HRMS migration

Migrate from Jarvi to BambooHR

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

Jarvi logo

Jarvi

Source

BambooHR

Destination

BambooHR logo

Compatibility

80%

8 of 10

objects map 1:1 between Jarvi and BambooHR.

Complexity

BStandard

Timeline

2-3 weeks

Rollback included Accuracy guarantee Field-level validation

Overview

What this migration involves

Jarvi is an ATS and CRM built for recruiting agencies; BambooHR is an HRIS built for small and medium businesses that added a hiring module as an add-on. These are different system categories, and the migration scope reflects that. We migrate Jarvi Contacts (client-facing recruiter relationships) into BambooHR as Employee records when the contact is a current or former staff member, and we preserve Jarvi Company records as organizational context. We do not migrate Candidates or Jobs into BambooHR's core employee model because candidates are not employees and BambooHR's applicant tracking is a separate module with a different data model. We deliver a written inventory of all Jarvi Jobs and pipeline stages for your BambooHR admin to recreate in the hiring module. Custom fields migrate via BambooHR's field-ID schema fetch, and we apply exponential backoff for BambooHR's undocumented rate limits throughout the process.

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

Jarvi logo

Jarvi

What's pushing teams away

  • Profile import updates from LinkedIn and other sources run on a scheduled basis (reportedly every 6 months for some imports), leaving candidate data stale between sync cycles and frustrating recruiters who need real-time information.
  • The Magic Reply AI feature and automated message variables lack polish—reviewers note that capitalization handling and multi-word field parsing in auto-generated messages produce awkward output requiring manual correction.
  • Some users report the platform still lacks certain advanced features present in larger competitors, and while the roadmap is active, feature gaps in reporting depth and advanced automation frustrate power users.

Choosing

BambooHR logo

BambooHR

What's pulling them in

  • Lowest friction entry point for SMBs moving off spreadsheets — intuitive interface means most teams are functional within days, not weeks.
  • Consolidation value: BambooHR merges ATS, onboarding, HR records, time-off, and payroll into a single pane of glass that employees never need to leave.
  • Volume discounts applied automatically by headcount, so pricing scales predictably as the company grows without renewal negotiations.
  • BambooHR reports most customers go live in four to six weeks, making it a realistic commitment for under-resourced HR teams.
  • Award-winning Support Heroes cited frequently in reviews — responsive human support after implementation is a differentiator.

Object mapping

How Jarvi objects map to BambooHR

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

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

Jarvi

Contact

maps to

BambooHR

Employee

1:1
Fully supported

Jarvi Contacts (recruiter client relationships, internal staff contacts) map to BambooHR Employee records. The mapping requires a pre-migration segmentation step: Contacts who are current or former staff members migrate as BambooHR Employees with full employee fields populated; external client contacts that are not employed by the customer's organization cannot map to BambooHR Employees (BambooHR enforces per-employee licensing). For external contacts, we export them as a CSV reference document attached to the migration handoff. Email, phone, company association, and custom Contact fields migrate to the corresponding BambooHR employee fields fetched via GET /v1/meta/fields.

Jarvi

Company

maps to

BambooHR

Employee (workLocation + custom org fields)

lossy
Fully supported

Jarvi Company records (firmographic data on client organizations) do not have a direct BambooHR equivalent because BambooHR is employee-centric rather than account-centric. We map Company name and industry to custom text fields on the Employee record or to a BambooHR custom lookup table (implemented as a custom Employee field) if the customer uses BambooHR's custom field API. Location data maps to BambooHR workLocation. This is a structural limitation of the ATS-to-HRIS migration and is flagged during scoping.

Jarvi

Candidate

maps to

BambooHR

Applicant (BambooHR Hiring module)

1:1
Fully supported

Jarvi Candidates cannot migrate directly into BambooHR's core Employee object because candidates are not current employees. BambooHR offers a separate Hiring module for applicant tracking, but it is a bolt-on module with a different object model (Applicants, Job Openings, Pipeline Stages) rather than a native ATS equivalent. We export all Candidate records as a structured CSV with all standard and custom fields for the customer's BambooHR admin to manually import into the BambooHR Hiring module. AI-generated candidate summaries from Jarvi export as a custom text column in that CSV.

