Project Management migration

Migrate from awork to Jira

Field-level mapping, validation, and rollback between awork and Jira. We move data and schema; workflows are rebuilt natively in Jira.

awork logo

awork

Source

Jira

Destination

Jira logo

Compatibility

80%

8 of 10

objects map 1:1 between awork and Jira.

Complexity

BStandard

Timeline

3-5 weeks

Rollback included Accuracy guarantee Field-level validation

Overview

What this migration involves

Moving from awork to Jira is a structural migration that reflects a shift from agency-focused task management to engineering-centric agile workflows. awork organizes work around a Client-Project-Task hierarchy with built-in time tracking; Jira organizes around Projects containing Issues (Epic, Story, Task, Bug) with Sprints, a configurable workflow schema, and a separate worklog model. We map awork's project and task structure to Jira Projects and Issue types, preserve time entries as Jira worklogs, and carry forward tags as Jira labels. We do not migrate awork automations or workflow rules because Jira's workflow engine uses a different trigger-and-transition model with per-project workflow schemes. We deliver a written inventory of any active awork automations for the customer's Jira admin to rebuild post-migration.

Field-level fidelity

Every standard and custom field arrives verified.

Schema-aware mapping

AI proposes the map; you confirm before any record moves.

Relationships preserved

Parent–child, lookups, and ownership stay linked.

Full activity history

Calls, emails, meetings — with original timestamps.

Attachments & notes

Documents, uploads, and inline notes move with the record.

Why teams make this switch

Two sides of the same decision

Leaving

awork logo

awork

What's pushing teams away

  • Time tracking cannot be logged directly against a Client record, only against Projects and Tasks, forcing teams that bill by client to create wrapper projects or lose billing granularity.
  • Small, ad-hoc tasks require a full Project to be created before they can be tracked, pushing teams toward either over-engineering their project structure or skipping time logging entirely.
  • Sortable priority tags are absent from the task interface, leaving teams without a native way to sequence or filter work by urgency across the project board.
  • A November 2025 review noted that despite being described as the best on the market, the platform fell short on core feature expectations and felt limiting for growing teams.

Choosing

Jira logo

Jira

What's pulling them in

  • Industry-standard tool with deep Git integration and sprint reporting that engineering teams already know, reducing onboarding friction for new hires.
  • Highly customizable workflows and status schemes let business teams model complex approval chains without writing code.
  • Strong ecosystem of Atlassian Marketplace apps means specialized capabilities like time tracking or portfolio management are one install away.
  • Free tier with up to 10 users and unlimited issues gives small teams a no-cost entry point to validate the platform before committing budget.
  • Visibility features — boards, backlog grooming, sprint reports, and dashboards — give leadership a shared view of what is planned, in progress, blocked, and done.

Object mapping

How awork objects map to Jira

Each row shows how a awork object lands in Jira, including any object-level transformations, lookup resolution, or schema-design dependencies.

Typical mapping — final map is confirmed during the sample migration step.

awork

Project

maps to

Jira

Project

1:1
Fully supported

awork Projects map directly to Jira Projects. We preserve project name, description, start and end dates, assigned users, and budget fields. Jira Projects require a project key (e.g., ENG, MKT) which we derive from the awork project name's initials or a customer-specified prefix. Projects are created first in the migration sequence so that subsequent task and time-entry imports have a valid parent reference.

awork

Task

maps to

Jira

Issue (Story or Task)

1:1
Fully supported

awork Tasks map to Jira Issues. The mapping to Jira Issue type (Story or Task) is determined during scoping based on the customer's workflow conventions. We preserve task name as Summary, description as Description, due date as Due Date, assignee as Assignee, and status by applying the collected awork workspace status schema to the Jira project's workflow scheme. awork's priority tagging (absent as native sortable tags) is mapped to Jira Priority values (Highest, High, Medium, Low) based on any existing priority indicators in awork.

awork

Subtask

maps to

Jira

Sub-Task Issue

1:1
Fully supported

awork Subtasks map to Jira Sub-Task Issue type. The parent-child relationship is preserved by setting the parent Issue key on each subtask during import. Jira's Sub-Task issue type is enabled per project in the Issue Type Scheme before migration. We flag subtask ordering if the destination project relies on rank-based ordering (such as Jira's backlog ranking algorithm) since awork does not expose a native sort order field.

