Helpdesk migration
Field-level mapping, validation, and rollback between Logicalware and Freshdesk. We move data and schema; workflows are rebuilt natively in Freshdesk.
Logicalware
Source
Freshdesk
Destination
Compatibility
7 of 8
objects map 1:1 between Logicalware and Freshdesk.
Complexity
BStandard
Timeline
2-4 weeks
Overview
Logicalware dissolved in April 2023 and was absorbed into Puzzel Scotland Ltd. There is no active vendor, no API endpoint, and no hosting SLA. Every Logicalware migration therefore begins with whatever export artifacts the customer still possesses, and the scope of that export determines what data is recoverable. We validate export file integrity during scoping, flag any corrupted or incomplete dumps, and document gaps explicitly rather than silently dropping records. Into Freshdesk, we map Tickets, Contacts, Companies, Agents, Conversations, Attachments, and Tags from the export files. We create the destination Freshdesk schema — agent roles, groups, ticket fields, and SLA policies — to match the available source data. Freshdesk automations, SLA policies, and knowledge base articles do not migrate as code; we deliver a written map of these for your admin to rebuild post-migration. Because no source API exists, parent-record resolution and orphaned reference handling require explicit customer input rather than live lookup calls.
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 Logicalware 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.
Logicalware
Ticket
Freshdesk
Ticket
1:1Logicalware Tickets export with ID, subject, body, status, priority, and timestamps in CSV or XML format. We map these to Freshdesk Ticket fields: subject, description_text, status, priority, and created_at. Logicalware ticket ID is preserved as source_ticket_id__c in a custom field for audit traceability. Channel metadata from Logicalware (email, chat, SMS) maps to the Freshdesk inbound_email or FreshdeskConversation channel property.
Logicalware
Customer (Contact Record)
Freshdesk
Contact
1:1Logicalware Customer records include name, email address, phone number, and any custom fields present in the export. We map to Freshdesk Contact (requester) by email as the dedupe key. If a Contact with the same email already exists in Freshdesk, we flag it for the admin to decide between merge and skip rather than creating duplicates. Any @logicalware.com email addresses in the export are flagged as likely inactive and held for manual owner reassignment.
Logicalware
Company
Freshdesk
Organization
1:1Logicalware Company records map to Freshdesk Organization by company name as the dedupe key. If a company name appears in multiple ticket records with slight spelling variations, we normalise to a single Organization and link all associated Contacts. Organizations with no linked Contacts in the export are flagged as potentially orphaned and noted in the scope document.
Logicalware
Conversation (Message Thread)
Freshdesk
Conversation
1:1Logicalware Conversations are flattened into individual message events per ticket. Each message migrates as a Freshdesk Conversation record with body text, timestamp, and sender type (agent or requester) preserved. Thread chronology ordering is maintained by created_at timestamps. If the Logicalware export does not include full message body text (only metadata), we flag the gap and document what is recoverable versus what is permanently missing.
Logicalware
Agent
Freshdesk
Agent
1:1Logicalware Agent records include name, email, and role. We map to Freshdesk Agents by email match. Any @logicalware.com email addresses are flagged as likely deactivated and mapped to a designated replacement owner during scoping rather than landing in unmonitored mailboxes. Role mapping (admin, agent, supervisor) is preserved in Freshdesk agent permissions settings during schema setup.
Logicalware
Channel
Freshdesk
Channel Property
lossyLogicalware channel types (email, live chat, SMS, WhatsApp, social media) are stored as properties on ticket and conversation records in the export. We preserve channel type as a Freshdesk ticket property and as a tag on the conversation record. Multi-channel tickets that span email and chat in a single Logicalware thread are split into separate Freshdesk conversation entries with channel tags so agents see the channel context on each message.
Logicalware
Attachment
Freshdesk
Attachment
1:1Logicalware attachment references in export files may be URLs pointing to the Logicalware platform or inline base64-encoded content. We migrate inline attachment content as Freshdesk attachments on the corresponding ticket or conversation. URL references pointing to the Logicalware platform are flagged as inaccessible after the 2023 dissolution; we document each inaccessible URL with the original filename so the customer can attempt recovery from their own backup systems.
