Zammad to Kayako migration requires API-to-API scripting with no native path. Route articles to cases/replies/notes, preserve timestamps via bulk import, and validate aggressively.
There is no native migration path, built-in connector, or vendor-provided import wizard from Zammad to Kayako—while Zammad offers a migrator for importing from Kayako, no reverse path exists. The fundamental data model difference centers on Zammad's article-based ticket messaging versus Kayako's conversation-centric case model, with internal notes routed to entirely separate API endpoints in Kayako. A reliable migration requires building or commissioning an API-to-API pipeline that extracts via Zammad's REST API and loads through Kayako's Cases API, with custom transform logic to handle field mapping, internal note routing, attachment transfer, and timestamp preservation.
Read this first
Pair-specific gotchas that catch teams out. Each one has cost somebody a weekend.
API Versioning Note
This guide is based on Zammad 6.x REST API and Kayako API v1 as of mid-2026. Zammad's API can change between major self-hosted versions — verify endpoint behavior against your installed version before scripting. Zammad Cloud instances may have different API rate limits or disabled endpoints compared to self-hosted installations — confirm access to all extraction endpoints before beginning. Several Kayako API reference pages still show a last-updated date of January 2017, so validate behavior in a sandbox before production. (developer.kayako.com)
Internal Notes Routing
Zammad's internal notes are articles on the ticket with internal: true. Kayako separates notes from case messages entirely — they live at a different API endpoint (/api/v1/cases/{id}/notes). Your migration script must detect internal articles and route them to Kayako's notes API, not the replies endpoint. Getting this wrong means internal agent notes become visible to customers. This is the single most common data exposure mistake in helpdesk migrations.
If your support team uses Zammad as a pseudo-CRM, split the project in two
Migrate support history into Kayako. Keep sales and marketing objects in the CRM, and carry only reference IDs or read-only context that agents need. Kayako documents cases, forms, types, users, and organizations — it is not a pipeline system.
Zammad Search Limit
Zammad's search endpoint (/api/v1/tickets/search) has a hard limit of 10,000 results regardless of pagination. If you have more than 10K tickets, do not use the search endpoint for extraction. Paginate through /api/v1/tickets using page and per_page parameters. If the paginated list endpoint also truncates at high page numbers, iterate by ticket ID ranges (e.g., GET /api/v1/tickets?page=1&per_page=100 and track the highest ID returned).
Timestamp Override
If you do not explicitly pass the historical created_at timestamp when creating a Kayako Case, Kayako will stamp it with the current server time. The bulk cases endpoint explicitly documents support for historical created_at and updated_at on both cases and nested posts. For single-case creates via POST /api/v1/cases.json, verify in your Kayako sandbox that created_at overrides are accepted — some Kayako plans or API versions may ignore this field on single creates. (developer.kayako.com)
Kayako's PUT-only update model
Kayako does not support PATCH. Any update via PUT must include all required fields, or omitted fields may silently revert to defaults. For multi-select custom fields, Kayako's documentation explicitly warns that omitted values are removed on update — never update field values without sending the full intended set. This is especially dangerous during post-migration corrections. (developer.kayako.com)
The runbook
Work top to bottom. Tick steps as you go — your progress is saved in this browser.
01 Discovery Establish why you are moving, what "done" means, and who signs off.
Objective A written scope with agreed success criteria, a named owner per workstream, and a budget approved by finance.
Keep these open
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Pull the real numbers out of Zammad
Export counts for tickets (open and closed separately), contacts, organisations, attachments, macros, triggers, automations, views and SLA policies. Note the oldest ticket date — history depth drives the whole timeline. Estimating from memory is the single most common cause of a blown migration window.
Data Profiler Get real record counts instead of estimating from memory -
Decide what history actually moves
Agree a cut-off with the support lead: all history, last 24 months, or open tickets plus a read-only archive. Every extra year of closed tickets adds API time and cost without adding much agent value. Get this in writing — it is the decision people relitigate mid-cutover.
A "move everything" default is what turns a two-week migration into a two-month one.
