# Everhour + Jira integration

> Sync time logs, issues, and project data between Everhour and Jira to cut manual entry and keep your team billing-ready.

**Canonical page:** https://tray.ai/connectors/everhour-jira-integrations/
**Everhour connector:** https://tray.ai/connectors/everhour-integrations/
**Everhour documentation:** https://tray.ai/documentation/connectors/service/everhour
**Jira connector:** https://tray.ai/connectors/jira-integrations/
**Jira documentation:** https://tray.ai/documentation/connectors/service/jira

## Overview

Everhour and Jira do two different jobs well. Jira tracks the work; Everhour tracks how long it takes. Used separately, teams end up manually cross-referencing time logs with tickets, sprint reports, and project milestones — which nobody has time for. Integrating Everhour with Jira on tray.ai keeps time entries, issue statuses, and project budgets in sync automatically.

Engineering teams, project managers, and agency leads use Jira to plan, assign, and track work across sprints and releases. But knowing the true cost of that work requires granular time data Jira can't provide on its own. Everhour fills that gap with detailed time tracking at the task, project, and team level. Connect the two through tray.ai and you can automatically create Everhour tasks when new Jira issues open, log time against the right tickets without switching tools, and pull budget burn rates alongside sprint velocity. You get one source of truth for both delivery progress and resource spend — which means smarter capacity planning, more accurate client invoicing, and retrospectives that reflect real hours rather than best guesses.

## Use cases

### Automatic Task Creation from Jira Issues

When a new issue is created in Jira — bug, story, or epic — a matching task is automatically created in Everhour with the same assignee, project, and due date. Every piece of work tracked in Jira is immediately billable and ready for time tracking in Everhour, with no manual setup. Teams stop losing hours to tasks that were never added to the time tracking tool.

- Eliminates manual task duplication between Jira and Everhour
- Every Jira issue is ready for time tracking from day one
- Assignees, labels, and due dates stay consistent across both tools

### Real-Time Time Log Sync to Jira Issues

Time entries logged in Everhour are automatically appended as work logs or comments on the corresponding Jira issue, giving project managers full visibility into hours spent without leaving Jira. Sprint reviews and stakeholder reporting stay accurate without anyone manually entering data twice. Developers log time in their preferred tool; managers see it where they already work.

- Jira issues reflect real hours worked without managers entering anything manually
- Sprint retrospectives use actual time data, not estimates
- Each team member works in their preferred tool without creating gaps in reporting

### Budget Alerts When Jira Projects Approach Limits

When cumulative time logged in Everhour against a Jira project hits a defined budget threshold, tray.ai automatically fires an alert via Slack, email, or a Jira comment to the project lead. That early warning gives stakeholders time to reprioritize or escalate before an overrun happens, rather than discovering it after the fact.

- Early warning notifications prevent budget overruns
- Clients and internal stakeholders stay informed without manual reporting
- Financial oversight ties directly to Jira project scope in real time

### Sprint Completion Reports with Actual vs. Estimated Hours

At the close of every Jira sprint, tray.ai pulls time data from Everhour and compiles an actual-vs-estimated hours report for every issue in the sprint. That report can go to Confluence, get emailed to team leads, or be logged back into Jira as a sprint summary. No one spends hours compiling spreadsheets to get answers that should be automatic.

- Post-sprint reporting runs automatically with no manual data aggregation
- Chronic underestimation patterns become visible at the issue or team level
- Future sprint planning improves with historical velocity and real time data

### Jira Status Changes Trigger Time Tracking Reminders

When a Jira issue moves to In Progress, tray.ai sends the assigned developer a reminder via Slack or email to start their Everhour timer. When an issue moves to Done or Closed, team members get a prompt to stop tracking and confirm their total logged hours. It's a simple nudge, but it closes the gap between task execution and accurate time records.

- Time tracking compliance improves across the engineering team
- End-of-week hour reconstruction becomes rare rather than routine
- Jira workflow transitions connect directly to Everhour timer behavior

### Client Invoicing Powered by Jira Project Time Data

For agencies and consultancies using Jira for client project management, tray.ai can aggregate all Everhour time entries tagged to a specific Jira project or epic and push the summary to an invoicing platform like QuickBooks or Xero. The manual step of exporting time reports and re-entering them into billing software disappears. Invoices go out faster, and clients get accurate, itemized billing tied to real deliverables.