Jarvi

Job

maps to

BambooHR

Job Opening (BambooHR Hiring module)

1:1
Fully supported

Jarvi Jobs (requisitions and postings) map conceptually to BambooHR Job Openings in the Hiring module, but the object schemas are not compatible for direct API-to-API migration. We export Jobs as a structured data document including job title, description, posting channels, associated pipeline stages, and candidate count per stage. The customer's BambooHR admin recreates these as Job Openings in the Hiring module. Job-to-candidate associations are preserved in the candidate export CSV so they can be re-established manually in BambooHR Hiring.

Jarvi

Pipeline Stage

maps to

BambooHR

Hiring Pipeline Stage (BambooHR Hiring module)

lossy
Fully supported

Jarvi custom pipeline stage definitions per Job do not have a direct BambooHR equivalent in the core HRIS. Stages map to BambooHR Hiring pipeline stages (Offer, Interview, Application Review) only if the customer licenses the BambooHR Hiring module. We extract the complete stage schema (names, ordering, win/loss states) as a configuration inventory for the admin to rebuild in the Hiring module. Stage-specific candidate counts are included in the Job export.

Jarvi

Activity

maps to

BambooHR

Not migratable

1:1
Fully supported

Jarvi Activity records (emails, LinkedIn messages, WhatsApp, calls, meetings linked to Contacts or Candidates) have no equivalent in BambooHR's employee-centric data model. BambooHR does not store outreach activity history as a first-class object. We export the full activity timeline as a timestamped CSV per Contact for the customer's records, but these do not migrate into BambooHR as native objects. This is a known limitation of the ATS-to-HRIS migration pattern.

Jarvi

Custom Fields (Contacts and Candidates)

maps to

BambooHR

Custom Employee Fields

1:1
Mapping required

Jarvi exposes custom fields via a UUID-based Custom Fields API. BambooHR requires a pre-migration schema fetch via GET /v1/meta/fields to retrieve the numeric field IDs assigned per account. Custom field values map to BambooHR custom employee fields by matching field type (text to text, number to number, date to date, dropdown to dropdown). We do not hardcode BambooHR field IDs because they vary per account. Any Jarvi custom field type without a BambooHR equivalent is flagged and exported as a CSV column in the handoff document.

Jarvi

Attachments (Resumes, Cover Letters)

maps to

BambooHR

Employee Files

1:1
Fully supported

Jarvi resume and cover letter attachments linked to Candidate profiles export as file references and binary blobs. These do not migrate as native BambooHR employee file attachments because BambooHR's file storage model is scoped to employee records (new hires, onboarding documents) rather than applicant resumes. We export attachments as a structured folder set (per candidate) and deliver them alongside the candidate CSV so the customer's admin can manually attach them in BambooHR Hiring if applicable.

Jarvi

Conversations (LinkedIn, WhatsApp, Telegram, Email)

maps to

BambooHR

Not migratable

1:1
Fully supported

Jarvi's unified multichannel inbox (LinkedIn InMail, email, WhatsApp, Telegram threads per Contact or Candidate) has no equivalent in BambooHR. This is a CRM-layer feature that does not exist in an HRIS data model. We export conversation thread metadata (participant, channel, timestamp, snippet) as a CSV reference for audit purposes, but the full threaded conversation history does not migrate into BambooHR.

Jarvi

AI Summaries (Jarvi agent output)

maps to

BambooHR

Custom text field or CSV export

1:1
Fully supported

Jarvi AI-generated candidate summaries and evaluations are stored as linked data points rather than standalone objects. When exporting candidates, these summaries land as a custom text column in the candidate CSV. If BambooHR has a custom long-text field available on the Applicant object in the Hiring module, we map the summary there; otherwise it is preserved in the exported CSV. This mirrors how we handle AI summaries in all Jarvi outbound migrations.

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.

