HRMS migration

Migrate from Kula to Recruit CRM & ATS

Field-level mapping, validation, and rollback between Kula and Recruit CRM & ATS. We move data and schema; workflows are rebuilt natively in Recruit CRM & ATS.

Kula logo

Kula

Source

Recruit CRM & ATS

Destination

Recruit CRM & ATS logo

Compatibility

92%

11 of 12

objects map 1:1 between Kula and Recruit CRM & ATS.

Complexity

BStandard

Timeline

3-5 weeks

Rollback included Accuracy guarantee Field-level validation

Overview

What this migration involves

Moving from Kula to Recruit CRM shifts from an AI-first ATS built for mid-market tech teams to a recruitment-agency CRM focused on candidate pipeline management, client relationships, and placement tracking. The migration centers on resolving Kula's Candidate-to-Job application model against Recruit CRM's candidate database structure, where the same candidate record can link to multiple jobs and clients. Kula's AI resume scores and interview summaries carry over as static text fields because Recruit CRM does not expose an equivalent scoring engine via API. Pipeline stages, custom fields, tags, and interviewer assignments require field-by-field mapping during scoping. We do not migrate Kula's career site configurations, outreach templates with conditional logic, or workflow automations; these require manual rebuild in Recruit CRM or are excluded from standard scope entirely.

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

Kula logo

Kula

What's pushing teams away

  • Reporting is consistently described as the weakest feature — dashboards lack depth, customization options are limited, and historical analytics require manual exports to fill gaps.
  • The platform attempts to cover too many recruiting scenarios at once, adding workflow complexity that teams with simple hiring processes find unnecessary.
  • As a newer ATS, Kula ships frequent updates that occasionally introduce bugs, slow screen loads, or sync issues between features that require workarounds.

Choosing

Recruit CRM & ATS logo

Recruit CRM & ATS

What's pulling them in

  • Agencies choose Recruit CRM for its full customizability — pipelines, stages, and fields can be tailored to any recruitment workflow without developer involvement.
  • Small teams value the built-in CRM and ATS combined in one subscription, eliminating the need to purchase and sync separate systems.
  • The Chrome extension for one-click LinkedIn profile collection streamlines candidate sourcing and reduces manual data entry for recruiters.
  • Responsive customer support with fast issue resolution is consistently cited as a reason teams stick with the platform long-term.
  • Automation options including email sequences and workflow triggers allow recruitment agencies to reduce repetitive manual outreach tasks.

Object mapping

How Kula objects map to Recruit CRM & ATS

Each row shows how a Kula object lands in Recruit CRM & ATS, including any object-level transformations, lookup resolution, or schema-design dependencies.

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

Kula

Candidate

maps to

Recruit CRM & ATS

Candidate

1:1
Fully supported

Kula Candidate records map directly to Recruit CRM Candidate records. Contact information, work history, sourced profile data, and tags transfer as standard fields. Kula's AI-generated resume scores transfer as read-only text fields (not live metrics) because Recruit CRM has no equivalent scoring engine. Candidate status from Kula (active, archived, disqualified) maps to Recruit CRM's status field with a custom status_reason field preserving the original Kula value.

Kula

Job

maps to

Recruit CRM & ATS

Job

1:1
Fully supported

Kula Job records (requisitions) map to Recruit CRM Job records with stage pipeline, assigned team members, and interviewer pool references transferred. Active versus closed status is preserved. Job type, location, and salary range fields map to Recruit CRM's equivalent structured fields. Kula's job-specific custom fields transfer to Recruit CRM job-level custom fields, created during the schema configuration phase before data import.

Kula

Application

maps to

Recruit CRM & ATS

Candidate-to-Job Link

1:1
Fully supported

Kula Application records (linking a Candidate to a Job) map to Recruit CRM's candidate-job association model. Source attribution (direct, referral, sourced-linkedin), submission date, current stage, and any rejection or offer outcome transfer as structured fields on the candidate-job link. Stage progression history is preserved as a series of status-change timestamps on the link record.