awork

User (Team Member)

maps to

Jira

User

1:1
Fully supported

awork workspace members map to Jira Users by email address. We extract all users referenced in awork task assignments, project assignments, and time entries. The Jira destination site's admin provisions the corresponding users before migration begins. Any awork user without a Jira match goes to a reconciliation queue for admin provisioning. Inactive Jira users are supported for historical assignment preservation.

awork

Time Entry

maps to

Jira

Worklog

1:1
Fully supported

awork Time Entries map to Jira Issue Worklogs. We preserve the user attribution (matched to Jira User), start timestamp as Started, duration as Time Spent, and billable flag as a custom worklog field billable__c. The parent Issue key is resolved from the awork task reference. Jira's worklog model requires a Started timestamp and time spent value; we derive these from awork's time entry start/end or duration fields. Non-billable entries are imported with the billable flag set to false.

awork

Project Status

maps to

Jira

Status (via Workflow Scheme)

lossy
Fully supported

awork workspace statuses require a per-project value map because each awork workspace defines its own status names, colors, and ordering. During scoping we collect every distinct status value across all source workspaces and map them to Jira Status values appropriate for the destination project's workflow scheme. For example, awork status 'In Review' may map to Jira 'In Review' or 'In Progress' depending on the target workflow. We apply the map during the task import phase to avoid misclassifying task states.

awork

Custom Field

maps to

Jira

Custom Field

1:1
Fully supported

awork Custom Fields (workspace-level, activated per-project) require activation verification in Jira. We check each custom field's project-level activation status in awork during scoping. Fields not activated for a given project do not appear in that project's task export. In Jira, we create equivalent custom fields via the project Custom Fields configuration, match field types (text to Text Field, number to Number Field, date to Date Picker), and map values during task import. Custom field context mismatches are a known Jira import issue and we address them before loading.

awork

Tag

maps to

Jira

Label

1:1
Fully supported

awork Tags map to Jira Labels. Tags export as key-value labels applied to tasks and carry across in the task data export. Jira Labels are a flat string field with comma-separated values per issue. We preserve tag names exactly, flag any tag normalization needed if Jira enforces label format restrictions (lowercase, no spaces) per the destination site's configuration.

awork

Project Template

maps to

Jira

Project Template (Shared Configuration)

1:1
Fully supported

awork Project Templates define reusable project structures including default tasks, statuses, and custom field configurations. Jira does not have an equivalent template import mechanism, so we document the template structure as a written specification (default tasks, configured statuses, custom field defaults) for the customer's Jira admin to recreate using Jira's project template creation flow. The template's task and status definitions are preserved in the migration inventory document.

awork

Client

maps to

Jira

Component or Project Category

lossy
Fully supported

awork Clients do not have a direct Jira equivalent. Jira Projects are the primary container and can be categorized using Project Categories or Components for sub-grouping. We discuss the client's preferred structure during scoping: either one Jira Project per awork Client (using Project Category for grouping), or multiple awork Projects within a single Jira Project using Components or Labels to distinguish client attribution. The chosen strategy is applied before migration begins.

Gotchas + challenges

What specifically takes care here

Platform-specific issues from each side, plus the pair-specific challenges that don't show up on either platform's page on its own.

awork logo

awork gotchas

Medium

Custom fields must be activated per project

Medium

Project statuses are per-workspace, not global

Low

Timeline export is an image, not structured data

Jira logo

Jira gotchas

High

Unsupported workflow validators silently skipped during migration

High

Custom fields converted to flat text labels when migrating to non-Jira platforms

Medium

Historical status-change timestamps lost when exporting without a Marketplace plugin

Medium

Attachment import failures from oversized files and JQL reference corruption

Medium

Points-based API rate limits enforced on Jira Cloud apps from March 2026

Pair-specific challenges

  • Custom fields must be verified active per project before export

    awork Custom Fields are created at the workspace level but must be explicitly activated for each project before they appear at the task level. If a project does not have a custom field activated, that field will not appear in any view or export for tasks in that project. We check every custom field's project-level activation status during scoping and flag any gaps before we begin the export. Unactivated fields result in incomplete task records at the destination, which requires post-migration gap-filling that adds scope. We also verify that Jira's custom field context covers the relevant issue types before importing.