Jarvi logo

Jarvi gotchas

Medium

Profile import endpoint is unpaginated

Low

AI-generated profile summaries are not native objects

Medium

LinkedIn data freshness depends on sync schedule

BambooHR logo

BambooHR gotchas

High

Undocumented API rate limits can trigger 503 errors

High

Per-employee pricing model requires active record count verification

Medium

API credentials must be sent on every request to avoid extra round trips

Medium

Custom field schema varies per account and requires manual inventory

Low

Document and attachment exports are not covered by standard report exports

Pair-specific challenges

  • ATS-to-HRIS model gap means candidates and jobs do not migrate natively

    Jarvi's primary objects are Candidates and Jobs (ATS layer) and Contacts and Companies (CRM layer). BambooHR is an HRIS with an employee-centric data model. Candidates and Jobs have no direct equivalent in BambooHR's core Employee object, and the BambooHR Hiring module is a separate bolt-on with a different object schema. We export Candidates, Jobs, and pipeline stage definitions as structured CSV documents, but the customer's BambooHR admin must recreate these in the Hiring module manually. This is not a data-loss issue caused by the migration process—it is a structural mismatch between system categories that must be addressed during scoping, not during migration.

  • BambooHR field IDs are assigned per account and must be fetched dynamically

    BambooHR does not expose a stable global field ID schema. Custom field IDs are numeric and assigned per account, meaning the same custom field will have different IDs across two BambooHR tenants. We must call GET /v1/meta/fields at the start of every migration to retrieve the field schema before any custom field mapping can occur. This adds a discovery step to the migration timeline. Field IDs cannot be hardcoded from documentation or prior migrations, and any integration built against a previous BambooHR customer's field IDs will break if pointed at a new tenant without re-fetching the schema.

  • BambooHR rate limits return 503, not 429, and are undocumented

    BambooHR does not publish exact rate limits and does not return a standard 429 Too Many Requests response. When the per-API-key limit (approximately 100 requests per minute) is exceeded, the API returns 503 Service Unavailable. Additionally, no Retry-After header is guaranteed. We implement exponential backoff on 503 responses throughout the extraction and load phases, and we treat any 5xx response from BambooHR as a rate-limit signal rather than a transient server error unless subsequent retries confirm the endpoint is genuinely down. This pacing strategy adds time to large data extractions.

  • Jarvi profile endpoint is unpaginated, creating extraction risk at scale

    The Jarvi API profiles endpoint returns all candidate and contact records in a single response with no pagination. For large recruiting agencies with thousands of profiles, this means the entire record set loads as one payload, risking memory exhaustion or timeout during extraction. We stream the response in chunks on our end and request the data in manageable batches, flagging expected record counts during scoping so the customer knows the volume before extraction begins. This is a known Jarvi API constraint that affects all migrations out of Jarvi, not just this pair.

Migration approach

Six steps for a successful Jarvi to BambooHR data migration

  1. Discovery and ATS-versus-HRIS scope gate

    We audit the Jarvi portal for Contacts, Companies, Candidates, Jobs, pipeline stage definitions, custom field schemas, attachment volumes, and activity history. We identify which Contacts are current/former staff (migratable to BambooHR Employees) versus external client contacts (exported as CSV reference only). We confirm whether the customer licenses the BambooHR Hiring module, because that determines whether Job and Candidate exports map to a BambooHR-native module or remain as CSV handoff documents. The discovery output is a written migration scope that explicitly gates unmigratable objects before extraction begins.

  2. BambooHR schema fetch and custom field mapping design

    We call GET /v1/meta/fields on the destination BambooHR tenant to retrieve the full field schema including numeric IDs for all custom fields. We cross-reference the Jarvi custom field schema against the BambooHR field schema to identify direct mappings (text-to-text, number-to-number), type conversions (date formats, dropdown values), and orphaned fields with no BambooHR equivalent. We design the custom field mapping table per account before any data extraction begins.

  3. Contact segmentation and Employee pre-creation

    We run Contact segmentation: current and former staff members identified by employment status properties or domain-matching logic are flagged for Employee migration. External client contacts are flagged for CSV export. For staff Contacts migrating to Employees, we verify that the BambooHR tenant has capacity under its employee count license. Any Contacts that reference Companies without a migratable equivalent are noted for custom org-field mapping.

