HRMS migration

Migrate from gradar to Crelate

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

gradar logo

gradar

Source

Crelate

Destination

Crelate logo

Compatibility

67%

8 of 12

objects map 1:1 between gradar and Crelate.

Complexity

BStandard

Timeline

2-4 weeks

Rollback included Accuracy guarantee Field-level validation

Overview

What this migration involves

Moving from gradar to Crelate is a cross-category migration. gradar is a point-factor job evaluation and compensation platform with grades 1 through 25, pay band structuring, equal pay regression analysis, and no public API. Crelate is a recruiting ATS and talent CRM with no native support for job evaluation, compensation bands, or grade structures. We bridge the gap by designing a custom field schema in Crelate that represents the key gradar objects (Job, Grade, Career Path, Factor Scores, Pay Band) as typed fields on Crelate's Opportunity record, pre-creating the schema before any data moves. We handle the non-standard gradar export formats, flag currency ambiguity in multinational pay band data, and deliver a written inventory of any gradar objects that cannot be represented in Crelate's ATS schema for the customer's admin to address post-migration. We do not migrate gradar's equal pay regression analysis results as code or dataset; these require a dedicated analytics platform rebuild.

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

gradar logo

gradar

What's pushing teams away

  • Some users report that the user interface needs improvement and can feel dated compared to modern SaaS platforms.
  • Exporting data for migration purposes is not straightforward — gradar does not expose a well-documented public API for bulk data extraction.
  • Limited automation around data sharing with external systems means HR teams often resort to manual exports or professional services assistance.

Choosing

Crelate logo

Crelate

What's pulling them in

  • Affordable per-seat pricing with transparent tiers makes Crelate accessible for small-to-mid staffing firms evaluating ATS platforms for the first time.
  • Fast implementation reported by customers—some describe getting live in a matter of minutes with support team assistance.
  • Unified ATS + CRM in a single product eliminates the need to buy and synchronize separate recruiting and sales tools.
  • Flexible custom fields across Contacts, Companies, and Opportunities allow recruiting teams to capture firm-specific data without developer involvement.
  • Positive reviews highlight the product's intuitive interface and functional breadth for teams that need recruiting workflows without enterprise overhead.

Object mapping

How gradar objects map to Crelate

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

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

gradar

Job (Role)

maps to

Crelate

Opportunity

lossy
Fully supported

gradar Job records are the core evaluated entity. We migrate Jobs to Crelate Opportunity records, with the Job title as Opportunity Name, evaluation date as a custom date field, and factor-level scores stored as custom number fields on the Opportunity. The Opportunity's Account lookup links to the associated Client or Department as configured during scoping. Crelate's native Opportunity record type and stage model are repurposed to represent the job evaluation status rather than a recruiting placement stage, requiring a custom Sales Process configuration.

gradar

Grade

maps to

Crelate

Opportunity (custom field: Grade Level)

1:1
Fully supported

gradar Grade values (1-25) migrate as a custom integer field on the Crelate Opportunity record. The Grade Name (where gradar assigns labels like Associate, Mid-Level, Senior) migrates as a custom text field. We create both fields during schema pre-build. The grade value drives any downstream reporting segmentation the customer's admin configures in Crelate's Advanced Reports.

gradar

Career Path

maps to

Crelate

Opportunity (custom field: Career Path)

1:1
Fully supported

gradar's three career paths are represented as a custom picklist field on the Opportunity record. We extract the career path assignment from each Job record during export processing and map it to the corresponding picklist value. Custom picklist values are created in Crelate during schema pre-build to match the customer's actual career path labels exactly.

gradar

Job Description

maps to

Crelate

Opportunity (custom field: Job Description)

1:1
Fully supported

gradar's AI-assisted job description body migrates as a custom long-text field on the Crelate Opportunity record. The field supports rich text. Crelate's custom field type for long-form text accommodates descriptions of any length. We note that Crelate's native Job Posting feature references Opportunity fields, so the description field can be surfaced in candidate-facing job posts if the customer uses Crelate's publishing tools post-migration.

gradar

Competencies

maps to

Crelate

Opportunity (custom field: Competency Profile)