Logicalware
Tag
Freshdesk
Tag
1:1Logicalware tags applied to tickets for categorisation migrate to Freshdesk Tags directly, preserving the original tag vocabulary. We do not consolidate synonymous tags unless explicitly requested. Tags that appear in the export file but not in the Freshdesk admin UI are created during the migration phase. Tag-based ticket filtering in Logicalware maps to Freshdesk's tag-based reporting filters.
| Logicalware | Freshdesk | Compatibility | |
|---|---|---|---|
| Ticket | Ticket1:1 | Fully supported | |
| Customer (Contact Record) | Contact1:1 | Fully supported | |
| Company | Organization1:1 | Fully supported | |
| Conversation (Message Thread) | Conversation1:1 | Fully supported | |
| Agent | Agent1:1 | Fully supported | |
| Channel | Channel Propertylossy | Fully supported | |
| Attachment | Attachment1:1 | Fully supported | |
| Tag | Tag1:1 | Fully supported |
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.
Logicalware gotchas
Company dissolution voids all SLA commitments
No public API or export endpoints documented
Agent email addresses may become stale post-dissolution
Multi-channel thread flattening may alter conversation context
Custom ticket fields export inconsistently
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
Export file audit and scope document
We review every export artifact the customer still possesses from Logicalware: CSV files, XML dumps, email server archives, or any CRM linkage records that reference Logicalware tickets. We validate file structure, column presence, row counts, and the presence of message body text versus metadata only. We generate an export quality report listing recoverable record counts by object, any gaps, and what is permanently missing. This report forms the migration scope and is the basis for the project quote.
Freshdesk schema design and agent mapping
We design the destination Freshdesk schema to match the available source data. This includes creating any required custom ticket fields, configuring agent roles and groups, setting up ticket type defaults (incident, request, problem), and mapping Logicalware agent records to Freshdesk agent accounts. For @logicalware.com email addresses, we map to the customer-designated replacement owners. We validate the schema with a dry-run import in a test Freshdesk account before production migration.
Data transformation and custom field mapping
We transform Logicalware export data into Freshdesk-compatible format, applying value mapping for status fields, priority levels, and channel types. Custom fields present in the export are mapped to Freshdesk custom fields; fields absent from the export are documented as unmapped rather than created as empty. Multi-channel threads are split by channel type with tags preserved so agents see channel context per message. Tags migrate directly without consolidation.
Production migration in dependency order
We run production migration in record-dependency order: Organizations first (as parent records for Contacts), then Contacts, then Agents, then Tickets, then Conversations and Attachments, then Tags. Each phase emits a row-count reconciliation report. Any records modified during the migration window are captured in a final delta migration pass. We flag orphaned references (contacts without a valid organisation, tickets without a requester) for the customer's admin to resolve post-migration.
Validation and automation rebuild handoff
We validate migrated data against the source export row counts and spot-check representative tickets for text integrity and conversation chronology. We deliver a written migration report including record counts migrated, gaps documented, and any unmigrated records with reasons. We provide an automation rebuild guide listing the Freshdesk automation fields and SLA policy settings to configure. We do not rebuild automations or knowledge base articles inside the migration scope; those are documented for the customer's admin.
Platform deep dives
Logicalware
Source
Strengths
Weaknesses
Freshdesk
Destination
Strengths
Weaknesses
Complexity grading
Standard Helpdesk migration. 2 of 7 objects need a mapping; the rest are 1:1.
Overall complexity
Standard migration
Derived from compatibility, mapping clarity, API constraints, and data volume across Logicalware and Freshdesk.
Object compatibility
2 of 7 objects need a mapping; the rest are 1:1.
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
Logicalware: Not publicly documented.
Data volume sensitivity
Logicalware doesn't expose a bulk API — REST + parallelization used for high-volume runs.
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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