COI & ROI Calculator Build the 36-month business case you will need for sign-off -
Confirm Kayako can hold your support model
Walk your current workflow through Kayako: multi-brand, business hours, SLA targets, CSAT, side conversations, public vs internal notes, and any channel you depend on (voice, chat, WhatsApp, social). List anything with no native equivalent — those are project risks, not configuration details.
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Build the business case
Model licence delta, migration effort, agent retraining, and the cost of staying put (Cost of Inaction). Executives approve a number, not a plan, and you will be asked for it again at the go/no-go.
Helpdesk Migration Planner Turn ticket volume into a dated Zammad → Kayako timeline -
Name owners and set the go/no-go date
One named owner each for data, configuration, integrations, and agent enablement, plus a decision-maker who can call a rollback. Put the go/no-go meeting in calendars now, 48 hours before the freeze.
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Identify unused data
Old ticket states, orphaned organizations, test accounts, suspended or merged users. Define a cutoff date if appropriate (e.g., "Only migrate tickets updated in the last 3 years"). Don't migrate garbage.
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Define scope
All history or a time window? Closed tickets? Knowledge base articles? CRM-style data mirrored into Zammad?
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Record count comparison
Ensure Total Zammad Tickets - Excluded Tickets = Total Kayako Cases. Compare users, organizations, and attachment counts. Use Kayako's archived=1 parameter when counting cases to include closed cases older than 30 days.
Helpdesk Evaluator Sanity-check that Kayako is the right target before you commit
Zammad → Kayako specifics
- Moving off self-hosted infrastructure
- Zammad is open-source and often self-hosted, requiring server maintenance, PostgreSQL/Elasticsearch upgrades, and security patching. Teams running Zammad on-premise who lack dedicated DevOps capacity migrate to Kayako Cloud to eliminate infrastructure overhead. (zammad.com)
- Conversation-centric data model
- Kayako organizes support around customer journeys and conversation timelines rather than ticket lists. Teams that need a unified customer view across email, chat, and social in a single thread find Kayako's case model structurally better suited.
- Native omnichannel integration
- Kayako's live chat, messenger widget, and social media integrations are tightly coupled with its case model — messages from all channels appear as posts within a single case. Zammad supports chat but treats it as a separate channel with a more basic implementation.
- Visual workflow automation
- Kayako's journey builders and SLA management provide drag-and-drop automation configuration suited for multi-tiered support teams without requiring triggers written in Zammad's condition/action syntax.
- Reduced admin surface area
- Zammad's flexibility — custom objects, extensive API surface, nested group hierarchies — becomes overhead for teams under 20 agents. Kayako's narrower configuration model (custom fields on cases, users, and organizations only) reduces the administrative burden.
Don't move on until
- Record counts confirmed for tickets, contacts, organisations and macros
- Success criteria signed off by the support lead
- Freeze window provisionally booked with the business
02 Data Audit Find out what is actually in the data before you try to move it.
Objective A profiled, cleaned export with every quality defect either fixed at source or explicitly accepted.
Keep these open
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Take a full Zammad export and profile it
Export to CSV or JSON and profile every file: row counts, null rates per column, distinct values, and type consistency. Compare row counts against the API totals from Discovery — a gap here means your export is silently truncated, usually by pagination.
Data Profiler Profile the Zammad export for nulls, outliers and type drift -
Validate file structure before anyone writes a transform
Check delimiters, quoting, encoding (expect UTF-8, watch for BOMs and Latin-1), duplicate headers, and embedded newlines in ticket bodies. Ticket descriptions with raw newlines and commas break naive CSV parsers and silently shift columns.
A single unescaped quote in one ticket body can shift every subsequent column without any error.
CSV Validator Catch broken headers and ragged rows in the raw export -
Inventory PII and set retention
Scan for emails, phone numbers, payment card fragments, national IDs and anything else regulated in ticket bodies and custom fields — support tickets are where customers paste things they should not. Decide what gets migrated, masked, or dropped, and record the legal basis.
