jira IT change requests submitted through AtomicWork are automatically forwarded to a Jira change management project for engineering review and approval, with all approval decisions synced back into AtomicWork. Requestors get automated status notifications at each approval stage — no manual relaying required from the IT team. The change advisory board process becomes transparent and auditable across both platforms. - Eliminates manual relay of approval decisions between engineering and IT teams - Gives requestors real-time change approval status inside AtomicWork - Produces a complete, auditable change record that spans both systems ### Sprint and Release Communication Back to AtomicWork Employees When a Jira sprint completes or a release ships that resolves known employee-reported issues, tray.ai automatically updates the corresponding AtomicWork tickets as resolved and sends employees a proactive notification about the fix. The feedback loop between engineering releases and employee experience closes on its own. Employees stay informed, and IT teams don't get flooded with 'is this fixed yet?' requests after every release. - Automatically closes AtomicWork tickets when linked Jira issues move to Done - Sends proactive employee notifications tied to engineering release milestones - Reduces post-release inbound support volume for already-resolved issues ## Templates ### AtomicWork Ticket to Jira Issue Escalation Automatically creates a Jira Software issue whenever an AtomicWork ticket is tagged for engineering escalation, populating it with the original request details, priority, and reporter information, then linking the Jira issue ID back to the AtomicWork ticket for bidirectional traceability. Connectors used: AtomicWork, Atlassian ### Bidirectional Incident Status Sync: AtomicWork and Jira Service Management Keeps incident status, priority, and resolution notes in sync between AtomicWork and Jira Service Management in real time. Updates made in either system are automatically reflected in the other — no manual duplication required. Connectors used: AtomicWork, Atlassian ### Resolved AtomicWork Ticket to Confluence Knowledge Article When an AtomicWork ticket is marked as resolved, this template automatically generates a structured Confluence page draft using the ticket's title, resolution notes, and root cause, then places it in the appropriate knowledge base space for IT team review and publication. Connectors used: AtomicWork, Atlassian ### New Employee Onboarding: AtomicWork Request to Jira Task Set Converts a single employee onboarding request in AtomicWork into a structured set of Jira tasks assigned to the relevant IT, HR, and engineering provisioning teams, with each task completion reported back to AtomicWork for unified progress tracking. Connectors used: AtomicWork, Atlassian ### SLA Breach Escalation from AtomicWork to Jira Monitors AtomicWork ticket SLA timers and automatically creates or updates a linked Jira issue with a high-priority SLA breach flag when a ticket approaches or exceeds its resolution time target, so engineering teams are alerted inside their own workspace. Connectors used: AtomicWork, Atlassian ### Jira Release Completion to AtomicWork Ticket Auto-Resolution When a Jira sprint or release is marked complete, this template automatically identifies linked AtomicWork tickets, updates their status to resolved, and sends employees a proactive notification confirming their reported issue has been addressed. Connectors used: AtomicWork, Atlassian ## Challenges Tray.ai solves ### Maintaining Field Mapping Consistency Across Schema Changes AtomicWork and Jira use different field structures, custom field configurations, and ticket taxonomies — and both drift over time as teams add or rename fields. When schemas change, manual integration scripts break silently, causing incomplete or misrouted ticket data with no visible error to catch it. **How Tray.ai helps:** tray.ai has a visual field mapping interface that makes the relationship between AtomicWork and Jira fields explicit and easy to update without writing code. When a field schema changes, operators can update mappings in the workflow editor in minutes. Built-in data transformation functions handle type mismatches and formatting differences automatically. ### Avoiding Infinite Update Loops in Bidirectional Sync When AtomicWork and Jira are both configured to sync status updates, a change in one system triggers an update in the other, which can fire a webhook back to the first system. Left unchecked, this creates a loop of redundant updates that floods both platforms and can corrupt ticket state. **How Tray.ai helps:** tray.ai workflows support conditional branching logic that inspects the event source and skips processing if the update was itself triggered by the integration. Teams can also use tray.ai's built-in data store to track the last-synced state of each ticket and suppress duplicate writes. ### Handling Authentication and Permission Boundaries Across Atlassian Products Jira Software, Jira Service Management, and Confluence each have separate permission schemes, project-level access controls, and API scopes. A single IT integration may need to touch all three, and managing that authentication with point-to-point custom scripts gets messy fast. **How Tray.ai helps:** tray.ai manages Atlassian OAuth credentials centrally and lets teams configure scoped connections to each Atlassian product from one interface. Workflow steps targeting Jira Software, Jira Service Management, or Confluence each reference the appropriate credential set, and tray.ai handles token refresh automatically so integrations don't fail on expired authentication. ### Scaling Onboarding and Offboarding Workflows Without Manual Coordination Employee onboarding and offboarding involve multiple teams, sequential dependencies, and time-sensitive provisioning tasks spread across AtomicWork and various Jira projects. At scale, coordinating this manually introduces delays, missed steps, and compliance risks when access isn't granted or revoked on schedule. **How Tray.ai helps:** tray.ai supports multi-step, conditional workflow orchestration that can model the full onboarding or offboarding sequence — including wait steps for task approvals, parallel task creation across Jira projects, and progress rollup reporting back to AtomicWork. The entire process runs automatically with error handling and retry logic built in. ### Surfacing AtomicWork Context Inside Jira for Engineering Teams Engineers working in Jira often lack the business context behind an escalated ticket — how many employees are affected, what the original request said, whether there were previous resolution attempts — because that information lives in AtomicWork and doesn't automatically attach to the Jira issue. Engineers end up switching tabs or pinging IT agents for background, and resolution slows down. **How Tray.ai helps:** tray.ai workflows can enrich the Jira issue creation step by pulling full ticket context from AtomicWork — requester details, affected user count, conversation history summary, previous related tickets — and formatting it into the Jira issue description or a linked Confluence page. Engineers get the full picture inside Jira without ever opening AtomicWork. ## Learn more - Intelligent Integration: https://tray.ai/platform/intelligent-ipaas/ - Merlin Agent Builder: https://tray.ai/platform/merlin-agent-builder/ - Agent Gateway for MCP: https://tray.ai/platform/agent-gateway/ - Book a demo: https://tray.ai/contact/