Kula

Interview

maps to

Recruit CRM & ATS

Interview

1:1
Fully supported

Kula Interview records (scheduled rounds, interviewer assignments, and feedback) map to Recruit CRM Interview records. We transfer interviewer names, scheduled date and time, interview type, and reviewer notes. Note that Kula's availability-aware scheduling engine does not have a Recruit CRM equivalent; scheduling rules and interviewer availability settings are destination-dependent and must be reconfigured post-migration. Deleted meetings do not sync back from Google Calendar to Recruit CRM; this is a known limitation documented in Recruit CRM's own community forums.

Kula

Scorecard

maps to

Recruit CRM & ATS

Interview Evaluation

1:1
Fully supported

Kula scorecard templates and submitted evaluations map to Recruit CRM interview evaluation records. We transfer reviewer name, evaluation date, rating values, and reviewer notes as structured text. Scorecard templates themselves (the rating criteria definitions) do not have a direct Recruit CRM equivalent and are documented as a configuration requiring manual rebuild in Recruit CRM's evaluation setup area.

Kula

AI Summary

maps to

Recruit CRM & ATS

Candidate Note (static)

1:1
Fully supported

Kula AI-generated interview summaries transfer as static Note records attached to the candidate or interview in Recruit CRM. These are preserved as reference text, not as linked metrics or scores. The original Kula AI score (numeric or tiered) transfers to a custom number field on the candidate record for reporting purposes, but the score does not trigger any Recruit CRM workflow or ranking behavior.

Kula

Pipeline Stage

maps to

Recruit CRM & ATS

Job Stage

lossy
Fully supported

Kula customizable pipeline stages per job are extracted from the source instance. We recreate an equivalent stage configuration in Recruit CRM by creating matching job stages in the order defined in Kula, preserving stage names and probability values where Kula exposes them. Any non-standard stages (stages with custom skip logic or conditional advancement rules) are flagged for manual review because such rules do not transfer.

Kula

Custom Field

maps to

Recruit CRM & ATS

Custom Field

1:1
Fully supported

Both Kula and Recruit CRM support custom fields on Candidates, Jobs, and Applications. We extract the custom field definitions and values from Kula, then map them to Recruit CRM custom fields created during schema configuration. Field types are mapped (Kula text to Recruit CRM text, Kula number to Recruit CRM number, Kula date to Recruit CRM date). Custom fields without a clear Recruit CRM equivalent are flagged and stored as text notes for customer review.

Kula

Tag

maps to

Recruit CRM & ATS

Tag

1:1
Fully supported

Kula tags applied to candidates (referral, sourced-linkedin, screening-pass, etc.) transfer as tags or custom properties in Recruit CRM. We preserve the tag label and apply it to the corresponding candidate record. Recruit CRM imposes tag name and count limits at certain subscription tiers; we flag any tag that exceeds those limits for customer review and tag consolidation strategy.

Kula

User / Team Member

maps to

Recruit CRM & ATS

User

1:1
Fully supported

Kula recruiter owners, hiring managers, and interviewers map to Recruit CRM User records resolved by email match. We extract every distinct user referenced on Jobs, Applications, Interviews, and Scorecards and match against the Recruit CRM user list. Any Kula user without a matching Recruit CRM account is held in a reconciliation queue for the customer's admin to provision before record import resumes.

Kula

Interviewer Pool

maps to

Recruit CRM & ATS

Interviewer Assignment

1:1
Fully supported

Kula interviewer pool membership records transfer as individual interviewer assignments on the relevant job or interview in Recruit CRM. Scheduling rules and availability windows managed in Kula's interviewer pool do not transfer because Recruit CRM lacks an equivalent scheduling-balance feature. The customer's Recruit CRM admin rebuilds interviewer availability settings post-migration.

Kula

Email / SMS Template

maps to

Recruit CRM & ATS

Email Template

1:1
Fully supported

Kula outreach templates used in automated candidate communication can be exported and mapped to Recruit CRM email templates. Rich formatting and conditional merge field logic may require manual reconstruction in Recruit CRM's template editor. We document the original template structure and flag any templates with complex conditional logic for admin rebuild.

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.