Ticket bodies and attachments routinely contain card and ID data that never appears in a structured field.
PII & Compliance Scanner Find regulated fields before they land in a new system -
Quantify duplicates, orphans and dead references
Count duplicate contacts (same email, different casing), tickets whose requester no longer exists, organisations with no members, and attachments whose parent ticket is gone. Fix these in Zammad where you can — migrating them just moves the mess.
Data Cleaner Strip empty rows, stray whitespace and dead columns -
Clean and normalise the export
Trim whitespace, drop empty rows and columns, normalise casing on emails and tags, and standardise every timestamp to UTC ISO 8601. Timezone drift is invisible at load time and shows up weeks later as SLA reports nobody can reconcile.
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Produce a masked copy for sandbox work
Generate a realistic but fake version of the export for testing and for any vendor who needs sample data. Loading real customer PII into a sandbox is a breach in most jurisdictions, and sandboxes are rarely covered by your DPA.
PII Masker Generate a safe copy for sandbox and vendor testing -
Audit your Zammad data
Count tickets, users, organizations, articles, attachments, and custom fields. Use GET /api/v1/tickets?only_total_count=true for ticket counts. For Zammad Cloud, confirm that all extraction endpoints are accessible — some Cloud instances may restrict admin-level API access compared to self-hosted.
Zammad → Kayako specifics
- Scalability
- Does not scale beyond a few thousand records.
- Inline image extraction
- Zammad users frequently paste images directly into the editor. These are stored as base64 strings in <img src="data:image/png;base64,..."> tags or as referenced attachments. Your script must parse the HTML, extract base64 content, upload it to Kayako as an attachment via the Files API, and rewrite the <img> tag to reference the uploaded file URL.
Don't move on until
- Export parses cleanly with no ragged rows or encoding errors
- PII inventory complete and retention decisions recorded
- Duplicate and orphan records quantified and triaged
03 Field Mapping Turn two schemas into one signed-off mapping spec.
Objective A reviewed field-level mapping covering every object, with an explicit decision for every field that has no target.
Keep these open
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Generate the first-pass Zammad → Kayako field map
Start from an automated match on both schemas, then review every row by hand. Automated matching gets the obvious 70% right and is confidently wrong on the rest — especially anything named "type", "status" or "custom_field_1".
Schema Mapper Opens pre-loaded with the Zammad → Kayako field pair -
Map status, priority and channel values, not just field names
Enumerate every value in each picklist on both sides and map them explicitly. Value-level mismatches are the defect class that survives all the way to production because the field itself mapped fine — a ticket that should be "Pending" arriving as "Open" reopens SLA clocks.
Statuses with no target equivalent (on-hold, pending-customer) need a policy decision, not a best guess.
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Decide how custom fields land
Create the target custom fields first, matching type exactly (a dropdown mapped to free text can never be mapped back). Where Kayako has no equivalent, decide between a new custom field, a tag, or a note appended to the ticket body — and record which.
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Resolve identity and threading
Decide how source IDs are preserved — most platforms will not let you set the primary key, so keep the original ID in a custom field. Without it, reconciliation becomes fuzzy matching and every future support question about an old ticket is unanswerable.
Losing the original ticket ID makes reconciliation and rollback effectively impossible.
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Plan attachments, inline images and threading order
Confirm size limits, allowed MIME types, and whether inline images survive as attachments or need rehosting. Decide the comment ordering and author attribution rules: comments loaded out of order, or all attributed to the API user, destroy the conversation history agents rely on.
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Freeze and sign off the mapping spec
Version the spec, walk the support lead through it row by row, and get explicit sign-off. Any change after this point goes through change control — mid-flight mapping edits are how partial loads happen.
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Map custom fields
Export Zammad's object attributes via GET /api/v1/object_manager_attributes and match each to a Kayako custom field. Watch for type mismatches: Zammad supports tree selects and external data source fields that have no direct Kayako equivalent. (admin-docs.zammad.org)
Zammad → Kayako specifics
- Small business (<5K tickets, no custom fields)
- Third-party tool or CSV if history is expendable.