1:1
Mapping required

gradar competency profiles linked to each Job migrate as a custom text field on the Opportunity record. Structured competency lists are serialized as comma-separated values or JSON within the field. We flag any custom competencies that have no standard gradar equivalent and document them separately for the customer's admin to normalise in Crelate. Crelate's Activity Forms and custom questions can be used post-migration to capture competency assessment against the migrated profile.

gradar

Grade Factor Scores

maps to

Crelate

Opportunity (custom fields: Factor Score 1-N)

lossy
Mapping required

Individual factor-level point scores that contribute to the overall grade are stored per job evaluation in gradar's advanced exports. We create a corresponding set of custom number fields on the Crelate Opportunity record for each factor used in the customer's gradar configuration (typically 6-12 factors). Total point score migrates as a separate custom integer field. We request the factor-level export explicitly during scoping as standard exports may not include this granular data.

gradar

Compensation Structure (Pay Bands)

maps to

Crelate

Opportunity (custom fields: Pay Band Min, Mid, Max)

1:1
Fully supported

gradar pay band definitions with min/mid/max per grade and currency migrate as custom currency fields on the Crelate Opportunity record. Currency ambiguity is resolved during scoping by requesting the customer confirm the correct currency per compensation structure. We create separate custom currency fields for each currency in use if the migration involves multiple regions. Crelate's custom field type for money fields handles currency formatting. We flag that Crelate does not natively manage pay band structures as a hierarchical object; bands are stored per Opportunity as indicative compensation ranges rather than a structured pay band table.

gradar

Benchmarking Data

maps to

Crelate

Opportunity (custom fields: Market Rate, Benchmark Source)

1:1
Mapping required

Market benchmarking data comparing roles to external market rates migrates as custom fields on the Opportunity record. We create a custom currency field for the market rate value and a custom text field for the benchmark source (e.g., Mercer, Radford, Aon). The linked Job reference is preserved through the Opportunity mapping. We note that third-party benchmarking datasets sourced from providers integrated into gradar are migrated as data records only, not as live integration connections; the customer must re-establish any benchmarking API integrations in their analytics environment post-migration.

gradar

Equal Pay Analysis

maps to

Crelate

Not migratable to Crelate ATS schema

lossy
Mapping required

gradar's gender pay gap regression analysis outputs are datasets, not standard CRM records. Crelate's ATS schema has no object that represents regression analysis results. We document the equal pay analysis as a written dataset export for the customer's HR analytics team to load into their preferred analytics platform (Excel, Power BI, Workday Analytics, or dedicated pay equity tools). The audit trail of how gradar calculated the gap is not migratable as a functional component; the source data (salary, grade, demographic fields) can be migrated to support a rebuild in a dedicated pay equity platform.

gradar

Users and Owners

maps to

Crelate

Contact

1:1
Mapping required

gradar user accounts and role-based access assignments migrate to Crelate as Contact records. We map gradar's user email as Contact Email, user name as Contact Name, and permission group assignments as custom text fields on the Contact. The Customer's Crelate admin provisions the actual Crelate User accounts post-migration, mapping the gradar user identities to Crelate User records with the appropriate access level. We deliver a user mapping document identifying which gradar users should become Crelate Users versus Contacts.

gradar

Grade Change History

maps to

Crelate

Opportunity (custom field: Evaluation Date, historical notes)

1:1
Fully supported

gradar evaluation dates and grade change history are not available in standard exports and require an explicit extended export request during scoping. We migrate the most recent evaluation date as a custom date field on the Opportunity. Historical grade progression is not migratable as a full audit trail unless the extended export is available; we document the gap in the migration handoff report and flag it for the customer's HR team to determine whether manual reconstruction is required.

gradar

Grade Map Configuration

maps to

Crelate

Not migratable

lossy
Fully supported

gradar's Grade Map (the 25-grade structure with point-threshold boundaries and grade labels) is a platform configuration object. Crelate has no equivalent configuration schema for job grading. We deliver the Grade Map as a written reference document that the customer's HR team uses to define grade labels and boundaries as picklist values on the custom grade field post-migration. This is not an automated migration step; it is a configuration handoff requiring admin input.