Kula logo

Kula gotchas

Medium

AI-generated scores do not carry over as live metrics

Medium

Reporting exports require a separate manual step

Low

Frequent platform updates can change field behavior

Recruit CRM & ATS logo

Recruit CRM & ATS gotchas

High

API rate limits are license-scaled and can throttle bulk migration

Medium

Custom field schemas vary per organization and require field-level mapping

Medium

Files and email attachments require separate extraction and re-upload

Low

Email sequences and automation logic do not transfer between platforms

Pair-specific challenges

  • Deleted Google Calendar meetings do not sync back to Recruit CRM

    Recruit CRM's Google Calendar integration syncs events created or updated in Google Calendar to Recruit CRM, but it does not sync deleted events back to Recruit CRM. A meeting deleted in Google Calendar remains visible as a scheduled interview in Recruit CRM unless manually removed. We flag this during migration planning and advise customers to run a calendar reconciliation check post-migration or to rely on Recruit CRM as the authoritative interview scheduling record rather than Google Calendar. This limitation is documented in Recruit CRM's own community forums and affects teams migrating from Zoho Recruit, Bullhorn, and similar platforms with bidirectional calendar sync.

  • AI-generated scores migrate as static text, not live metrics

    Kula's in-house AI generates resume scores and interview summaries that are computed by Kula's models. Recruit CRM has no equivalent AI scoring engine exposed via API. We preserve Kula's AI scores as read-only text fields and numeric custom fields on the candidate record so historical context is not lost. However, these scores do not trigger ranking, filtering, or workflow behavior in Recruit CRM. Customers expecting AI-powered candidate ranking in Recruit CRM must run a fresh scoring pass using Recruit CRM's available search and enrichment tools post-migration.

  • Kula platform updates can rename or deprecate fields before migration

    Kula ships updates regularly, which occasionally rename or recategorize fields in its API. We run a schema validation pass within 48 hours of migration start to catch any field discrepancies introduced by recent platform updates. If a field has been renamed or deprecated since scoping, we update the mapping and re-run validation before confirming the migration is complete. This is especially relevant for teams with active Kula subscriptions where updates may have occurred between discovery and migration execution.

  • Interview scheduling rules and availability settings do not transfer

    Kula's interviewer pool feature balances scheduling load across available team members using availability windows and interviewer preferences. Recruit CRM lacks an equivalent scheduling-balance engine. We transfer pool membership as individual interviewer assignments, but availability settings and scheduling rules require manual rebuild in Recruit CRM's calendar and interview scheduling setup. Teams relying heavily on Kula's automated scheduling should plan for a one-to-two week admin rebuild period post-migration.

  • Career site configurations and branded career page content cannot migrate

    Kula's branded career site builder with drag-and-drop templates, custom styling, and published job pages is not accessible via Kula's API. Career site content, URL structure, and job board distribution settings cannot be transferred to Recruit CRM. We flag the career site URL and page structure in the pre-migration checklist so customers can plan for a rebuild in Recruit CRM's career site builder or an alternative hosted careers page. Job board distribution settings for over 100 channels (a Kula feature) similarly require manual reconfiguration in Recruit CRM's distribution settings or via an integrated job board aggregator.

Migration approach

Six steps for a successful Kula to Recruit CRM & ATS data migration

  1. Discovery and schema audit

    We audit the source Kula instance across candidates, jobs, applications, interviews, scorecards, custom fields, tags, and user assignments. We document pipeline stage names and ordering, any custom stage advancement rules, AI score field locations, and interviewer pool configurations. We pair this with a Recruit CRM destination audit of existing fields, custom field capacity, tag limits, and user accounts. The discovery output is a written migration scope document listing every object, field, and dependency requiring mapping or rebuild.

  2. Schema configuration in Recruit CRM

    We create the destination schema in Recruit CRM before any data moves. This includes creating any custom fields on Candidate, Job, and Application records that correspond to Kula custom fields, recreating pipeline stage configurations with names and ordering matched to Kula, and setting up interview evaluation criteria that correspond to Kula scorecards. Tag consolidation occurs here if Kula tags exceed Recruit CRM tag limits. User accounts in Recruit CRM are validated or provisioned to match the Kula user list resolved by email.