- State mapping
- Zammad states → Kayako statuses. Query GET /api/v1/cases/statuses from your Kayako instance to get actual status IDs — do not hardcode. Zammad's "Pending Reminder" state has no direct equivalent in Kayako's default statuses — create a custom status before migration.
- Priority mapping
- Zammad priorities (1–4) → Kayako priorities (query via API). Verify label alignment.
- Article → message/note routing
- Articles with internal: true go to Kayako's notes endpoint. Public articles become replies. Check the type field as well — article types like note and phone may also need routing decisions.
- User deduplication
- Match users by email address. Create in Kayako if not found. Handle email-less users by generating deterministic placeholder emails (e.g., zammad-user-{id}@placeholder.local).
Don't move on until
- Every source field is mapped, deliberately dropped, or parked in a custom field
- Status, priority and channel value maps agreed with the support lead
- Mapping spec version-controlled and signed off
04 Test Migration Prove the pipeline on a small, representative slice.
Objective A pilot load into a Kayako sandbox that reconciles cleanly and has been reviewed by real agents.
Keep these open
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Stand up a Kayako sandbox that matches production config
Create the custom fields, groups, brands, business hours and SLA policies first. A pilot into a default sandbox tests nothing, because the failures you care about are all configuration mismatches.
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Pick a deliberately nasty pilot sample
Take 500-1000 records chosen for difficulty, not convenience: the longest ticket threads, tickets with the most attachments, non-Latin character sets, merged and split tickets, deleted requesters, and every status value. A clean random sample proves only that easy records are easy.
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Run the load with masked data and instrument everything
Log every API request and response with its source record ID. When 40 records fail out of 10,000 you need to know exactly which ones and why, without re-running the whole batch.
PII Masker Never load real customer PII into a sandbox -
Measure real throughput against the rate limit
Record achieved records-per-hour under Kayako's actual rate limits, including retries and backoff. Extrapolate to the full volume: if the maths says the full load exceeds your freeze window, you fix that now, not on cutover night.
Published rate limits are ceilings, not throughput. Assume real-world rates are meaningfully lower once retries and backoff are counted.
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Reconcile the pilot and triage every failure
Diff source against target on record counts and field-level values. Every discrepancy gets a root cause and a fix — "probably fine" at pilot scale becomes thousands of broken records at full scale.
Migration Validation Tool Diff the pilot batch against source before scaling up -
Put real agents in front of the pilot data
Have two or three agents work sample tickets end to end in the sandbox. They find the things reconciliation cannot see: unreadable threading, missing context, macros that no longer make sense. Fix the mapping, then re-run.
Zammad → Kayako specifics
- Field-level spot checks
- Sample 50 tickets across different states, priorities, and ages. Verify subject, status, assignee, requester, tags, and custom field values match. Include at least 5 tickets with custom field values and 5 with multi-select fields.
- Attachment integrity
- Download 10 attachments from Kayako and compare file hashes (SHA-256) against Zammad originals. Open them to verify they're not corrupted or 0-byte files. Verify the attachment count per case matches the source.
- Relationship integrity
- Verify user→organization links and case→assignee links survived the migration. Sample 20 users and confirm their organization association matches the source.
- Thread ordering
- Confirm articles appear in chronological order within each case. Check at least 10 cases with >5 articles each.
- Inline image rendering
- Open 10 cases that contained pasted images in Zammad and verify they render correctly in Kayako.
Don't move on until
- Pilot batch reconciles to 100% on record counts
- Agents have reviewed sample tickets and confirmed they are workable
- Measured throughput extrapolates to a viable full-load window
05 Cutover Execute the switch inside a controlled, reversible window.
Objective All in-scope data live in Kayako, agents working in the new system, and a rollback path that stayed available throughout.
Keep these open
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Pre-load history before the freeze
Load closed tickets and contacts days or weeks ahead while Zammad stays live. Only open tickets and the final delta need to move inside the freeze — this is the single biggest lever on window length.
