HRMS migration
Field-level mapping, validation, and rollback between cvviz and Crelate. We move data and schema; workflows are rebuilt natively in Crelate.
cvviz
Source
Crelate
Destination
Compatibility
9 of 12
objects map 1:1 between cvviz and Crelate.
Complexity
BStandard
Timeline
3-5 weeks
Overview
Moving from CVViZ to Crelate is a migration between two ATS platforms with fundamentally different data models. CVViZ organizes its universe around Candidate, Job, and Application records with an AI-driven scoring layer, while Crelate uses a Core Record model (Contacts, Companies, Opportunities) with configurable pipelines and custom fields built on a Logical Name API layer. We extract CVViZ Candidate records and map them to Crelate Contacts, preserving Application-to-Job associations and stage history. Resume files require binary attachment handling since Crelate does not carry CVViZ's parsed resume NLP fields. CVViZ's proprietary AI ranking scores migrate as a custom numeric field snapshot, not a live recalculable metric. Pipeline stages are fully configurable per organization on both platforms, which means a named stage mapping exercise is required before migration. Automation rules, sourcing configurations, and job board distribution settings do not migrate; we deliver a written inventory for the customer's admin to rebuild in Crelate.
Every standard and custom field arrives verified.
AI proposes the map; you confirm before any record moves.
Parent–child, lookups, and ownership stay linked.
Calls, emails, meetings — with original timestamps.
Documents, uploads, and inline notes move with the record.
Why teams make this switch
Leaving
What's pushing teams away
Choosing
What's pulling them in
Object mapping
Each row shows how a cvviz 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.
cvviz
Job
Crelate
Job
1:1CVViZ Job records map to Crelate Job records with title, description, department, and job board distribution settings preserved. Active job status maps directly unless the job exceeds the target Crelate subscription tier's concurrent limit, in which case the job migrates as Inactive with a flag for post-migration activation. We preserve job posting metadata but note that the posting must be republished on the destination platform because job board distribution settings are platform-specific API connections that do not transfer.
cvviz
Candidate
Crelate
Contact (Core Record)
1:1CVViZ Candidate records map to Crelate Contact records, which is the Core Record that stores candidate data. Name, email address, phone, social profiles (LinkedIn, GitHub, Stack Overflow URLs), employment history, and source attribution map to standard Crelate Contact fields. Crelate's Logical Name API field naming convention is applied during import; we preserve the original CVViZ field names in custom documentation for the admin's reference during rebuild.
cvviz
Application
Crelate
Job Submission or Opportunity
1:1CVViZ Application records link a Candidate to a Job with a pipeline stage and timestamp. We map Applications to Crelate's Job Submission feature or, where the workflow requires pipeline tracking against a business entity, to the Opportunity Core Record. The stage assignment maps through the pre-migration stage name mapping, and the Application timestamp preserves the candidate journey timeline. If Crelate's Opportunity object is used for tracking, the Opportunity AccountId points to the relevant Client Company in Crelate.
cvviz
Resume
Crelate
Contact Attachment
1:1CVViZ stores parsed resume data alongside the raw PDF/DOCX file as a binary attachment. We extract the raw file and attach it to the corresponding Crelate Contact record as a file attachment. The parsed structured fields (work experience entries, education, skills) migrate to Crelate custom fields on the Contact record or to a Crelate Notes section as structured text. Crelate does not perform AI resume parsing on ingest, so the parsed NLP fields from CVViZ are stored as a snapshot in text fields rather than as recalculable structured data.
cvviz
Pipeline Stage
Crelate
Pipeline Stage
lossyCVViZ pipeline stages are fully customizable per organization with no universal stage schema. We capture the complete CVViZ stage map (names, order, and any conditional routing) during the pre-migration schema review, then apply a named mapping to Crelate's pipeline configuration. Stages with no Crelate equivalent are flagged as requiring manual configuration before the final import run. The mapping document becomes the stage configuration guide for the customer's Crelate admin.
cvviz
Talent Pool (CRM)
Crelate
Contact (Passive Tag)
1:1CVViZ's Talent Pool maintains passive candidates not tied to a specific active job requisition. We migrate Talent Pool entries as Crelate Contacts with a Passive or Talent Pool lifecycle tag. Source attribution (where the candidate was originally sourced from) preserves as a custom field on the Contact. Candidates that appear in both the Talent Pool and active Applications are deduplicated at the Contact level during migration.
