Project Management migration

Migrate from AGILITY to Jira

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

AGILITY logo

AGILITY

Source

Jira

Destination

Jira logo

Compatibility

92%

11 of 12

objects map 1:1 between AGILITY and Jira.

Complexity

BStandard

Timeline

4-6 weeks

Rollback included Accuracy guarantee Field-level validation

Overview

What this migration involves

Moving from digital.ai Agility to Jira is a schema translation, not a record copy. Agility stores work in a layered ALM hierarchy (Projects, Teams, Sprints, Stories, Defects, Tasks) with attachments managed through a separate OID registry and custom fields identified by their System Name in the Data Mart, not their display label. Jira uses a flat project-based structure where Stories, Bugs, Tasks, and Epics are all Issue types within a Project, and custom fields are created with display-naming conventions. We resolve the Agility Data Mart System Name to Jira custom field mapping during discovery, flatten the iteration calendar into Jira Sprints, split Test Sets and Test Cases into Jira's Test Management structure, and run a two-pass attachment workflow to prevent orphaned references. Agility's Enterprise-tier API access requirement is verified before extraction; Starter and Pro tier customers without API access receive a file-based migration path using Agility's native export. Workflows, automations, and ALM-specific governance rules do not migrate as configuration code.

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

AGILITY logo

AGILITY

What's pushing teams away

  • Public pricing is not disclosed by digital.ai, requiring sales-led engagement even for small evaluations — competitors like Jira and Azure DevOps publish per-seat rates.
  • UI is widely perceived as dated relative to Jira, Linear, and Azure DevOps, particularly for individual contributors who interact with work items daily.
  • Edition gating means API and Data Mart access are restricted to higher tiers, blocking smaller orgs from automation and reporting.
  • Custom-field System-Name vs. display-label divergence creates silent data mismatches that bite teams during reporting and integration builds.
  • Smaller and less active community than Atlassian's ecosystem, so add-ons, third-party integrations, and shared expertise are harder to source.

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 AGILITY objects map to Jira

Each row shows how a AGILITY 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.

AGILITY

Project

maps to

Jira

Project

1:1
Fully supported

Agility Projects map directly to Jira Projects. Each Agility Project OID is preserved in a custom Jira field agility_oid__c for traceability. Project metadata including name, description, owner, and team assignments migrate as Project-level fields. If the customer uses multiple Agility Teams within a single Project, we discuss whether to consolidate into one Jira Project with multiple Boards or create separate Jira Projects per Team.

AGILITY

Sprint/Iteration

maps to

Jira

Sprint

1:1
Fully supported

Agility Iterations (with start date, end date, status, and velocity settings) map to Jira Sprints. We preserve the iteration name, start/end dates, and status (Active, Closed, Planning) as Sprint fields. If Agility uses multiple concurrent Iterations, these map to multiple active Jira Sprints within the same Project. Historical sprint velocity metrics from Agility become custom fields on the Jira Sprint for reporting continuity.

AGILITY

Story

maps to

Jira

Story (Issue Type)

1:1
Fully supported

Agility Stories map to Jira Story issues within the destination Project. The Story title, description, acceptance criteria, story points (if numeric), status, and priority migrate directly. Parent-child relationships to Epic or parent Story in Agility become Jira Epic links or parent Story links. Custom fields on the Story use the System Name-to-Jira field mapping generated during discovery. Stories without a direct Jira equivalent are mapped to the closest Issue Type during scoping.

AGILITY

Defect

maps to

Jira

Bug (Issue Type)

1:1
Fully supported

Agility Defects map to Jira Bug issues. Defect-specific fields (severity, detected-in-iteration, resolution type, steps to reproduce) migrate to Jira Bug fields or custom fields of equivalent type. The Defect-to-Story parent relationship maps to the Jira Bug's parent Epic or linked Story. Defects with no severity equivalent in Jira's default configuration become custom Jira priority or severity fields that we configure before import.

