Helpdesk migration
Field-level mapping, validation, and rollback between Helpy and Freshdesk. We move data and schema; workflows are rebuilt natively in Freshdesk.
Helpy
Source
Freshdesk
Destination
Compatibility
6 of 8
objects map 1:1 between Helpy and Freshdesk.
Complexity
BStandard
Timeline
2-3 weeks
Overview
The Helpy-to-Freshdesk migration is a CSV-to-API translation. Helpy exposes no public REST endpoint for record creation, so we work through its documented CSV import templates to extract Customers, Tickets, Ticket Replies, KB Articles, and Categories. Those records are then transformed into typed Freshdesk API payloads and written via the Freshdesk REST API (available from Blossom plan and above). The primary structural difference is that Helpy organizes KB content under a flat Category layer, while Freshdesk uses a Category > Section > Article hierarchy — we reconstruct that tree during the KB pass. Ticket Replies are a discrete import type in Helpy, referenced by parent ticket number; we sort them chronologically before sequencing them into Freshdesk's conversation thread model. Attachments do not migrate via Helpy's CSV path; we extract them to a managed CDN bucket and deliver a post-migration reference table mapping each ticket to its attached file URLs. Automations, workflows, and any active rule sets in Helpy are not migratable and are delivered as a written inventory for the customer's admin to rebuild in Freshdesk.
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 Helpy object lands in Freshdesk, including any object-level transformations, lookup resolution, or schema-design dependencies.
Typical mapping — final map is confirmed during the sample migration step.
Helpy
Customer
Freshdesk
Contact
1:1Helpy customer records export via CSV with name, email, company, and locale fields. We transform these into Freshdesk Contact API payloads, mapping the Helpy email field to Freshdesk's email property, name to name, and company to the company_id lookup. Any locale or timezone metadata from Helpy becomes a custom Contact field in Freshdesk. Email uniqueness serves as the dedupe key during import.
Helpy
Ticket
Freshdesk
Ticket
1:1Helpy ticket CSV exports include subject, body, priority, status, assignee email, and channel. We map status values (open, pending, resolved, closed) to Freshdesk Ticket status integers, priority to priority integers, and assignee email to a Freshdesk agent lookup resolved via the Freshdesk agents endpoint. The original Helpy ticket ID is preserved in a custom field for audit and cross-referencing.
Helpy
Ticket Reply
Freshdesk
Conversation (Ticket Reply)
1:1Helpy Ticket Replies are a standalone CSV type referenced by parent ticket number. We sort all reply records by created_at timestamp before writing, then post each reply to Freshdesk's conversations API endpoint as an inbound reply on the target ticket. Parent ticket existence is verified against Freshdesk before the reply pass begins to prevent dropped threads. Private notes and public replies are distinguished by a flags column if present in the Helpy CSV.
Helpy
Category
Freshdesk
Category + Section
1:manyHelpy's flat Category layer maps to Freshdesk's two-level KB hierarchy. Each Helpy Category becomes a Freshdesk Category; if the Helpy category contains more than 20 articles or spans distinct topic groups, we recommend splitting into multiple Freshdesk Sections under the parent Category. The customer decides the split strategy during scoping. Category sort order from Helpy's CSV column_index field is preserved in Freshdesk display_order.
Helpy
Knowledge Base Doc
Freshdesk
Article
1:1Helpy KB Docs export via CSV with title, body (markdown or HTML depending on installation), meta keywords, and category_id reference. We map body content to Freshdesk's article description, apply HTML sanitization if the source is markdown, and wire the article to the target Freshdesk Category and Section. Meta keywords become Freshdesk article tags. Article authored_at and updated_at timestamps are preserved.
Helpy
User / Agent
Freshdesk
Agent
1:1Helpy agents are not a standalone CSV import type — they are created manually in the admin panel or via admin provisioning. We extract every agent email referenced in ticket assignee and reply author fields, then provision corresponding Freshdesk agents via the Freshdesk agents API with the customer's specified group and role assignments. Inactive or departed agents receive tickets reassigned to the primary admin before migration.
Helpy
Attachment
Freshdesk
Attachment (CDN reference)
lossyHelpy's CSV import does not support inline attachments. We scan all Helpy ticket bodies and KB article bodies for attachment references, extract files to a managed CDN bucket, and deliver a post-migration reference table mapping each source attachment URL to its CDN URL. The customer pastes CDN URLs back into Freshdesk ticket notes or article bodies as a post-import step. File size and type restrictions match Freshdesk's attachment API limits (25 MB per file on Growth and above).