cvviz
Candidate Scoring / Ranking
Crelate
Custom Numeric Field (Contact)
1:1CVViZ's AI-generated candidate scores are proprietary to its NLP model and calculated against the job description and historical hiring decisions. We carry the numeric score value as a custom field on the Crelate Contact record as a migration-time snapshot. Crelate will not recalculate or update this score because it has no equivalent proprietary algorithm. We recommend documenting the scores as a time-stamped snapshot and setting expectations that ranking will re-normalize over time as Crelate's own AI features (if enabled) begin processing hiring patterns.
cvviz
Pre-Screening Questions
Crelate
Custom Fields (Job or Application)
1:1CVViZ stores job-specific pre-screening questions and candidate responses as key-value pairs on the Application record. We map these to Crelate custom fields on the Job record or the Application (Job Submission) record. If Crelate does not have a matching field type, we flag the response as unstructured text in a Crelate Notes field. The customer chooses the preferred target during scoping.
cvviz
Custom Fields (Jobs and Candidates)
Crelate
Custom Fields (Jobs and Contacts)
1:1CVViZ custom field names, data types, and values migrate to Crelate custom fields on the equivalent Core Record (Job or Contact). Crelate requires pre-creation of custom fields in the Settings area under Core Records before import; we coordinate this during schema setup so that fields exist in Crelate with matching Logical Names before the data import run. Custom fields that do not have a Crelate equivalent are flagged for manual configuration before migration.
cvviz
User and Roles
Crelate
User and Roles
1:1CVViZ users with role-based access control map to Crelate users. We extract user name and email and match by email against the Crelate destination tenant. Role permissions are documented as a written inventory for the customer's Crelate admin to reconfigure in Crelate's permissions model, since role structures are platform-specific and do not transfer directly. Active and inactive user status is preserved in the inventory.
cvviz
Automation Rules
Crelate
Not Migrated (Inventory Documented)
lossyCVViZ automation rules for email triggers, notifications, and stage transitions are platform-specific and do not map cleanly to Crelate's workflow model. We document the rule logic (trigger condition, actions, delays, and recipients) as a written inventory for the customer's admin to rebuild in Crelate. Automation rebuild is outside the migration scope and is a separate configuration engagement.
cvviz
Job Board Distribution
Crelate
Not Migrated (Metadata Documented)
lossyCVViZ job board distribution settings (LinkedIn, Google for Jobs, and other job boards) are stored as platform API connections that do not transfer. We document the distribution configuration as metadata for each Job so that the customer can re-establish the postings in Crelate. Job descriptions and requirements are fully migrated; only the posting delivery channel requires manual reconfiguration.
| cvviz | Crelate | Compatibility | |
|---|---|---|---|
| Job | Job1:1 | Fully supported | |
| Candidate | Contact (Core Record)1:1 | Fully supported | |
| Application | Job Submission or Opportunity1:1 | Fully supported | |
| Resume | Contact Attachment1:1 | Fully supported | |
| Pipeline Stage | Pipeline Stagelossy | Fully supported | |
| Talent Pool (CRM) | Contact (Passive Tag)1:1 | Mapping required | |
| Candidate Scoring / Ranking | Custom Numeric Field (Contact)1:1 | Mapping required | |
| Pre-Screening Questions | Custom Fields (Job or Application)1:1 | Mapping required | |
| Custom Fields (Jobs and Candidates) | Custom Fields (Jobs and Contacts)1:1 | Fully supported | |
| User and Roles | User and Roles1:1 | Fully supported | |
| Automation Rules | Not Migrated (Inventory Documented)lossy | Mapping required | |
| Job Board Distribution | Not Migrated (Metadata Documented)lossy | Fully supported |
Gotchas + challenges
Platform-specific issues from each side, plus the pair-specific challenges that don't show up on either platform's page on its own.