AGILITY

Task

maps to

Jira

Sub-Task or Task (Issue Type)

1:1
Fully supported

Agility Tasks (child work items belonging to Stories or Defects) map to Jira Sub-Tasks linked to their parent Story or Bug. Task fields including assignee, estimated hours, remaining hours, and status migrate directly. If the customer's Agility uses Tasks as standalone work items rather than children, we map them to Jira Task issues at the same level as Stories. Parent-child linkage is reconstructed using the Agility work item OID preserved in agility_oid__c.

AGILITY

Test Set

maps to

Jira

Test Cycle

1:1
Fully supported

Agility Test Sets aggregate Test Cases and generate Fact.PrimaryWorkitem records in the Data Mart. They map to Jira Test Cycles (Xray) or Test Executions (Zephyr) depending on the customer's Jira add-ons. The Test Set name, description, assigned tester, and execution status migrate. If the customer does not have a test management add-on installed, Test Sets are mapped to Jira Epic or Label for manual test management configuration post-migration.

AGILITY

Test Case

maps to

Jira

Test

1:1
Fully supported

Agility Test Cases (with steps, expected results, and custom fields) map to Jira Test Case records under the corresponding Test Cycle or Project. Step-level data decomposes into Jira's test step structure with the Given-When-Then format if the destination supports it. Test Case status from Agility (Draft, Approved, Active) maps to Jira test status values. Any fields that exist in Agility Enterprise but have no Jira equivalent are flagged in the mapping document for manual recreation.

AGILITY

Issue

maps to

Jira

Issue or Story (Issue Type)

1:1
Fully supported

Agility Issues are tracked in Fact.Issue and behave like standalone Defects with their own schema distinct from primary work items. They have status, priority, assignee, and description fields. We migrate them as first-class Jira Issues or as Story-type issues depending on the customer's Jira project configuration. Issue-specific fields (issue-type classification, external reference) migrate to custom Jira fields.

AGILITY

Custom Field

maps to

Jira

Custom Field

1:1
Fully supported

Agility custom fields (checkbox, date, text, number, drop-down) on any asset type map to Jira custom fields of the matching type. The critical mapping is System Name to Jira field: the Agility Data Mart generates column names from the field's System Name, not its display label. During discovery we extract both the System Name and display label and generate a dual-key mapping table. Without this, destination field matching silently fails and data lands in the wrong columns or is dropped.

AGILITY

Attachment

maps to

Jira

Attachment

lossy
Fully supported

Attachments in Agility are stored as binary assets with a separate OID registry from the work item JSON payload. We run a two-pass workflow: first, we export the work item data and attachment OID list; second, we upload attachments to Jira (using the Jira REST API attachment endpoint), capture the Jira-generated attachment IDs, then update the cross-reference table mapping Agility OID to Jira attachment ID. Finally we re-associate the attachment with the parent work item. This prevents orphaned attachment references. Jira's attachment size limit is 256 MB per file; we flag any Agility attachments exceeding this during discovery.

AGILITY

Member/User

maps to

Jira

User

1:1
Fully supported

Agility user records (display name, email, role, team membership) map to Jira Users. We resolve users by email match against the Jira destination instance. Active Directory integration in Agility can source users externally; we detect whether Jira will use local user management or directory-based provisioning (Atlassian Access, Google Workspace, Okta, Azure AD) and align the migration accordingly. Users without a matching Jira account are held in a reconciliation queue for the customer's admin to provision before record import.

AGILITY

Comment

maps to

Jira

Comment

1:1
Fully supported

Comments on Agility work items (author, timestamp, body) migrate as Jira Comments on the corresponding Issue. Author attribution is preserved by resolving the Agility user email to the Jira User account. Comment timestamps are preserved as the Jira comment creation date. Rich-text comments from Agility are converted to Jira's Wiki markup or kept as plain text depending on complexity. Comments on Test Cases, Defects, and standalone Issues all migrate with their parent work item.

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.

