HRMS migration

Migrate from cvviz to Crelate

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

cvviz logo

cvviz

Source

Crelate

Destination

Crelate logo

Compatibility

75%

9 of 12

objects map 1:1 between cvviz and Crelate.

Complexity

BStandard

Timeline

3-5 weeks

Rollback included Accuracy guarantee Field-level validation

Overview

What this migration involves

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.

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

cvviz logo

cvviz

What's pushing teams away

  • Reported bugs and missing items in the product make users feel the platform lacks maturity, with one AppSumo reviewer citing inability to add internal notes as a blocking issue.
  • No white-label or custom domain option frustrates agencies that want to embed the platform under their own brand for client-facing use.
  • Lack of robust follow-up automation means recruiters must manually manage candidate communications at each pipeline stage.
  • LinkedIn and CRM integrations are reported as inconsistent, causing data sync failures that require repeated manual corrections.

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 cvviz objects map to Crelate

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

maps to

Crelate

Job

1:1
Fully supported

CVViZ 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

maps to

Crelate

Contact (Core Record)

1:1
Fully supported

CVViZ 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

maps to

Crelate

Job Submission or Opportunity

1:1
Fully supported

CVViZ 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

maps to

Crelate

Contact Attachment

1:1
Fully supported

CVViZ 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

maps to

Crelate

Pipeline Stage

lossy
Fully supported

CVViZ 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)

maps to

Crelate

Contact (Passive Tag)

1:1
Mapping required

CVViZ'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

maps to

Crelate

Custom Numeric Field (Contact)

1:1
Mapping required

CVViZ'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

maps to

Crelate

Custom Fields (Job or Application)

1:1
Mapping required

CVViZ 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)

maps to

Crelate

Custom Fields (Jobs and Contacts)

1:1
Fully supported

CVViZ 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

maps to

Crelate

User and Roles

1:1
Fully supported

CVViZ 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

maps to

Crelate

Not Migrated (Inventory Documented)

lossy
Mapping required

CVViZ 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

maps to

Crelate

Not Migrated (Metadata Documented)

lossy
Fully supported

CVViZ 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.

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.

cvviz logo

cvviz gotchas

Medium

Resume files require binary export handling

Low

Active job limits reset at migration time

Medium

Pipeline stage names are organization-specific

Low

AI candidate scores are proprietary and non-transferable

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

  • Resume files require binary attachment export from CVViZ

    CVViZ stores resumes as parsed structured data alongside raw PDF/DOCX files linked to the Candidate record. During migration, resume files must be treated as binary attachments rather than simple field values. We chunk large resume libraries into batches, extract the raw file alongside parsed fields, and attach the binary to the Crelate Contact record. Crelate does not have a native resume parser that extracts structured fields from the attached file on ingest, so parsed CVViZ fields (work history, education, skills) must be mapped to custom text fields or a structured Notes section as a one-time snapshot. The raw attachment remains searchable in Crelate through its document indexing.

  • CVViZ AI candidate scores are non-transferable as live metrics

    CVViZ's AI ranking scores are proprietary and calculated by its own NLP model against job descriptions and historical hiring decisions. We carry the score value as a custom numeric field on the Crelate Contact record, but this is a static snapshot. Crelate will not recalculate, update, or display this score in a ranking context because it has no equivalent algorithm. We document the score as a time-stamped migration snapshot and recommend communicating to the hiring team that rankings will re-normalize as Crelate's own data accumulates.

  • Pipeline stage names require manual mapping before import

    CVViZ allows fully customizable pipeline stage names and order per organization. Crelate also uses configurable pipeline stages. There is no universal stage schema on either platform, so we conduct a pre-migration schema review to capture the complete CVViZ stage map. Stages with no Crelate equivalent are flagged for manual configuration before the import run. Skipping this step results in stage values landing as unstructured text in Crelate rather than as typed pipeline stage values, breaking reporting and workflow routing.

  • Crelate custom fields must be pre-created before import

    Crelate requires custom fields to be created in the Settings area (under Core Records: Contacts, Companies, Opportunities) before any data is mapped to them. We coordinate with the customer's Crelate admin to pre-create all custom fields with the correct data type and Logical Name during the schema setup phase. If a custom field does not exist in Crelate at import time, the mapped data either lands in an unstructured Notes field or is flagged as unresolvable. We resolve this during scoping, not during import.

  • Automation rules, sequences, and sourcing configs do not migrate

    CVViZ automation rules (email triggers, notifications, stage transitions), sourcing configurations (LinkedIn access tokens, GitHub integration credentials), and job board distribution API connections are platform-specific and do not transfer. We deliver a written inventory of every active CVViZ automation with its trigger, conditions, and actions, plus the sourcing and job board configuration metadata for each Job. The customer's Crelate admin rebuilds these post-migration. CVViZ's 800M+ candidate sourcing database access does not have a Crelate equivalent and is documented as a gap for the customer to address through Crelate's own integrations or manual sourcing processes.

Migration approach

Six steps for a successful cvviz to Crelate data migration

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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

Context on both ends of the pair

cvviz logo

cvviz

Source

Strengths

  • AI-driven resume screening using NLP and machine learning that adapts from historical hiring decisions over time.
  • 800M+ candidate profile database covering LinkedIn, GitHub, and Stack Overflow for active and passive sourcing.
  • Recruitment CRM built in, enabling talent pool management and candidate nurturing separate from active job requisitions.
  • Job posting distribution to LinkedIn, Google for Jobs, and other major job boards handled natively.
  • Pricing includes unlimited users across all tiers, avoiding per-seat cost surprises as hiring teams scale.

Weaknesses

  • Platform maturity concerns — reviews report bugs and missing features including inability to add internal notes to candidates.
  • No white-label or custom domain option, limiting use for staffing agencies wanting a branded client experience.
  • Integration stability issues with LinkedIn and CRM systems create sync failures requiring manual correction.
  • Pre-built follow-up automation is limited, requiring recruiters to manage candidate communications manually at each stage.
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 cvviz 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

    cvviz: Not publicly documented.

  • Data volume sensitivity

    B

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

Estimator

Estimate your cvviz 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 cvviz to Crelate data migrations

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

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Most migrations land between three and five weeks for accounts under 10,000 Candidates and 500 Jobs with no complex pipeline customization. Migrations with large Talent Pool libraries (over 50,000 passive candidates), extensive custom field schemas, resume-heavy volumes, or multi-pipeline configurations requiring named stage mapping extend to eight to fourteen weeks because of schema review scope, bulk resume attachment handling, and stage mapping validation across the full pipeline.

Adjacent paths

Related migrations to explore

Ready when you are

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