Helpdesk Migration Planner Size the freeze window from Kayako's real API limits -
Publish the runbook with times, owners and abort criteria
A timed sequence: freeze start, final export, delta load, channel switch, smoke test, go/no-go, agent switch. Name who does each step and the explicit condition that triggers a rollback. Decide the abort criteria before the night, when nobody wants to be the one to call it.
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Freeze Zammad and take the final delta
Stop new ticket creation, let agents finish in-flight replies, then export everything changed since the pre-load. Announce the freeze to the whole business, not just support — someone always tries to raise a ticket during it.
Tickets created during an unenforced freeze land in the old system and are the most common source of permanently lost data.
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Load the delta and open tickets
Run the delta load, then reconcile counts before touching any channel. Do not repoint email until the delta has verified — an inbound ticket arriving mid-load is far harder to untangle than a few extra minutes of freeze.
Migration Validation Tool Confirm the final delta landed before you reopen -
Repoint channels and verify with live traffic
Switch email forwarding and MX or connector settings, update chat widgets and web forms, and re-authorise integrations. Then send real test tickets through every channel and confirm each lands, routes and triggers the right automation.
Email forwarding changes can take up to a full DNS TTL to propagate — check the TTL days in advance and lower it if needed.
Cron Expression Builder Schedule the delta syncs that run through the freeze -
Run the go/no-go and switch the agents
Walk the exit criteria with the decision-maker, call it explicitly, then move agents over with a named person on hand for the first few hours. Keep Zammad read-only rather than cancelled — cancelling the old contract on day one removes your only fallback.
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Plan your rollback
Keep Zammad running in read-only mode until Kayako is confirmed. Prepare a rollback script that bulk-deletes all cases created by your migration API user — Kayako's DELETE /api/v1/cases/{id} endpoint handles individual case deletion, but there is no documented bulk delete endpoint, so your script must iterate through created case IDs. Note that Kayako automations triggered on imported cases (e.g., auto-replies, SLA timers) may have already fired and cannot be cleanly reversed.
Zammad → Kayako specifics
- Rollback plan
- Keep Zammad running in read-only mode for at least 2 weeks post-migration. Maintain a list of all Kayako case IDs created during migration for potential rollback via DELETE /api/v1/cases/{id}.
Don't move on until
- Full historical load complete and counts matched
- Inbound channels repointed and verified with live test tickets
- Rollback decision point passed explicitly, not by default
06 Validation Prove the migration is complete, then close it out.
Objective Documented evidence that data, workflow and reporting all survived, and a signed acceptance.
Keep these open
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Run the full reconciliation
Compare source and target on every object: total counts, counts by status, counts by group, attachment counts, and field-level spot checks on a random sample. Produce one report you can hand to an auditor.
Migration Validation Tool Reconcile Zammad and Kayako record-for-record -
Verify field completeness, not just record counts
Re-profile the loaded data and compare null rates per field against the source profile. Matching record counts with a field that silently arrived empty is the failure mode counts alone will never catch.
Data Profiler Prove field completeness held up through the load -
Rebuild reporting and compare against baselines
Recreate your core dashboards — volume, first response time, resolution time, CSAT — and compare to pre-migration figures for the same period. Explain every variance; a changed SLA calculation is a real finding, not a rounding error.
SLA and first-response metrics are usually recalculated from the loaded timestamps, so they will differ if any timestamp mapping was approximate.
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Test the workflow layer end to end
Fire every trigger, automation, SLA escalation, macro and notification with a live ticket. Workflow does not migrate — it gets rebuilt — so it is untested until someone has actually watched it run.
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Confirm compliance and produce the audit trail
Re-scan the loaded data for regulated fields, confirm retention and deletion policies are configured in Kayako, and file the evidence with your PII decisions from the audit phase.
PII & Compliance Scanner Produce the compliance evidence your auditor will ask for -
Sign off, then decommission on a schedule
Get written acceptance against the Discovery success criteria. Keep Zammad read-only for an agreed period (30-90 days is typical), take a final archive export, and only then cancel. Diarise the decommission date so it does not quietly renew.