- Project delivery and client billing connect automatically
- Invoice preparation drops from hours to minutes
- Every invoiced hour is traceable back to a specific Jira issue

### New Jira Project Setup Syncs Project Structure to Everhour

When a new Jira project is created, tray.ai automatically replicates its structure — components, epics, and default assignees — into Everhour as a matching project with budget and team members already configured. Finance and delivery teams are aligned from kickoff, not three days later when someone notices the Everhour project doesn't exist yet.

- Everhour projects are ready the moment a Jira project goes live
- Project naming and structure stay consistent across both platforms
- Less onboarding overhead for project managers and team leads

## Templates

### Create Everhour Task When Jira Issue Is Created

Automatically creates a matching Everhour task with the same name, assignee, and due date every time a new issue is added to a specified Jira project, so time tracking is ready from the moment work begins.

Connectors used: Jira, Everhour

### Log Everhour Time Entries as Jira Work Logs

Whenever a time entry is submitted in Everhour, this template posts it as a Jira work log on the linked issue, keeping Jira's time tracking view current for project managers who don't use Everhour directly.

Connectors used: Everhour, Jira

### Send Budget Threshold Alert from Everhour to Jira and Slack

Monitors cumulative time logged in Everhour against a project budget and fires an alert to the relevant Jira project and a Slack channel when a configurable threshold (e.g., 80%) is reached, so stakeholders know before an overrun happens.

Connectors used: Everhour, Jira

### Generate Sprint Time Report When Jira Sprint Closes

At the end of each sprint, this template pulls all Everhour time entries for issues in that sprint, calculates actual vs. estimated hours per issue, and emails a formatted summary report to the project lead.

Connectors used: Jira, Everhour

### Remind Assignee to Track Time When Jira Issue Goes In Progress

When a Jira issue status changes to In Progress, this template sends the assignee a direct Slack message or email reminder to start their Everhour timer — without any manager having to follow up manually.

Connectors used: Jira, Everhour

### Sync New Jira Project to Everhour with Budget Configuration

Whenever a new Jira project is provisioned, this template automatically creates a matching Everhour project, assigns the relevant team members, and sets an initial budget based on a predefined template or custom field value in Jira.

Connectors used: Jira, Everhour

## Challenges Tray.ai solves

### Keeping Issue IDs Linked Across Both Platforms

Everhour and Jira use different internal identifiers for tasks and issues. Without a reliable mapping layer, time entries can be logged against the wrong task or go unlinked entirely, causing reporting errors and billing discrepancies.

**How Tray.ai helps:** tray.ai maintains a persistent mapping between Jira issue IDs and Everhour task IDs using workflow state and intermediate data storage. Every time a Jira issue triggers a workflow, the corresponding Everhour task ID is looked up or created and stored, so all downstream actions reference the correct record in each system.

### Handling Jira Issue Updates After Everhour Tasks Are Created

Jira issues change constantly — assignees get swapped, due dates shift, summaries get edited — but those changes rarely make it to Everhour, leaving stale or mismatched task data in the time tracking tool.

**How Tray.ai helps:** tray.ai listens for Jira issue update webhooks and selectively syncs changed fields to the corresponding Everhour task. Conditional logic in the workflow ensures only meaningful changes (like assignee or due date) trigger an update, avoiding unnecessary API calls and rate limit issues.

### Reconciling Time Entries Logged in Both Tools

Some teams enter time directly in Jira's native time tracking fields and in Everhour, creating duplicate or conflicting records that skew project cost reports and sprint velocity metrics.

**How Tray.ai helps:** tray.ai can be configured to treat Everhour as the single source of truth for time tracking and ignore Jira-native time fields in reporting workflows. Deduplication logic checks for existing work logs before writing new entries, and reconciliation workflows can flag conflicts for manual review.

### Managing High-Volume Jira Environments at Scale

Enterprise teams with thousands of Jira issues and hundreds of daily status transitions can overwhelm basic integration approaches, causing webhook backlogs, missed events, and delayed time tracking reminders.

**How Tray.ai helps:** tray.ai handles high-throughput webhook ingestion with built-in queuing, retry logic, and parallel execution. Workflows can be filtered at the trigger level to process only relevant projects, issue types, or assignees, cutting down unnecessary processing overhead significantly.

### Surfacing Everhour Budget Data Without Disrupting Jira Workflows

Finance and account management teams need budget burn data from Everhour, but they live in Jira and don't want to switch tools just to check hours against project budgets.

**How Tray.ai helps:** tray.ai runs scheduled or event-driven workflows that pull Everhour budget summaries and push them directly into Jira as issue comments, custom field updates, or Confluence page entries. Stakeholders get the financial data they need inside the tools they already use, with no manual exports required.

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