AGILITY logo

AGILITY gotchas

High

Edition-gated API access blocks migration extraction

High

Custom field System Name vs. display label mismatch

Medium

Rate limits are undocumented for direct consumption

Medium

Test Set and Test Case schemas vary by Agility edition

Medium

Attachment OID registry requires a separate migration pass

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

  • Agility API access requires Enterprise-tier licensing

    Agility's REST API and Data Mart are restricted to Enterprise-tier licenses. Starter and Pro tier customers cannot programmatically export data via API, forcing reliance on manual CSV exports or the built-in UI. We identify the customer's current edition during scoping; if API access is unavailable we pivot to a file-based migration path using Agility's native export functionality. This approach limits which asset types and custom fields are extractable, and the customer must manually prepare export files. We document exactly which fields and relationships are available through file-based export versus API export before scoping closes.

  • Custom field System Name mismatch silently drops data

    The Agility Data Mart generates column names for custom fields from the field's System Name (the internal identifier), not the user-facing display label. A field named 'Customer Priority' in the Agility UI may have a Data Mart column of 'Custom_CustomerPriority' or similar. We extract both the System Name and display label during the discovery phase and generate a dual-key mapping table that maps both to Jira custom fields. Without this step, destination field matching silently fails, data lands in the wrong columns, or is dropped entirely. This is the most common source of data loss in Agility migrations.

  • Attachment OID registry requires a separate migration pass

    Binary attachments in Agility are stored with their own OID separate from the work item JSON payload. During export we extract the attachment OID list alongside the work item data. During Jira import we upload attachments first, capture the destination-generated attachment IDs, then re-associate them with the corresponding Jira Issue records using a cross-reference table. This two-pass approach prevents orphaned attachment references but adds a migration phase and requires the Jira attachment API to be available (not blocked by firewall or Atlassian Admin settings). Jira's 256 MB per-file attachment limit must be verified against the largest Agility attachment before import begins.

  • Test Set and Test Case schemas vary by Agility edition

    Test Sets and Test Cases have richer schema in Agility Enterprise editions compared to lower tiers, including additional custom field slots and step-level attachments. When migrating to Jira (with or without a test management add-on like Xray or Zephyr), we map the intersection of fields available in both the source edition and the destination schema. Any fields that exist in Agility but have no Jira or add-on equivalent are flagged in the mapping document for manual recreation by the customer's QA lead. Test Case step structure (given-when-then or step-expected-result) is decomposed into Jira's step format during the transform phase.

  • Jira required fields with null values block import

    If Jira's project configuration marks a field as required and the Agility source has no equivalent data (or the field was not included in the file-based export), the Jira import rejects those records. We coordinate with the customer's Jira admin to identify all required fields on the target project and either create default values in the migration transform or request that the admin make those fields optional before import begins. Common culprits include Fix Version, Sprint, Epic Link, and custom fields marked required by the project's field configuration. A null in a required field at import time halts the affected batch until resolved.

Migration approach

Six steps for a successful AGILITY to Jira data migration

  1. Discovery and edition verification

    We audit the source Agility instance across edition (Starter/Pro/Enterprise), API access availability, custom field inventory (with System Name extraction from Data Mart), work item counts by type, iteration calendar, test asset inventory (Test Sets, Test Cases, step counts), attachment volume and file size distribution, and user roster. If the Agility edition is Starter or Pro (no API access), we scope a file-based extraction path using Agility's native export, acknowledging the field limitations upfront. The discovery output is a written migration scope document with the full object inventory and a flag for any unsupported asset types.

  2. Schema design and field mapping

    We design the destination Jira project structure: Jira Project key, Issue type scheme (Story, Bug, Task, Sub-Task), field configuration, and screen scheme. For every Agility custom field we create a corresponding Jira custom field of the closest matching type (text, number, date, select, multi-select). The critical deliverable here is the System Name-to-Jira field mapping table generated from the Agility Data Mart. We also configure the Jira sprint board, backlog, and any required workflows before data import. If the customer uses a test management add-on (Xray, Zephyr), we configure Test Cycles and Test Case issue types at this stage.