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Rebuild automations
Zammad triggers, schedulers, macros, and SLAs cannot be migrated programmatically. Recreate them manually in Kayako's automation builder. Document each Zammad automation and its Kayako equivalent.
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Monitor for data gaps
Run daily record count comparisons for the first week. Check for missing attachments, broken user links, or orphaned cases.
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Update knowledge base
If you migrated knowledge base content, verify that article formatting, images, and internal links survived the transfer. Run a link checker across all migrated KB articles.
Zammad → Kayako specifics
- Internal note verification
- Confirm notes appear in Kayako's notes panel, not as public messages. Test by viewing a migrated case as a customer-role user — internal notes should not be visible.
- Recreate canned responses
- Zammad Text Modules become Kayako Macros. Export Text Modules via GET /api/v1/text_modules and recreate in Kayako.
- Reconfigure integrations
- Any Zammad webhooks, Zapier connections, or custom API integrations must be rewired to Kayako endpoints. Monitor API error logs for 48 hours post-launch to catch any integrations still pushing data to Zammad.
- Agent training
- Kayako's conversation-centric UI differs significantly from Zammad's ticket-list model. Budget 1–2 days for team onboarding, focusing on: case search and filtering, internal note workflow, macro usage, and SLA visibility.
Don't move on until
- Full reconciliation report attached to the project record
- Reporting baselines match pre-migration figures within agreed tolerance
- Formal acceptance signed and archive retention scheduled
Field mapping reference
The field-by-field mapping for each object. Use this as the starting point for your mapping spec.
Zammad Kayako
| Zammad field | Kayako field | Notes |
|---|---|---|
| ticket.number | legacy_id | Store Zammad ticket number as Kayako's legacy_id for traceability |
| title | subject | Direct map |
| state_id | status_id | Map: new→New, open→Open, pending reminder/pending close→Pending, closed→Closed. Status IDs are instance-specific — query GET /api/v1/cases/statuses to get your Kayako instance's actual IDs. Create custom statuses in Kayako first if needed. |
| priority_id | priority_id | Query GET /api/v1/cases/priorities to get Kayako's priority IDs. Verify label alignment between platforms. |
| group_id | assigned_team_id | Create teams first, build lookup map |
| owner_id | assigned_agent_id | Match by email; only if agent exists in Kayako |
| customer_id | requester_id | Match or create by email |
| organization_id | organization_id | Load orgs first, build lookup map |
| tags | tags | Direct map; comma-separated on Kayako side |
| created_at | created_at | Must be explicitly passed. Bulk import endpoint documents historical timestamp support. Without explicit passing, Kayako stamps with current server time. |
| updated_at | updated_at | Must be explicitly passed |
| article.body | posts [].contents or reply contents | Sanitize HTML encoding; extract inline base64 images |
| article.internal | Route to Notes API | true → POST to /api/v1/cases/{id}/notes, not replies |
| article.attachments | attachment_file_ids or multipart upload | Upload files first via Files API for bulk import |
| Custom ticket/user/org fields | field_values [...] | Pre-create fields and map types carefully. Verify option values match exactly for select/dropdown fields. |
Data Endpoint
| Zammad field | Kayako field | Notes |
|---|---|---|
| Tickets | GET /api/v1/tickets?page=X&per_page=Y&expand=true | Paginate with page and per_page. Max per_page is 500. |
| Articles | GET /api/v1/ticket_articles/by_ticket/{ticket_id} | Returns all articles for a ticket |
| Attachments | GET /api/v1/ticket_attachment/{ticket_id}/{article_id}/{attachment_id} | Returns binary content |
| Users | GET /api/v1/users?page=X&per_page=Y&expand=true | Includes role, organization, custom fields |
| Organizations | GET /api/v1/organizations?page=X&per_page=Y | |
| Groups | GET /api/v1/groups | Maps to Kayako Teams |
| Tags | GET /api/v1/tags?object=Ticket&o_id={ticket_id} | Per-ticket tags |
| Custom attributes | GET /api/v1/object_manager_attributes | Schema definitions for custom fields |
Load in Kayako
| Zammad field | Kayako field | Notes |
|---|---|---|
| Organizations | POST /api/v1/organizations | Create before users. Response: {"data": {"id": ...}} |
| Users | POST /api/v1/users | Create customer/agent users. Response includes id in data object. |
| Cases | POST /api/v1/cases.json | Creates a case with initial message |
| Bulk cases | POST /api/v1/bulk/cases.json | Batch creation — up to 200 cases per request. Supports legacy_id and historical timestamps. |
| Replies | POST /api/v1/cases/{id}/replies | Add subsequent public messages |
| Notes | POST /api/v1/cases/{id}/notes | Internal notes (separate from messages) |
| File uploads | POST /api/v1/files | Upload first, then reference attachment_file_ids in case creation |
| Case deletion | DELETE /api/v1/cases/{id} | For rollback — no bulk delete endpoint; must iterate |
Risk matrix
Per-object risk for this pair. Plan extra validation around anything marked high.
