Bullhorn-to-Ceipal migration requires API-based extraction (1,500 req/min limit), careful object mapping (Application V2 has no Ceipal equivalent), and strict load ordering to preserve relationships.
A technical guide to migrating from Bullhorn to Ceipal — covering API rate limits, object mapping, ETL architecture, and edge cases that break ATS migrations.
Read this first
Pair-specific gotchas that catch teams out. Each one has cost somebody a weekend.
Ceipal does not expose a direct equivalent to Bullhorn's Application V2 / Application
Ceipal does not expose a direct equivalent to Bullhorn's Application V2 / Application History objects through its API. Stage-level history and audit trails from Bullhorn's ATS v2 model cannot be mapped 1:1 into Ceipal. Plan for data loss or custom workarounds here.
API usage by validated Bullhorn Marketplace Partners does not count toward your API call limits
If you're using a migration partner with Bullhorn partner status, their calls won't eat into your 100,000 monthly cap.
Ceipal's onboarding team may use internal tooling for bulk imports that is not exposed
Ceipal's onboarding team may use internal tooling for bulk imports that is not exposed through the public API. If you're using Ceipal's free migration service, ask their team directly whether they have a higher-throughput path for your data volume. This is worth the conversation before committing to a record-by-record API approach.
Keep a permanent ID crosswalk
Bullhorn uses standard integer IDs; Ceipal v2 detail flows use encrypted IDs. If you lose the mapping between them, you cannot rebuild relationships after the fact. (developer.ceipal.com)
CSV exports from Bullhorn flatten the ClientCorporation → ClientContact → JobOrder →
CSV exports from Bullhorn flatten the ClientCorporation → ClientContact → JobOrder → JobSubmission → Placement chain into disconnected rows. You'll spend more time rebuilding relationships manually than you saved by avoiding the API.
Always store the Bullhorn source ID alongside every Ceipal record you create
You'll need this mapping table to rebuild relationships (e.g., linking Submissions to the correct Applicant and Job Posting) and to validate the migration.
Attachment migration is often the longest-running part of the pipeline
A database with 500K candidates and 2–3 files each means 1M+ API calls just for file downloads. At Bullhorn's 1,500 req/min limit, that's roughly 11+ hours of continuous extraction for downloads alone — and that's before uploads to Ceipal, which has no bulk endpoint. In practice, with retries and rate-limit backoff, plan for several days for attachment extraction and loading. Run this in a dedicated, heavily rate-limited background queue separate from your primary data extraction.
The runbook
Work top to bottom. Tick steps as you go — your progress is saved in this browser.
01 Discovery Scope candidates, pipelines and the compliance obligations that come with them.
Objective Agreed scope across candidates, applications, jobs and interview history, with legal signed up on retention.
Keep these open
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Inventory every object in Bullhorn
Count candidates, applications (a candidate can have many), jobs and requisitions, interviews, scorecards, offers, and resume files. Applications and scorecards usually outnumber candidates several times over, and resume files dominate storage.
Data Profiler Get real record counts instead of estimating from memory -
Settle retention and consent with legal
Candidate data is heavily regulated: GDPR right-to-erasure, EEOC/OFCCP record-keeping, and per-region retention windows that conflict with each other. Decide what may be migrated at all before you scope anything else — this frequently shrinks scope substantially.
Migrating candidate records whose consent has lapsed or whose retention window has expired creates a new compliance breach in the target system.
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Map the hiring pipeline and agree the target stages
Document every job's pipeline, stage, and rejection reason, then agree the Ceipal model with talent leadership. Stage definitions drive every funnel metric you report, so changing them silently rewrites your hiring analytics.
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Catalogue integrations and the job-board estate
List job boards, careers-site integration, HRIS, background check, assessment platforms, calendar and email. The careers site and job boards are customer-facing, so their cutover needs its own plan and its own testing.
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Build the business case and choose the window
Model licence delta, effort and recruiter productivity dip. Time the window against your hiring cycle: a migration during peak graduate recruitment or a hiring surge will fail on people, not technology.
Vendor Evaluator Score Ceipal against alternatives on weighted criteria
Bullhorn → Ceipal specifics
- Big bang
- everything at once, cutover over a weekend
- Deep experience with relational ATS data models
- we've mapped Bullhorn's Application V2, JobSubmission, and Placement hierarchies into multiple target systems.