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.

gradar logo

gradar gotchas

High

No public API forces reliance on manual exports

Medium

Evaluation history and grade change records require explicit extraction

Medium

Pay band data uses multiple currencies in multinational deployments

Crelate logo

Crelate gotchas

High

120 req/min API rate limit throttles bulk migrations

High

20 custom field per-entity cap forces data model decisions

Medium

15,000-record export ceiling on single operations

Medium

Sequences and automation workflows do not migrate

Low

API key is a querystring parameter, not a header

Pair-specific challenges

  • gradar has no public API for bulk data extraction

    gradar does not expose a documented REST API. All data extraction for migration relies on the platform's built-in reporting exports, which produce non-standard file formats that require preprocessing before they can be imported into Crelate. We handle the conversion of these exports to migration-ready formats and flag any records that cannot be fully represented in Crelate's schema before migration begins. Customers should expect to dedicate time during scoping to identify all required exports and confirm their completeness with gradar support if necessary.

  • Crelate has no native job evaluation or pay band schema

    Crelate is a recruiting ATS and talent CRM. It has no native objects for job evaluation grades, point-factor scores, career paths, or pay band structures. All gradar evaluation data must be mapped to custom fields on Crelate's Opportunity record. We pre-build the custom field schema in Crelate (including data types for integer grades, decimal factor scores, and currency pay bands) before any data moves. Customers should understand that Crelate's reporting on migrated job evaluation data relies entirely on the custom field setup; no native reporting templates exist for this data type.

  • Pay band currency ambiguity in multinational deployments

    Organisations with operations across multiple countries maintain pay bands in local currencies per grade. gradar's export does not consistently tag currency against each pay band row. We flag currency ambiguity at scoping and ask the customer to confirm the correct currency for each compensation structure before we commit the data. Mis-tagging currency causes incorrect pay band creation in Crelate's custom currency fields. This ambiguity is a gradar export limitation, not a Crelate limitation, but it directly impacts migration accuracy.

  • Equal pay regression analysis does not migrate

    gradar's gender pay gap regression analysis produces analytical datasets, not standard CRM records. Crelate's ATS schema cannot represent regression outputs, benchmarking datasets, or pay equity analysis results as functional records. We deliver these as structured data exports for the customer's HR analytics team to rebuild in a dedicated pay equity or BI platform. The audit trail of how gradar calculated pay gaps is not migratable as a functional component.

  • Grade change history requires explicit extended export

    gradar stores evaluation dates and grade change history as part of the job record. Standard exports surface only the current grade, not the historical progression. We request extended exports that include the evaluation timeline for each job. Where historical data cannot be extracted from gradar's built-in reporting tools, we document the gap in the migration handoff report, migrate the most recent evaluation record, and flag the incomplete audit trail for the customer's HR team to address manually post-migration.

Migration approach

Six steps for a successful gradar to Crelate data migration

  1. Discovery and export extraction

    We audit the gradar instance across all modules in use: Jobs, Grades, Career Paths, Competencies, Compensation Structures, Benchmarking Data, Equal Pay Analysis, and User accounts. We identify the exact built-in exports required for each module and confirm with the customer which exports are available and complete. We explicitly request the extended evaluation history export for grade change audit trails. We also review the Crelate destination instance for existing custom field configurations that may conflict with our planned schema.

  2. Custom field schema design in Crelate

    We design the custom field schema in Crelate's Opportunity record to represent gradar's job evaluation data. This includes custom fields for Grade Level (integer), Grade Name (text), Career Path (picklist), Factor Scores 1-N (decimal), Total Point Score (integer), Pay Band Min/Mid/Max (currency), Market Rate (currency), Benchmark Source (text), Competency Profile (long text), Job Description (long text), and Evaluation Date (date). Field types are chosen to match gradar's data types precisely. Schema is deployed via Crelate's field management interface into the destination Crelate instance before any data import begins.