| Object | Risk | Notes |
|---|---|---|
| Tickets/Cases | medium | One-to-one mapping is structurally straightforward, but preserving original timestamps and status values requires explicit field mapping and use of Kayako's `created_at` override. |
| Articles/Messages | high | Zammad's article model must be split between Kayako's posts/replies endpoint and its separate notes endpoint based on the internal flag, making misrouting a significant data exposure risk. |
| Internal Notes | high | Failure to detect Zammad's `internal: true` articles and route them to Kayako's dedicated notes API is the single most common data exposure mistake in helpdesk migrations. |
| Contacts/Users | low | Customer and agent users can be matched by email address across both platforms, though role mappings (agent vs. admin vs. collaborator) require manual verification. |
| Organizations | low | Both platforms support organization objects linked to users, and these must be loaded before users and cases to preserve relational integrity. |
| Custom Fields | high | Zammad supports custom object attributes on groups and uses exotic field types that have no direct Kayako equivalent, requiring type conversion, flattening, or data loss. |
| Attachments | medium | Attachments must be individually extracted from Zammad articles and re-uploaded to Kayako, with volume directly impacting migration duration and API rate limit consumption. |
| Tags | low | Both platforms support per-ticket/per-case tags with a direct mapping, making this a straightforward transfer with minimal transformation. |
| Groups/Teams | medium | Zammad's nested group hierarchies must be flattened into Kayako's flat team structure, potentially losing organizational granularity and requiring routing rule adjustments. |
| Knowledge Base | medium | Zammad's multilingual knowledge base with categories and answers must be restructured into Kayako's Help Center sections and articles, treated as a separate migration scope. |
The hard parts
What makes this specific migration difficult, beyond the mechanics.
Internal Notes Data Exposure
Zammad stores internal notes as ticket articles with an `internal: true` flag, but Kayako separates notes onto a distinct API endpoint, so misrouting them to the replies endpoint exposes private agent communications to customers.
Nested Group Flattening
Zammad supports nested group hierarchies for ticket routing, while Kayako uses a flat team structure, requiring all nested groups to be flattened and remapped before loading.
Custom Field Type Mismatches
Zammad allows custom object attributes on tickets, users, organizations, and groups, but Kayako only supports custom fields on cases, users, and organizations, meaning group-level and exotic-type fields must be flattened or dropped.
API Rate Limit Management
Both Zammad and Kayako impose API rate limits that require implementing pagination, exponential backoff, batch checkpointing, and dead-letter queues to avoid failed or incomplete data transfers at scale.
Attachment and Inline Image Transfer
Attachments must be individually downloaded from Zammad's article API and re-uploaded to Kayako's case posts, with inline images requiring HTML reference rewriting to maintain message fidelity.
Automation and Workflow Rebuild
Zammad triggers, schedulers, macros, and SLAs cannot be migrated programmatically and must be manually rebuilt in Kayako's automation and journey builder interfaces.
What breaks
Known failure modes. Have a recovery plan for each before you cut over.