  3. Attachment export and OID registry extraction

    We extract the Agility work item JSON payload alongside the attachment OID registry. Attachments are downloaded as binary files from Agility and stored in a migration staging directory organized by work item OID. We generate the Agility-OID-to-attachment-file mapping table at this stage. Any attachments exceeding Jira's 256 MB limit are flagged for the customer to decide whether to exclude, split, or host externally with a link substituted.

  4. Sandbox migration and reconciliation

    We run a full migration into the customer's Jira Sandbox environment (or a trial Jira Cloud site if no Sandbox exists) using production-equivalent data volume. The customer's project manager and QA lead reconcile record counts, spot-check 25-50 random issues against the Agility source, verify sprint calendar accuracy, and confirm test case step structure. Any mapping corrections (wrong field, missing values, wrong issue type) happen here before production migration begins. We also validate that Jira required fields are not blocking import batches.

  5. Production migration in dependency order

    We run production migration in dependency order: Jira Users (manual provisioning validated), Projects, Sprints (iteration calendar), Stories and Epics (with parent links resolved), Bugs and Defects, Tasks (with parent references resolved), Test Cases (with step structure decomposed), Comments (linked to parent issue), and Attachments (uploaded and re-associated via cross-reference table). Each phase emits a row-count reconciliation report before the next phase begins. We use Jira's REST API for standard issues and the Jira Bulk API for large record batches with rate-limit handling and checkpoint logging.

  6. Cutover, validation, and workflow rebuild handoff

    We freeze Agility 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 a written inventory of Agility workflows, SLA rules, and governance configurations requiring rebuild in Jira. Jira's workflow builder (or Jira Automation) is the replacement target. We do not rebuild Agility automations as Jira automations inside the migration scope; that is a separate engagement. We support a one-week hypercare window where we resolve any reconciliation issues raised by the customer's team.

Platform deep dives

Context on both ends of the pair

AGILITY logo

AGILITY

Source

Strengths

  • JSON-based export/import mapping files allow declarative, auditable migration configurations that can be version-controlled
  • Custom fields are available on a wide range of asset types and exposed through both the REST API and Data Mart reporting layer
  • Multi-edition architecture means Teams, Sprints, and Iterations are first-class citizens with stable OIDs and relationship fields
  • Rate limiting is documented as a system-wide protection, reducing the risk of accidental API-induced outages during migration
  • Export and import operations can be run incrementally, supporting phased cutover rather than a single big-bang switchover

Weaknesses

  • Specific API rate limit values are not publicly documented, requiring empirical testing to calibrate migration throughput
  • Custom field Data Mart column names derive from System Names, not display labels — silent mismatches occur if this naming layer is not handled explicitly
  • Edition gating on API access means Starter and Pro tier orgs have limited or no programmatic data extraction capability
  • No public deprecation timeline or changelog for the API means schema changes between Agility versions are not proactively communicated
  • Attachments and binary assets are managed through a separate OID registry from the JSON mapping data, adding a second migration pass
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 AGILITY 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

    AGILITY: Rate limiting is documented but specific quota values are not publicly disclosed; limits vary by Agility edition and org tier.

  • Data volume sensitivity

    B

    AGILITY doesn't expose a bulk API — REST + parallelization used for high-volume runs.

Estimator

Estimate your AGILITY 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 AGILITY to Jira data migrations

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

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Most migrations land between four and six weeks for environments with fewer than 10,000 work items, no test assets, and API-accessible Agility Enterprise editions. Migrations with large test suites (Test Sets with hundreds of Test Cases), extensive custom field schemas (30+ fields per work item type), or Starter/Pro Agility editions requiring file-based extraction move to eight to fourteen weeks because of the manual export preparation, custom field System Name resolution work, and two-pass attachment workflow. Jira configuration time (project setup, workflow design, screen configuration) adds an additional one to two weeks at the front end regardless of data volume.

Adjacent paths

Related migrations to explore

Ready when you are

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