- Zero downtime guarantee
- your recruiters keep working in Bullhorn until the exact cutover moment. We run the bulk migration, then execute a delta sync to catch any records modified during the process.
Don't move on until
- Counts confirmed for candidates, applications, jobs and offers
- Retention and consent obligations confirmed with legal
- Hiring-stage model agreed with talent leadership
02 Data Audit Audit candidate data with compliance sitting next to you.
Objective Profiled exports with duplicates, expired records and resume files all quantified and triaged.
Keep these open
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Export and profile candidates, applications and jobs
Profile each object separately and reconcile against API counts. Watch the candidate-to-application ratio: a mismatch usually means applications have been silently truncated by pagination.
Data Profiler Profile the Bullhorn export for nulls, outliers and type drift -
Quantify duplicate candidates and agree survivorship
The same person applies repeatedly over years with different emails and name spellings. Measure the duplicate rate and agree survivorship rules — which record wins and what happens to the application history attached to the losers.
Merging candidates without agreed survivorship rules destroys application and interview history that you may be legally required to retain.
Data Cleaner Strip empty rows, stray whitespace and dead columns -
Identify records outside their retention window
Flag candidates whose consent has expired, who have exercised erasure, or who fall outside regional retention. Exclude them from scope and document the exclusion — you need to show the decision was deliberate.
PII & Compliance Scanner Find regulated fields before they land in a new system -
Inventory resume files and attachments
Count files, total volume and MIME types, and check every attachment still resolves to a live URL. Expiring signed download URLs are the classic reason a resume migration completes with a large fraction of empty files.
Resume download URLs are often short-lived signed links. Fetch files close to load time or they will 404 mid-migration.
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Verify relationship integrity
Confirm every application links to a live candidate and a live job, and every scorecard to a real interview. Orphaned applications produce a funnel report that does not tie to anything.
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Clean, normalise and produce masked test data
Normalise emails, phone formats and locations, standardise timestamps to UTC, and generate a masked dataset for the sandbox. Real candidate data in a sandbox is a compliance breach in most jurisdictions.
PII Masker Generate a safe copy for sandbox and vendor testing
Bullhorn → Ceipal specifics
- Custom scripts handle Bullhorn's 429 rate limits, pagination, and session management
- your team doesn't build retry logic for a one-time move.
Don't move on until
- Duplicate candidate rate quantified with a merge policy agreed
- Records outside retention identified and excluded
- Resume and attachment inventory complete with total volume
03 Field Mapping Map the candidate-application-job triangle before anything else.
Objective A signed mapping covering objects, stages, rejection reasons, scorecards and EEO fields.
Keep these open
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Map the candidate, application and job model
ATS platforms differ on whether a person or an application is the primary record. Establish this first: getting it wrong means one candidate becomes five, or five applications collapse into one, and the entire field map has to be redone.
Candidate-centric and application-centric models are not interchangeable. Confirm which Ceipal uses before mapping any field.
Schema Mapper Match Bullhorn fields to Ceipal by uploading both schemas -
Map pipeline stages and rejection reasons exhaustively
Enumerate every stage and rejection reason across all jobs, including retired values on historical applications, and map each explicitly. Unmapped rejection reasons are both a reporting gap and, in regulated hiring, a compliance one.
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Decide EEO and diversity data handling
These fields are separately regulated and often legally required to be stored apart from the candidate record. Confirm with legal whether they migrate at all, and how Ceipal isolates them.
EEO data usually cannot be migrated into ordinary custom fields without breaching the segregation rules that govern it.
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Map interviews, scorecards and feedback
Structured scorecards rarely have a native equivalent. Decide whether to reconstruct them, flatten them into notes, or keep them only in the archive — and be explicit that flattening loses the ability to report on them.
JSON to CSV Converter Flatten nested API responses into a reviewable sheet -
Plan resume and file migration
Confirm size limits, MIME support and whether Ceipal re-parses resumes on upload. Re-parsing can overwrite carefully curated candidate fields with worse machine-extracted values, so test it deliberately.
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Set load order and freeze the spec
Users, then jobs, then candidates, then applications, then interviews and scorecards, then files. Keep source IDs in custom fields, then version and sign off the spec.
