Connectors / Integration
Connect Harvest and Jira to Put Time Tracking and Project Management in Sync
Automatically sync time entries, issues, and project data between Harvest and Jira so your teams stay on the same page without manual data entry.
Harvest + Jira integration
Harvest and Jira are two of the most widely used tools in software and professional services teams — Harvest for time tracking and invoicing, Jira for issue tracking and agile project management. When they're not connected, teams end up manually logging hours against tickets, reconciling project budgets with sprint progress, and pulling reports from two separate platforms. Integrating Harvest with Jira cuts out that friction by creating a direct data bridge between your time tracking and project workflows.
Connecting Harvest and Jira pays off fast for engineering, product, and client services teams. When a developer logs time against a Jira issue, that data flows into Harvest automatically to update project budgets and client billing records — no double entry. Project managers get a real-time view of hours per epic, sprint, or ticket alongside their Jira boards, which makes forecasting and resource planning a lot more reliable. Finance and account teams get cleaner billing because every billable hour is captured the moment work is logged. Automating the sync between these two systems cuts admin overhead, reduces billing errors, and means your project profitability data is always current.
Automate & integrate Harvest + Jira
Automating Harvest and Jira business processes or integrating data is made easy with Tray.ai.
Use case
Automatic Time Entry Sync from Jira to Harvest
When a developer logs a work log on a Jira issue, tray.ai automatically creates a matching time entry in Harvest against the right project and task. Engineers don't have to context-switch between tools just to record hours, so time capture goes up without adding work.
- Eliminates duplicate time logging across Jira and Harvest
- Improves time capture rates by meeting developers in their primary tool
- Keeps billing accurate by syncing work logs in near real-time
Use case
New Jira Project Creates a Harvest Project Automatically
Whenever a new project is created in Jira, tray.ai can automatically provision a matching project in Harvest with the right name, client assignment, and budget settings. Your time tracking setup stays in step with your project management setup, and orphaned time entries stop being a problem.
- Reduces project setup time and manual admin work
- Prevents time entries from landing on incorrect or missing projects
- Keeps Harvest project lists consistent with active Jira projects
Use case
Jira Issue Status Changes Update Harvest Task Status
As Jira issues move through workflow stages — To Do, In Progress, Done — tray.ai can update related Harvest tasks to match. Your time tracking data stays contextually accurate, and project managers get a synchronized view of progress across both platforms.
- Maintains consistency between project management and billing systems
- Cuts manual status updates across multiple tools
- Gives accurate task-level billing context for client reporting
Use case
Budget Alerts When Harvest Hours Approach Jira Epic Estimates
When total hours logged in Harvest for a project approach or exceed the story point estimates mapped to a Jira epic, tray.ai can fire automated alerts to project managers via Slack or email. Teams get a heads-up before budgets are overrun, not after.
- Lets teams course-correct before overruns happen
- Connects financial data in Harvest to planning data in Jira
- Reduces the risk of unprofitable project delivery
Use case
Weekly Time Report Digest Linked to Jira Sprint Progress
At the end of each sprint, tray.ai can generate a combined report pulling hours logged in Harvest alongside the completion status of Jira issues, then deliver it to stakeholders via email or a project channel. Leadership gets a unified view of both effort and output without anyone compiling it by hand.
- Saves hours of manual reporting every sprint cycle
- Combines team productivity data from two sources into one view
- Gives stakeholders clearer visibility into budget vs. delivery performance
Use case
Harvest Invoice Generation Triggered by Jira Sprint Completion
When a Jira sprint is marked complete, tray.ai can trigger Harvest to compile all billable hours logged during that sprint and draft an invoice for the associated client. Delivery milestones and billing stay connected, which speeds up the invoicing cycle for client-facing teams.
- Speeds up invoice generation by tying it to delivery milestones
- Ensures all billable sprint hours are captured before invoicing
- Reduces revenue leakage from delayed or forgotten invoices
Challenges Tray.ai solves
Common obstacles when integrating Harvest and Jira — and how Tray.ai handles them.
Challenge
Mapping Users Across Harvest and Jira
Harvest and Jira maintain separate user directories with different identifiers, which makes it hard to automatically attribute time entries to the right Harvest user when syncing from Jira work logs. Mismatches mean time entries land on the wrong person or fail to sync at all.
How Tray.ai helps
tray.ai has a built-in data mapping layer where you can define and store cross-platform user mappings using lookup tables or custom connector configuration. Once mapped, every sync operation resolves the correct user identity in both systems automatically.
Challenge
Keeping Project Structures Aligned Between the Two Tools
Jira organizes work into projects, epics, stories, and subtasks. Harvest uses projects and tasks. The hierarchies don't map one-to-one, and without a clear strategy, time entries end up at the wrong level of granularity — which makes reporting unreliable.
How Tray.ai helps
tray.ai workflows let you configure custom field mappings that translate Jira's multi-level hierarchy into Harvest's project and task structure. You can define rules that map Jira epics to Harvest tasks or projects to tasks depending on your billing model, so you control exactly how data is structured across both platforms.
Challenge
Handling Real-Time Webhook Reliability at Scale
For high-volume engineering teams logging dozens of work entries per day, a webhook-driven sync between Jira and Harvest can hit delays, duplicate events, or dropped payloads — especially during busy periods. The result is inaccurate time records or missed billing entries.
How Tray.ai helps
tray.ai's workflow engine includes built-in error handling, retry logic, and deduplication. Workflows can detect and discard duplicate events while retrying failed API calls automatically, so every work log reaches Harvest reliably even under heavy load.
Sync Jira Work Logs to Harvest Time Entries
Jira 
Harvest Automatically creates a Harvest time entry whenever a work log is added to a Jira issue, mapping the user, duration, and issue details to the correct Harvest project and task.
Create Harvest Project When a Jira Project Is Created
Jira Harvest Listens for new Jira project creation events and automatically provisions a matching project in Harvest with the appropriate client, budget, and billing settings.
Sprint Completion Triggers Harvest Invoice Draft
Jira Harvest When a Jira sprint is closed, this template aggregates all billable hours logged in Harvest during the sprint window and generates a draft invoice for the associated client.
Harvest Budget Threshold Alert via Jira and Slack
Harvest Jira Monitors Harvest project budgets and fires an alert when logged hours hit a configurable threshold, with the notification enriched by linked Jira epic and sprint context.
Weekly Sprint and Hours Summary Report
Jira Harvest Generates a combined weekly digest pulling Jira sprint status and Harvest time data, then delivers a unified report to stakeholders every Friday.
Jira Issue Resolved Marks Harvest Task Complete
Jira Harvest When a Jira issue transitions to a resolved or done status, this template automatically updates the associated Harvest task to closed, keeping both systems in sync without manual intervention.
How Tray.ai makes this work
Harvest + Jira runs on the full Tray.ai platform
Intelligent iPaaS
Integrate and automate across 700+ connectors with visual workflows, error handling, and observability.
Learn more →Agent Builder
Build AI agents that read, write, and take action in Harvest and Jira — with guardrails, audit, and human-in-the-loop.
Learn more →Agent Gateway for MCP
Expose Harvest + Jira actions as governed MCP tools — observable, rate-limited, authenticated.
Learn more →Ship your Harvest + Jira integration.
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