  3. gradar export preprocessing

    We convert gradar's non-standard export files into migration-ready tabular formats. This includes parsing nested factor score exports, resolving currency ambiguity against the customer's confirmed currency map, splitting multinational pay band rows by the correct currency per structure, and serialising competency lists for storage in the custom text field. Any export records with missing required fields are flagged in a pre-migration data quality report with a recommended resolution for each record before we commit to import.

  4. Pay band currency confirmation

    We present the customer with a currency confirmation checklist covering every compensation structure extracted from gradar. The customer confirms or corrects the currency per structure. We do not proceed to migrate pay band data until the currency map is signed off, because incorrect currency values in Crelate's currency fields create downstream reporting errors that are difficult to correct post-migration.

  5. Test migration and reconciliation

    We run a full test migration into a Crelate test environment using production data volume. The customer's HR lead reconciles record counts (Jobs in, Opportunities in), spot-checks 25-50 random Opportunity records against the gradar source data for field accuracy, and validates that pay band values and grades are correctly populated. We also verify that the Opportunity's Account lookups are correctly resolved. Any field mapping corrections happen in the test environment before production migration begins.

  6. Production migration and handoff

    We run the production migration in record dependency order: Accounts (linked to the relevant Client or Department), then Opportunities with all custom fields populated. We deliver the written equal pay analysis dataset export, the Grade Map configuration reference document, the user-to-contact mapping document, and the workflow rebuild inventory for any gradar administrative workflows requiring Crelate rebuild. We do not migrate equal pay regression analysis as a functional component; the HR analytics team rebuilds this in their preferred platform using the delivered dataset.

Platform deep dives

Context on both ends of the pair

gradar logo

gradar

Source

Strengths

  • Point-factor evaluation methodology is objective and legally defensible across jurisdictions including the EU and Germany.
  • Grade Map with 25 grades across three career paths handles roles from entry-level to executive.
  • Comprehensive compensation suite covers evaluation, pay structuring, benchmarking, and equal pay analysis in one platform.
  • Highly affordable compared to consultant-led job evaluation — customers report saving up to 95% on typical projects.
  • Multilingual and multinational-ready with support for many languages and global job structures.

Weaknesses

  • No publicly documented REST API — data export relies on built-in reporting tools or manual downloads.
  • Interface and user experience is considered dated by some users compared to modern SaaS standards.
  • Export formats are non-standard and require preprocessing before they can be imported into most destination HRMS platforms.
  • Limited third-party integrations out of the box; data portability for migrations is not a primary platform design goal.
Crelate logo

Crelate

Destination

Strengths

  • Unified ATS and CRM in a single platform reduces data synchronization overhead for recruiting teams.
  • Fast setup with guided implementation reported as a significant time saver for small teams.
  • Transparent per-seat pricing without surprise fees at the base tier.
  • Flexible custom field configuration across core objects without developer dependency.
  • Export capability supports up to 15,000 records per operation for Contacts, Companies, and Opportunities.

Weaknesses

  • API rate limit of 120 requests per minute restricts bulk migration throughput.
  • Custom field cap of 20 per entity requires field consolidation for complex recruiting schemas.
  • All advanced features (Activities, Activity Forms, Core Record Field customization) are tier-gated add-ons.
  • Customer service responsiveness receives consistent negative feedback in reviews.
  • Resume parsing quality trails competitors and generates support requests.

Complexity grading

How hard is this migration?

Standard HRMS migration. 1 of 7 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 gradar and Crelate.

  • Object compatibility

    B

    1 of 7 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

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

  • API constraints

    B

    gradar: Not publicly documented.

  • Data volume sensitivity

    B

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

Estimator

Estimate your gradar to Crelate 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 gradar to Crelate data migrations

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

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Most migrations land between two and four weeks for organisations with fewer than 1,000 Job records, a single career path structure, and no multinational pay band complexity. Migrations with multiple career paths, full factor-score history exports, multicurrency pay band data, and 5,000+ job records move to six to ten weeks because of gradar export preprocessing, custom field schema design, and currency confirmation. The gradar export extraction phase (scoping and confirming available reports) typically adds one to two weeks before migration work begins.

Adjacent paths

Related migrations to explore

Ready when you are

Move from gradar.
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