  • Workspace statuses require manual value mapping per Jira project

    awork does not enforce a global status vocabulary. Each workspace defines its own set of statuses with custom names, colors, and ordering. Jira's workflow scheme ties Status values to transitions and screens, so the status names in Jira must match the workflow's defined values exactly. We collect the full status schema during the discovery phase, build a value map for every unique status found in the source workspace, and apply it during the load step. Without this mapping, task states arrive in Jira with mismatched or unrecognizable status values that break workflow transitions.

  • a work has no publicly documented API; export depends on list and board views

    awork does not publish a confirmed API with documented authentication, endpoints, or rate limits. Data export for migration relies on list and board view exports, or on Excel-format time entry exports. Timeline exports produce a PNG or SVG image, not structured data, so timeline-based scheduling data must be reconstructed from task-level due dates and start dates. This constraint means migration scoping must account for data completeness checks against the available export format rather than a structured API response, and any missing data fields are flagged in the discovery report before export begins.

  • Jira workflow and automation configurations do not migrate from awork

    awork workspace-level automation rules (trigger-action workflows for task state changes, notifications, or assignments) do not have a migration path to Jira's workflow engine. Jira workflows use a different model based on project-specific workflow schemes, status transitions, validators, and post-functions. We do not migrate automations as code. We deliver a written inventory of every active awork automation rule with its trigger, conditions, and actions, and the customer's Jira admin rebuilds the equivalent in Jira's workflow designer or Automation for Jira. Teams should plan for two to five days of workflow rebuild effort per automation rule depending on complexity.

  • Subtask ordering may not preserve across the migration

    awork subtasks are ordered within their parent task but the sort order field is not exposed in the standard task export. Jira uses a rank-based ordering algorithm (similar to Folson ranking) for backlog and sprint prioritization. We preserve the parent-child relationship of subtasks but cannot guarantee ordering is maintained unless the customer specifies a sort field (such as awork task created date or a custom priority field) that we can translate into Jira's rank values. Ordering gaps are flagged post-migration for the customer's admin to resolve using Jira's backlog ranking UI.

Migration approach

Six steps for a successful awork to Jira data migration

  1. Discovery and export preparation

    We audit the source awork account across all workspaces, collecting project names, task counts, subtask nesting depth, time entry volume, custom field definitions, and workspace-level status schemas. We verify each custom field's project-level activation status and flag any gaps. We export task data from list and board views (not the timeline image export) and time entries in Excel format. We inventory any active automation rules for the written handoff document. The discovery output is a written migration scope, a data completeness report, and a list of any export gaps that require customer action before migration begins.

  2. Jira project and schema setup

    We work with the customer's Jira admin to create Jira Projects with appropriate Issue Type Schemes (Epic, Story, Task, Sub-Task), a Workflow Scheme with status values that match the mapped awork workspace statuses, and any required custom fields with correct field types and contexts. If the customer uses Project Categories to group by client (mapped from awork Clients), we configure those before migration. We validate the schema in a Jira Sandbox or non-production environment before moving to production data.

  3. User reconciliation and Jira provisioning

    We extract every distinct awork user referenced in task assignments, project memberships, and time entries. We match by email address against the Jira destination site's User table. Users without a matching Jira account go to a reconciliation queue. The customer's Jira admin provisions any missing users (active or inactive depending on whether the original awork user is still active) before the record import phase begins. OwnerId references on Jira issues require an active or inactive User record to resolve.

  4. Task and subtask migration in hierarchy order

    We run task migration in dependency order: Jira Projects first, then parent tasks (Epics or Stories), then child tasks (Stories or Tasks), then subtasks last with their parent reference resolved. We apply the collected workspace status schema map during task import so that status values are translated correctly. Custom field values are mapped per field type. Tags are imported as Jira Labels. Each phase emits a row-count reconciliation report before the next phase begins. Any task without a resolved assignee is assigned to the project lead or placed in a backlog queue for admin resolution.

  5. Time entry migration as Jira worklogs

    We migrate awork Time Entries as Jira Issue Worklogs. Each worklog references the Jira Issue key resolved from the awork task, the Jira User resolved from the awork user, the Started timestamp from the original time entry, and the time spent value. Billable flags migrate to a custom worklog field. Jira's worklog model does not support bulk import via CSV for large volumes, so we use the Jira REST API with batch chunking and exponential backoff to load time entries without exceeding per-instance write limits. We validate total hours by project against awork's project-level time totals to catch any missing records.