Don't move on until
- Candidate/application/job model mapped and reviewed
- Every stage and rejection reason explicitly mapped
- EEO and diversity field handling agreed with legal
04 Test Migration Pilot whole candidate journeys, not isolated records.
Objective A sandbox pilot where candidate journeys, funnel metrics and resume files all verify.
Keep these open
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Configure the Ceipal sandbox with the agreed pipelines
Create jobs, pipeline stages, scorecard templates, user roles and custom fields first. Loading applications before the stages exist puts every candidate in a default stage and invalidates the pilot.
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Select complete candidate journeys as the pilot slice
Take 100-200 candidates with all their applications, interviews, scorecards and files — including repeat applicants, hires, rejections at every stage, and candidates on multiple jobs. Repeat applicants are where the model mapping actually gets tested.
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Run the load in dependency order with logging
Jobs, candidates, applications, interviews, then files, logging each request against its source ID. Track file uploads separately: they fail for different reasons and at different rates than record writes.
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Verify journeys and funnel metrics
Confirm each candidate sits at the right stage on the right job with their history intact, and that per-stage funnel counts match Bullhorn for the pilot jobs. Funnel mismatches point straight back to stage mapping.
Migration Validation Tool Diff the pilot batch against source before scaling up -
Open every pilot resume and check re-parsing
Actually open the files rather than trusting the upload count, and check whether re-parsing has overwritten any candidate fields. A resume that uploaded as a zero-byte file still counts as a success in most logs.
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Put recruiters in front of the pilot data
Have recruiters work their own pilot requisitions end to end. They immediately spot missing feedback, wrong stages and unreadable history that reconciliation cannot see.
Don't move on until
- Candidate-application-job relationships intact for the pilot
- Funnel counts per stage match source for pilot jobs
- Resume files open correctly for every pilot candidate
05 Cutover Switch recruiting without dropping a live candidate.
Objective All in-scope recruiting data live in Ceipal, careers site and boards repointed, recruiters working.
Keep these open
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Pre-load historical candidates and closed jobs
Load closed requisitions, rejected candidates and archived applications while Bullhorn stays live. Only active pipeline and the final delta need to move in the window.
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Publish the runbook including the careers-site switch
A timed sequence with owners and abort criteria, treating the careers site and job boards as first-class steps. They are candidate-facing, so a failure there is publicly visible in a way a data defect is not.
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Freeze Bullhorn and take the final delta
Stop new applications and let recruiters finish in-flight actions, then export everything changed since the pre-load. Coordinate with anyone actively interviewing so feedback is not entered into the old system mid-freeze.
Interview feedback entered in the old ATS during the freeze is lost, and it is the data recruiters most immediately notice missing.
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Load active pipeline and reconcile stages
Load active candidates and applications, then verify every active candidate is at the correct stage on the correct job before repointing anything. Active-stage accuracy is what recruiters check first on day one.
Migration Validation Tool Confirm the final delta landed before you reopen -
Repoint careers site, job boards and integrations
Switch the careers-site integration, repost or migrate live job ads, and repoint HRIS, background check, assessment and calendar integrations. Then submit a real test application through the careers site and every major board.
Job ads left posted against the old ATS keep collecting applications that never reach the new system.
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Go/no-go and switch recruiters over
Call the decision against the exit criteria, then move recruiters with support on hand for the first day. Keep Bullhorn read-only — candidate records have retention obligations that outlast the migration.
Don't move on until
- Historical load complete and reconciled before the freeze
- Careers site and job boards posting into Ceipal and verified
- Active candidates confirmed at the correct stage
06 Validation Prove the funnel, the files and the compliance position.
Objective Reconciled recruiting data, funnel parity with baseline, and a defensible compliance record.
Keep these open
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Reconcile every object including files
Compare counts for candidates, applications, jobs, interviews, scorecards and files, with field-level spot checks on a sample. Count files separately — they are the object most likely to be quietly short.
Migration Validation Tool Reconcile Bullhorn and Ceipal record-for-record -
Tie funnel and time-to-hire reporting to baseline
Rebuild funnel conversion, time-to-hire, source effectiveness and offer-acceptance reporting and compare to pre-migration figures. Variances trace back to stage mapping and to how application timestamps were handled.
Time-to-hire depends on stage-transition timestamps. If those were approximated, the metric will differ even with identical records.
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Verify file integrity at scale
Sample-open resumes across the whole load and compare file sizes against source. Zero-byte and truncated files are common and never surface in an upload success count.