Helpy
Custom Ticket Fields
Freshdesk
Custom Ticket Fields
1:1Helpy custom ticket fields vary by installation since the CSV schema is not fixed. We audit the target Helpy instance's custom field configuration during discovery, then pre-create matching custom fields in Freshdesk via the ticket_fields API before migration. Field type mapping: Helpy text fields map to Freshdesk text, checkboxes to boolean, date fields to date. Fields without a Freshdesk equivalent are flagged and handled as post-migration custom field additions.
| Helpy | Freshdesk | Compatibility | |
|---|---|---|---|
| Customer | Contact1:1 | Fully supported | |
| Ticket | Ticket1:1 | Fully supported | |
| Ticket Reply | Conversation (Ticket Reply)1:1 | Fully supported | |
| Category | Category + Section1:many | Fully supported | |
| Knowledge Base Doc | Article1:1 | Fully supported | |
| User / Agent | Agent1:1 | Fully supported | |
| Attachment | Attachment (CDN reference)lossy | Fully supported | |
| Custom Ticket Fields | Custom Ticket Fields1:1 | Mapping required |
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.
Helpy gotchas
No REST API for bulk record creation
CSV import is admin-only and schema-sensitive
Knowledge Base Docs and Categories must be sequenced correctly
Ticket Replies imported as a separate type require chronological sequencing
Freshdesk gotchas
API access is blocked on the free plan
Per-minute rate limits are account-wide and endpoint-specific
Multi-channel source types do not map 1:1 to all destinations
Custom objects created in-product cannot be accessed by other apps
Contact import requires at least 10 existing tickets in the account
Pair-specific challenges
Migration approach
Discovery and Helpy CSV template audit
We audit the source Helpy instance's CSV import templates by downloading the official template pack from the Helpy Google Drive resources and comparing it against the target Helpy installation's actual CSV column headers. We inventory all active Customers, Tickets, Replies, KB Categories, and KB Articles, plus any custom fields present in the ticket CSV. We also confirm the destination Freshdesk plan (Sprout, Blossom, Growth, or Pro) to determine API access availability and feature parity. The discovery output is a written migration scope with record counts, object mapping table, and a recommendation to upgrade to Blossom or above if the destination is on Sprout.
Freshdesk schema pre-configuration
We pre-configure the Freshdesk destination before any data import begins. This includes creating custom Contact fields (for Helpy locale and timezone metadata), creating custom Ticket fields (for Helpy custom fields and the source Helpy ticket ID), defining KB Category and Section hierarchy in Freshdesk, and provisioning agent accounts via the Freshdesk agents API for every Helpy agent email identified in discovery. The Freshdesk API key is obtained from Profile Settings, and we verify API connectivity before proceeding.
CSV extraction from Helpy and data transformation
We export all records from Helpy via its CSV import interface for each object type: Customers first, then Categories, then KB Articles, then Tickets, then Replies. Each CSV is validated against Helpy's expected column headers before transformation. We convert Helpy field types to Freshdesk API-compatible payloads, apply deduping logic on email for Contacts, and sort Replies by created_at for chronological threading. Custom field values that do not map to Freshdesk typed fields are written to custom text fields for later cleanup.
Staged write to Freshdesk API with reconciliation
We write data to Freshdesk in dependency order: Categories and Sections first (KB hierarchy required for article assignment), then Contacts, then Tickets, then Replies, then Articles. Each phase writes to the Freshdesk REST API, emits a row-count reconciliation report, and waits for validation before the next phase begins. For the Replies phase, we batch requests to stay within Freshdesk API rate limits (variable by plan) and verify each parent ticket exists before posting. Any record rejected by the Freshdesk API is logged with the error response for correction and retry.
Attachment extraction and reference table delivery
We scan all Helpy ticket bodies and KB article bodies for attachment references, extract files to a managed CDN bucket, and validate download accessibility. We deliver a post-migration reference table (CSV) mapping each source Helpy attachment URL to its CDN URL, associated ticket or article ID, and file metadata. The customer or their admin pastes CDN URLs into Freshdesk ticket notes or article bodies as a post-migration step, since Helpy's CSV import does not carry binary attachment data.
Cutover, validation, and automation inventory handoff
We freeze Helpy writes during cutover, run a final delta migration of any records modified during the migration window, then deliver a full reconciliation report comparing source counts against Freshdesk destination counts for every object type. We deliver the automation inventory document (listing every Helpy trigger, routing rule, and SLA rule with Freshdesk Scenario Automation equivalent) to the customer's admin team. We do not rebuild Helpy automations as Freshdesk automations inside the migration scope; that work requires a separate engagement or an internal admin task.
Platform deep dives
Helpy
Source
Strengths
Weaknesses
Freshdesk
Destination
Strengths
Weaknesses
Complexity grading
Standard Helpdesk migration. 1 of 7 objects need a manual workaround.
Overall complexity
Standard migration
Derived from compatibility, mapping clarity, API constraints, and data volume across Helpy and Freshdesk.
Object compatibility
1 of 7 objects need a manual workaround.
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
Helpy: Not publicly documented as numeric quotas.
Data volume sensitivity
Helpy exposes a bulk API — large-volume migrations stream efficiently.
Estimator
Rule-based pricing — no per-record fees, no manual quotes. Migrations over 2M records are scoped individually.
Step 1
Pick a category, then your source and destination platforms.
Category
FAQ
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