  6. Cutover, validation, and automation handoff

    We freeze awork writes during cutover, run a final delta migration of any records modified during the migration window, then enable Jira as the system of record. We deliver the migration inventory document including the automation rule inventory for the customer's Jira admin to rebuild, the custom field mapping reference, and the status value map. We support a one-week post-migration window where we resolve reconciliation issues raised by the customer's team. We do not rebuild awork automations as Jira workflows inside the migration scope; that work is documented separately for the customer's admin or a Jira partner.

Platform deep dives

Context on both ends of the pair

awork logo

awork

Source

Strengths

  • Built-in time tracking keeps billable data linked directly to tasks without a separate tool.
  • Clean, accessible interface reduces onboarding time for non-technical team members.
  • Workflow customization requires far less configuration overhead than comparable tools like Jira.
  • Automation capabilities and Lexoffice integration support end-to-end agency billing workflows.
  • GDPR and ISO 27001 compliance with European-hosted data addresses regulatory requirements.

Weaknesses

  • Time cannot be logged against a Client record directly, only against Projects or Tasks.
  • Small, ad-hoc work items still require a full project to be created before they can be tracked.
  • Native sortable priority tagging is absent from the task interface.
  • No publicly documented API with confirmed authentication or rate limit specifications.
  • The feature set is optimized for agencies and may be limiting for non-agency project teams.
Jira logo

Jira

Destination

Strengths

  • Deeply customizable workflows and status schemes with no hard limits on workflow complexity or number of custom statuses.
  • Strong agile ceremony support: sprint planning, backlog grooming, velocity tracking, and burndown charts for Scrum teams.
  • Industry-standard developer tool with native Git integration linking commits, pull requests, and deployments to issues.
  • Large Atlassian Marketplace with thousands of plugins extending time tracking, portfolio management, and reporting capabilities.
  • Free tier available for up to 10 users with unlimited issues, enabling evaluation before committing to a paid plan.

Weaknesses

  • Excessive configurability creates a steep learning curve; cross-team consistency is hard to maintain without strict governance.
  • Performance degrades with large backlogs, complex custom fields, and heavily nested issue hierarchies.
  • Reporting requires additional configuration or paid plugins; out-of-the-box analytics are limited for business users.
  • Jira lacks native sprint management, requiring Jira Software for true agile team features.
  • Teams outside engineering resist adoption due to UI complexity, leaving the all-in-one promise unfulfilled for cross-functional organizations.

Complexity grading

How hard is this migration?

Standard Project Management migration. 3 of 8 objects need a mapping; the rest are 1:1.

B

Overall complexity

Standard migration

Derived from compatibility, mapping clarity, API constraints, and data volume across awork and Jira.

  • Object compatibility

    B

    3 of 8 objects need a mapping; the rest are 1:1.

  • Field mapping clarity

    C

    Field mapping is derived from defaults — final spec confirmed during the sample migration.

  • Timeline complexity

    B

    8-object category — typical timelines run 2–7 days end-to-end.

  • API constraints

    B

    awork: Rate-limited per client; 429 Too Many Requests response includes RateLimit-Reset header indicating seconds until reset.

  • Data volume sensitivity

    A

    awork exposes a bulk API — large-volume migrations stream efficiently.

Estimator

Estimate your awork to Jira migration cost

Rule-based pricing — no per-record fees, no manual quotes. Migrations over 2M records are scoped individually.

Step 1

What are you migrating?

Pick a category, then your source and destination platforms.

Category

FAQ

Frequently asked questions about awork to Jira data migrations

Answers to the questions buyers ask most during awork to Jira migration scoping. Not seeing yours? Book a call.

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Migrations under 5,000 tasks and 1,000 time entries with straightforward project structures land between three and five weeks. Migrations with complex subtask hierarchies, per-workspace status schemas requiring multi-project mapping, large time-entry histories (over 10,000 worklogs), or custom field activation gaps needing project-by-project verification move to eight to twelve weeks because of data reconciliation and schema setup. Jira API rate limits and worklog batch sizing add overhead for large time-entry volumes.

Adjacent paths

Related migrations to explore

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