Harvest + Jira
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.
Why integrate Harvest and Jira?
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.
Automate & integrate Harvest & Jira
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.
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.
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.
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.
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.
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.
Use case
New Harvest Client Synced to Jira Customer or Label
When a new client is added to Harvest, tray.ai can automatically create a matching label, component, or organization tag in Jira so issues can be tied to the right client from day one. Cross-platform reporting gets simpler, and client data stays consistent across both tools.
Get started with Harvest & Jira integration today
Harvest & Jira Challenges
What challenges are there when working with Harvest & Jira and how will using Tray.ai help?
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 Can Help:
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 Can Help:
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 Can Help:
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.
Challenge
Managing Bidirectional Sync Without Infinite Loops
When data flows both ways between Harvest and Jira, updates made by the integration can trigger additional webhook events, creating sync loops that corrupt data or burn through API rate limits.
How Tray.ai Can Help:
tray.ai workflows support conditional logic and event source detection so you can tell whether a change came from a human or from the integration itself. Loop prevention rules can be embedded directly in your workflow logic, so automated updates don't re-trigger the same process and rate limits stay intact.
Challenge
Reconciling Historical Data During Initial Setup
When teams first connect Harvest and Jira, there's usually a backlog of historical time entries and issues that need reconciling before anything is consistent. Matching that historical data by hand is slow and error-prone.
How Tray.ai Can Help:
tray.ai supports paginated bulk data operations that can iterate over historical records in both Harvest and Jira via their REST APIs. A one-time migration workflow can match and import historical time entries and project data in batches, with consistent transformation logic applied throughout, so you start with clean data from day one.
Start using our pre-built Harvest & Jira templates today
Start from scratch or use one of our pre-built Harvest & Jira templates to quickly solve your most common use cases.
Harvest & Jira Templates
Find pre-built Harvest & Jira solutions for common use cases
Template
Sync Jira Work Logs to Harvest Time Entries
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.
Steps:
- Trigger: A work log is added or updated on a Jira issue
- Lookup: Match the Jira project key to the corresponding Harvest project ID
- Action: Create or update a time entry in Harvest with the logged duration, user, and issue reference
Connectors Used: Jira, Harvest
Template
Create Harvest Project When a Jira Project Is Created
Listens for new Jira project creation events and automatically provisions a matching project in Harvest with the appropriate client, budget, and billing settings.
Steps:
- Trigger: A new project is created in Jira
- Transform: Map Jira project name, key, and lead to Harvest project fields
- Action: Create a new project in Harvest and optionally notify the project manager via email
Connectors Used: Jira, Harvest
Template
Sprint Completion Triggers Harvest Invoice Draft
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.
Steps:
- Trigger: A Jira sprint is marked as complete
- Action: Query Harvest for all billable time entries within the sprint date range for the related project
- Action: Create a draft invoice in Harvest and notify the account manager for review
Connectors Used: Jira, Harvest
Template
Harvest Budget Threshold Alert via Jira and Slack
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.
Steps:
- Trigger: Harvest project hours reach a defined budget percentage threshold
- Lookup: Retrieve the associated Jira epic or active sprint for the project
- Action: Send a formatted alert to a Slack channel or email with budget status and Jira issue links
Connectors Used: Harvest, Jira
Template
Weekly Sprint and Hours Summary Report
Generates a combined weekly digest pulling Jira sprint status and Harvest time data, then delivers a unified report to stakeholders every Friday.
Steps:
- Trigger: Scheduled run every Friday at a configured time
- Action: Fetch open and completed Jira issues for the current sprint alongside Harvest time entries for the week
- Action: Compile and send a formatted summary report to a designated Slack channel or email distribution list
Connectors Used: Jira, Harvest
Template
Jira Issue Resolved Marks Harvest Task Complete
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.
Steps:
- Trigger: A Jira issue transitions to the 'Done' or 'Resolved' status
- Lookup: Find the matching task in Harvest using the Jira issue key stored as a reference
- Action: Update the Harvest task status to complete and log a final timestamp
Connectors Used: Jira, Harvest