Duplicate users
Zammad allows users without email addresses in some configurations (e.g., Twitter integrations, phone-only contacts). Kayako enforces strict email uniqueness. Generate deterministic placeholder emails (e.g., zammad-user-{id}@placeholder.local) for these profiles. For users with emails, deduplicate on email (case-insensitive), not display name. (admin-docs.zammad.org)
Internal notes becoming public
If your script posts internal articles to Kayako's replies endpoint instead of the notes endpoint, those notes become visible to customers. This is the most common data exposure mistake in helpdesk migrations. Mitigate by checking both article.internal == true and article.type == "note" — belt and suspenders.
Inline images
Zammad users frequently paste images directly into the editor. These are stored as base64 strings in the HTML body (<img src="data:image/png;base64,...">) or as referenced attachments. Your script must: (a) parse the HTML with a library like BeautifulSoup, (b) extract base64 content from data: URIs, (c) upload each image to Kayako via the Files API, (d) rewrite the <img> tag's src to reference the uploaded file URL.
Zammad article types vary
Article types include email, note, phone, web, chat, twitter status, twitter dm, facebook feed post, and others depending on installed channels and add-ons. Do not assume every article is a customer-visible email — check the type and internal flag on every article. (docs.zammad.org)
Kayako archived cases
Closed Kayako cases older than 30 days are omitted from the default GET /api/v1/cases response unless you add archived=1 as a query parameter. This distorts post-cutover audits done weeks later — your validation script must include this parameter. (help.kayako.com)
Attachment size limits
Kayako plan-dependent file size limits may reject large attachments (common limits: 20MB–50MB per file depending on plan). Log any that exceed the limit for manual handling rather than letting the entire case creation fail.
Reassignment audit trails
If a Zammad ticket was reassigned multiple times, the historical audit log entries are stored separately from articles. Focus on migrating the messages and current assignment, not the metadata audit trail — Kayako does not have an equivalent audit log import endpoint.
Enum field updates
Kayako warns that omitted multi-select values are removed on PUT updates. Never update field values without sending the full intended set. (developer.kayako.com)
Missing file uploads
Failed attachment uploads create valid cases with broken history links. Implement retry logic (at least 3 retries with exponential backoff) for every file upload, and verify attachment counts per case after migration against expected counts from Zammad. (developer.kayako.com)
HTML rendering differences
Zammad's rich text editor and Kayako's editor handle whitespace, line breaks, and CSS differently. Common issues: <br> vs <p> tag handling, CSS classes stripped by Kayako's sanitizer, table layouts collapsing. Visual QA on 20–30 tickets before full migration is essential.
Tools used in this playbook
All free, all run entirely in your browser — nothing is uploaded.
FAQ
Is there a native migration tool from Zammad to Kayako?
No. Zammad has a built-in migrator for importing FROM Kayako into Zammad, but there is no reverse path. Zammad-to-Kayako requires API-based extraction and loading via custom scripts or a managed migration service.
Can I migrate Zammad tickets to Kayako using CSV?
Only for small, flat datasets. Zammad's reporting download is limited to 6,000 entries and does not export individual articles, internal notes, or attachments. Kayako has no native bulk CSV import for cases. Full thread history and timestamps require API-based migration.
How do I migrate Zammad internal notes to Kayako?
Zammad stores internal notes as articles with 'internal: true'. In Kayako, notes are a separate resource — you must POST them to the /api/v1/cases/{id}/notes endpoint, not the messages/replies endpoint. Getting this wrong exposes internal notes to customers.
How long does a Zammad to Kayako migration take?
For a DIY approach: 3–5 days for under 5K tickets with no custom fields, 1–3 weeks for 5K–50K tickets with custom fields and attachments. A managed migration service typically completes in 3–5 business days regardless of complexity.
Does Kayako preserve historical timestamps during import?
The bulk cases endpoint (POST /api/v1/bulk/cases.json) explicitly supports historical created_at and updated_at on both cases and posts. For single-case creates, verify that your Kayako plan accepts created_at overrides — if not, all imported cases will be stamped with the current date.