  4. Sandbox migration and reconciliation

    We run a full migration into a BambooHR sandbox (if available) or a parallel production trial import with a subset of records. We reconcile record counts (Contacts in, Employees created, Companies mapped, custom fields populated), spot-check field values against the Jarvi source, and verify that BambooHR field validation rules are satisfied. Mapping corrections and custom field ID updates occur here before the production migration window opens.

  5. Production migration in dependency order

    We run production migration in dependency order: BambooHR custom field schema (validated), then Employees (from staff Contacts), then Employee custom fields populated, then Company org context attached. Candidate and Job exports run in parallel as CSV documents. Activity history exports as timestamped CSV per Contact. Attachment binaries export as a structured folder set per candidate. Each phase emits a row-count reconciliation report. BambooHR rate-limit pacing is applied throughout using exponential backoff on 503 responses.

  6. Cutover, delta pass, and migration handoff

    We freeze Jarvi writes during cutover and run a final delta migration for any Contact or Employee records modified during the migration window. We enable BambooHR as the system of record for HR data. We deliver the Candidate CSV, Job export, Pipeline Stage configuration inventory, Activity history CSV, and Attachment folder set to the customer's BambooHR admin with instructions for the Hiring module import. We do not rebuild Jarvi hiring workflows, sequences, or pipeline automations in BambooHR Hiring; those are documented as a separate rebuild task in the handoff.

Platform deep dives

Context on both ends of the pair

Jarvi logo

Jarvi

Source

Strengths

  • All-in-one ATS plus CRM eliminates the need for separate subscriptions, combining candidate tracking with client relationship management under one roof.
  • Built-in AI agent covers resume parsing, candidate matching, outreach drafting, and meeting note-taking at no additional cost per seat.
  • Native multichannel communication hub integrates LinkedIn (all license types), email, WhatsApp, and Telegram into a single searchable inbox.
  • Efficient data management and positive onboarding experience are cited by customers as reducing time-to-productivity for new users.
  • Modern interface with responsive customer support and a proactive product team with frequent feature releases.

Weaknesses

  • Profile updates from external sources (LinkedIn, resume imports) run on a scheduled cadence rather than real-time, potentially leaving candidate data outdated between sync windows.
  • Advanced automation capabilities and reporting depth trail those of larger enterprise ATS platforms, limiting appeal for high-volume agency operations.
  • AI-generated content (outreach messages, summaries) still requires human review and editing, particularly for edge cases in variable handling and tone.
  • Pricing transparency is limited; the site does not publish per-seat or tier pricing publicly, requiring a sales conversation to obtain a quote.
BambooHR logo

BambooHR

Destination

Strengths

  • Single platform consolidating ATS, onboarding, HR records, payroll, and time-off reduces system sprawl for SMBs.
  • Fast implementation — BambooHR reports four to six weeks from kickoff to go-live for most customers.
  • Per-employee pricing with automatic volume discounts makes cost predictable as headcount grows.
  • Strong customer support reputation (Support Heroes) cited consistently across G2, Capterra, and direct testimonials.
  • Well-documented API with UTF-8 encoding, clear field types, and HTTPS-only access.

Weaknesses

  • Mobile application is significantly limited compared to the desktop experience, frustrating remote and field workers.
  • Companies above 150–200 employees frequently outgrow the platform's feature depth and customization surface.
  • Limited advanced reporting and analytics compared to enterprise HR platforms — custom report building is the ceiling.
  • PTO and profile customization are pain points — non-standard accrual policies and complex org structures require workarounds.
  • Document management and attachment handling lack the granularity of dedicated document-centric HR systems.

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 Jarvi and BambooHR.

  • 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

    Jarvi: Not publicly documented..

  • Data volume sensitivity

    B

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

Estimator

Estimate your Jarvi to BambooHR 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 Jarvi to BambooHR data migrations

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

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Straightforward migrations covering Contacts, Companies, and custom fields under 1,000 records typically complete in two to three weeks. Migrations with large custom field schemas, complex Contact segmentation (mix of staff and external clients), or multiple attachment volumes move to four to eight weeks because of the BambooHR field-ID schema resolution work and rate-limit pacing. The candidate and job export (CSV handoff) runs in parallel and does not add significant time to the core migration timeline.

Adjacent paths

Related migrations to explore

Ready when you are

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