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Confirm retention, consent and EEO configuration
Verify retention rules, consent state and EEO segregation are correctly configured in Ceipal, and that excluded records genuinely did not migrate. File this as your compliance evidence.
PII & Compliance Scanner Produce the compliance evidence your auditor will ask for -
Test workflow, notifications and candidate-facing paths
Fire every stage automation, interview scheduling flow, rejection template and offer approval, and submit a live application through the careers site. Candidate-facing emails going out wrong is a brand problem, not just a bug.
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Sign off and schedule decommission
Get written acceptance against the Discovery criteria, retain Bullhorn read-only for the period your retention policy requires, take a final archive export, and diarise cancellation.
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Rebuild automations
Bullhorn workflows, triggers, and saved searches don't transfer. Recreate them in Ceipal's workflow builder.
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Configure integrations
Reconnect job boards, email, calendar, and VMS integrations in Ceipal.
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Monitor for 30 days
Watch for missing data, broken links, and recruiter-reported issues. Run daily count comparisons for the first week.
Bullhorn → Ceipal specifics
- Train recruiters
- Ceipal's UI and terminology differ from Bullhorn. Plan 1–2 days of hands-on training.
- Decommission Bullhorn
- Only after validation is complete and the team has been running on Ceipal for at least 30 days.
- Full validation
- record counts, field-level sampling, and relationship integrity checks before handoff.
Don't move on until
- Reconciliation complete across candidates, applications and files
- Funnel and time-to-hire reporting tie to baseline
- Retention and EEO configuration verified, acceptance signed
Field mapping reference
The field-by-field mapping for each object. Use this as the starting point for your mapping spec.
Entity Equivalent
| Bullhorn field | Ceipal field | Notes |
|---|---|---|
| Candidate | Applicant | Direct mapping; field-level differences |
| ClientCorporation | Client | Company records |
| ClientContact | Client Contact (within Client) | Ceipal nests contacts under clients |
| JobOrder | Job Posting | Field names differ significantly |
| JobSubmission / Application V2 | Submission | Most complex mapping. Bullhorn stage histories must translate to Ceipal pipeline stages. |
| Placement | Placement | Billing and financial fields differ |
| Opportunity | Lead or external CRM | Ceipal's public ATS docs do not show a first-class Opportunity resource. Redesign rather than 1:1 load. (developer.ceipal.com) |
| Note | Notes / Activity | No standalone "create note" endpoint in Ceipal v1 API |
| Appointment (type=Interview) | Interview | Watch for Bullhorn parent/child appointment duplication |
| Application History | No equivalent | Audit trail not portable |
| Tearsheet | No equivalent | Candidate lists — recreate manually |
| Custom Objects | Custom Fields | Flatten into Ceipal custom fields |
Tools used in this playbook
All free, all run entirely in your browser — nothing is uploaded.
FAQ
Can I migrate from Bullhorn to Ceipal using CSV exports?
Yes, but CSV exports flatten relationships and lose Application V2 stage history, attachments, and notes. It's only viable for small datasets under 5,000 records with simple field structures.
What are Bullhorn's API rate limits for data migration?
Bullhorn allows 1,500 API requests per minute per OAuth Client ID, up to 50 concurrent sessions (Enterprise), and 100,000 total API calls per month unless negotiated. Exceeding the per-minute limit returns a 429 error — wait 1 second and retry. Calls returning 429 do not count against your limits.
Does Ceipal offer free data migration from Bullhorn?
Yes, Ceipal provides complimentary data migration assistance for new customers. Their team has migrated databases of up to 1 million records from 30+ ATS platforms. However, highly customized Bullhorn environments with custom objects or complex stage configurations may exceed their standard mapping templates.
What Bullhorn data cannot be migrated to Ceipal?
Application V2 stage history, Application History audit trails, Tearsheets (hot lists), Opportunities (no first-class Ceipal equivalent), saved Lucene searches, email integration history, and Bullhorn-specific workflow automations have no direct Ceipal equivalents. Custom objects must be flattened into custom fields.
How long does a Bullhorn to Ceipal migration take?
Timelines vary by volume and complexity. A small agency (<5K records) with CSV import can finish in days. Enterprise migrations (100K+ records) with attachments and custom objects typically take 2–6 weeks including testing and validation.