cvviz gotchas
Resume files require binary export handling
Active job limits reset at migration time
Pipeline stage names are organization-specific
AI candidate scores are proprietary and non-transferable
Crelate gotchas
120 req/min API rate limit throttles bulk migrations
20 custom field per-entity cap forces data model decisions
15,000-record export ceiling on single operations
Sequences and automation workflows do not migrate
API key is a querystring parameter, not a header
Pair-specific challenges
Migration approach
Discovery and schema audit
We audit the source CVViZ environment across tier (Starter at 5 active jobs through Pro at 50), custom fields on Jobs and Candidates, pipeline stage names and order, Talent Pool volume, active automation rules, and integration connections (LinkedIn, GitHub, job boards). We pair this with a Crelate target assessment covering current subscription tier, existing custom field definitions, pipeline configuration, and user count. The discovery output is a written migration scope document specifying record counts, field mapping table, stage name mapping, and the automation inventory requirements.
Stage name mapping and custom field pre-creation
We conduct the pre-migration schema review to capture the complete CVViZ stage map and produce the named stage mapping to Crelate's pipeline configuration. We also work with the customer's Crelate admin to pre-create all custom fields in Crelate Settings under Core Records (Contacts, Companies, Opportunities) with matching Logical Names and correct data types. This step is sequential: Crelate fields must exist before data can map to them. Any CVViZ custom fields without a Crelate equivalent are flagged for customer decision during scoping.
Resume binary export and parsed field extraction
We extract resume files from CVViZ as binary PDF/DOCX attachments in batches, preserving the Candidate-to-Resume linkage via the Application ID. Simultaneously, we extract the parsed structured fields (work history, education, skills, screening responses) from CVViZ for mapping to Crelate custom text fields. Resume files are staged for bulk attachment to Crelate Contact records after the Contact base records are created. This step runs in parallel with the schema setup to maximize throughput.
Test migration to Crelate sandbox
We run a full migration into a Crelate test environment using a representative data sample (minimum 100 Candidates, 20 Jobs, 50 Applications). The customer's recruiting lead spot-checks 25-50 records against the CVViZ source, validates pipeline stage mapping, confirms resume attachments are present and readable, and signs off the field mapping table. Any mapping corrections are applied here before production migration begins. Stage name mapping validation is a required checkpoint at this step.
User and owner reconciliation
We extract every distinct CVViZ user referenced on Candidate, Application, and Talent Pool records and match by email against the Crelate destination tenant's user list. Users without a matching Crelate account are held in a reconciliation queue for the customer's admin to provision. This step gates the production migration because Owner and Assigned Recruiter fields on records in Crelate require a valid user reference at import time.
Production migration in dependency order
We run production migration in record-dependency order: Jobs (first, as the parent organizational unit), Companies (if separate from Candidates), Contacts (from CVViZ Candidates with the passive talent pool tag applied where applicable), Applications (Job Submissions or Opportunities with stage names resolved through the mapping), resume attachments (bulk attach to Contact records), Talent Pool entries (deduplicated against active Candidates), and custom field values (populated after the base records exist). Each phase emits a row-count reconciliation report before the next phase begins.
Cutover, delta sync, and automation inventory handoff
We freeze CVViZ writes during the cutover window, run a final delta migration of any records created or modified during the migration window, then enable Crelate as the system of record for recruiting activity. We deliver the automation rules inventory, sourcing configuration documentation, and job board distribution metadata to the customer's Crelate admin. We support a one-week hypercare window for reconciliation issues. We do not rebuild CVViZ automations in Crelate inside the migration scope; that is a separate configuration engagement.
Platform deep dives
cvviz
Source
Strengths
Weaknesses
Crelate
Destination
Strengths
Weaknesses
Complexity grading
Standard HRMS migration. 1 of 7 objects need a mapping; the rest are 1:1.
Overall complexity
Standard migration
Derived from compatibility, mapping clarity, API constraints, and data volume across cvviz and Crelate.
Object compatibility
1 of 7 objects need a mapping; the rest are 1:1.
Field mapping clarity
Field mapping is derived from defaults — final spec confirmed during the sample migration.
Timeline complexity
7-object category — typical timelines run 2–7 days end-to-end.
API constraints
cvviz: Not publicly documented.
Data volume sensitivity
cvviz doesn't expose a bulk API — REST + parallelization used for high-volume runs.
Estimator
Rule-based pricing — no per-record fees, no manual quotes. Migrations over 2M records are scoped individually.
Step 1
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FAQ
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