  3. Data validation and pre-cleaning

    We run a data quality audit against Kula's candidate, job, and application records before migration. Duplicate candidates (same email, different records), records with missing required fields in Recruit CRM, and orphaned records (interviews linked to deleted candidates) are flagged in a pre-cleaning report. The customer reviews and resolves duplicates, fills missing required fields, and confirms how to handle orphaned records. This step prevents import rejections and reduces post-migration cleanup workload.

  4. Sandbox migration and reconciliation

    We run a full migration into a Recruit CRM staging environment using production-like data volume. The customer's recruiting operations lead reconciles record counts (candidates in, jobs in, applications in, interviews in), spot-checks 25-50 records against the Kula source, and validates that pipeline stages, tags, and interview assignments transferred correctly. Any mapping corrections and schema adjustments happen in this phase. Sign-off on the sandbox migration unlocks production migration.

  5. Production migration in dependency order

    We run production migration in record-dependency order: Recruit CRM Users first (validated from Kula user list), then Candidates (with AI scores and tags preserved), then Jobs (with stage configurations), then Applications (with candidate-to-job links and stage history), then Interviews (with interviewer assignments), then Scorecards and AI summaries (as notes and evaluation records), then custom fields last. Each phase emits a row-count reconciliation report. Any records that fail import are logged with error reason for resolution before the next phase begins.

  6. Cutover, validation, and admin rebuild handoff

    We freeze Kula writes during the cutover window, run a final delta migration of any records modified during the migration window, then set Recruit CRM as the system of record. We deliver a written inventory of Kula workflow automations, outreach templates with conditional logic, interviewer pool scheduling rules, and career site configurations requiring manual rebuild in Recruit CRM. We support a one-week post-migration window for reconciliation issues raised by the recruiting team.

Platform deep dives

Context on both ends of the pair

Kula logo

Kula

Source

Strengths

  • Built-in AI for resume scoring, interview summarization, and candidate notetaking without third-party LLM dependencies.
  • Active sourcing across LinkedIn and GitHub integrated directly into the candidate discovery workflow.
  • Clean, modern UI that hiring managers with no recruiting-tool background can navigate without training.
  • Automated interview scheduling aligned with interviewer availability and workload balancing.
  • Structured migration program with a dedicated implementation manager and a 4–6 week migration timeline.

Weaknesses

  • Reporting and analytics lag behind competitors — dashboards lack depth, customization is limited, and historical reporting requires manual workarounds.
  • Frequent feature updates occasionally introduce bugs, slow screen loads, or sync inconsistencies between modules.
  • Attempting to cover many recruiting scenarios adds workflow complexity that smaller teams with simple hiring needs may find excessive.
  • As a younger product, Kula lacks the long track record and ecosystem depth of established ATS platforms like Greenhouse or Lever.
Recruit CRM & ATS logo

Recruit CRM & ATS

Destination

Strengths

  • Fully customizable pipelines, stages, and fields without requiring developer involvement
  • Combines recruitment CRM and ATS in one subscription for staffing agencies and small teams
  • Built-in email sequences and automation reduce manual outreach work
  • Chrome extension enables one-click LinkedIn profile collection directly into the CRM
  • Responsive customer support cited across multiple reviews with fast resolution times

Weaknesses

  • Several features are gated as paid add-ons rather than included in the base subscription
  • Email functionality has been reported as unreliable by multiple users
  • Interface occasionally lags during high-activity periods in large pipelines
  • Pricing is considered higher than comparable recruitment CRMs by some customers
  • Limited native reporting — users request pre-made report exports rather than manual data pulls

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 Kula and Recruit CRM & ATS.

  • 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

    Kula: Not publicly documented.

  • Data volume sensitivity

    A

    Kula exposes a bulk API — large-volume migrations stream efficiently.

Estimator

Estimate your Kula to Recruit CRM & ATS 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 Kula to Recruit CRM & ATS data migrations

Answers to the questions buyers ask most during Kula to Recruit CRM & ATS 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, 500 jobs, and no complex custom field schemas. Migrations with large interview histories (over 5,000 interview records), complex custom field configurations, multiple interviewer pool assignments, or data requiring pre-cleaning move to six to ten weeks because of the pre-cleaning phase and the manual rebuild work for interview scheduling rules.

Adjacent paths

Related migrations to explore

Ready when you are

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