Helpdesk migration
Field-level mapping, validation, and rollback between Mava and Freshdesk. We move data and schema; workflows are rebuilt natively in Freshdesk.
Mava
Source
Freshdesk
Destination
Compatibility
6 of 9
objects map 1:1 between Mava and Freshdesk.
Complexity
BStandard
Timeline
1-3 weeks
Overview
Moving from Mava to Freshdesk is a migration from a community-native, AI-first support tool built for Discord and Telegram into a mature multi-channel helpdesk with full API access, custom objects, and enterprise SLA management. Mava's conversation records (tickets) map 1:1 to Freshdesk Tickets, but Mava's community platform identities (Discord IDs, Telegram IDs) require resolution to email or username before they can land as Freshdesk Contacts. We flag identity records that cannot be resolved and work with the customer to enrich them before migration. Agent and team structures map 1:1 to Freshdesk Agents and Groups. Mava's per-channel AI bot intent catalogs are extracted as JSON and documented for the customer's admin to rebuild in Freshdesk's automation framework. SLA policies migrate where Freshdesk plan supports them. Webhook configurations are extracted and documented for manual reconnection in the Freshdesk integrations panel.
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 Mava 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.
Mava
Conversations
Freshdesk
Ticket
1:1Mava's Conversations map directly to Freshdesk Tickets. The conversation message thread, timestamps, channel source (Discord, Telegram, or web), and participant metadata transfer as-is. Status values from Mava (open, pending, resolved, closed) map to Freshdesk ticket_status equivalents. We preserve the original channel source as a custom field if the customer needs to filter by Mava origin after migration.
Mava
Conversations
Freshdesk
Ticket Fields
lossyMava conversation metadata (custom fields set by bot rules, channel-specific attributes) migrates to Freshdesk custom ticket fields. We pre-create matching custom fields in Freshdesk before migration so that field values land in the correct places. If Mava uses custom fields not yet defined in Freshdesk, we create them during the schema phase.
Mava
AI Bots
Freshdesk
Scenario Builder / Freddy AI (documented for rebuild)
1:1Mava's AI bot intents and automated responses are stored as per-channel JSON payloads that do not have a direct Freshdesk equivalent. We extract the full intent catalog across all Discord, Telegram, and web channels, consolidate duplicate intents, and document the intent-to-response mapping in a structured JSON manifest. The customer's Freshdesk admin uses this manifest to rebuild equivalent rules in Freshdesk's Scenario Builder or Freddy AI Copilot. This is a documentation deliverable, not an automated migration.
Mava
Users/Members
Freshdesk
Contact
1:manyMava community members identified by Discord ID or Telegram ID map to Freshdesk Contacts. Where a Discord or Telegram user has a resolvable email, we link it to the Contact record directly. Where the identity cannot be resolved to an email, we create a Contact with the platform ID stored in Freshdesk's external_id field and flag the record for enrichment. Multiple Mava channel identities for the same individual are merged into a single Contact where the platform IDs are linked.
Mava
Agents
Freshdesk
Agent
1:1Mava agents (support team members with name, email, role, and assignment rules) map directly to Freshdesk Agents. We resolve by email match. Any Mava agent without a matching Freshdesk Agent account goes to a reconciliation queue for the customer's admin to provision before migration resumes. Group and team assignments on agents map to Freshdesk Groups.
Mava
Teams
Freshdesk
Group
1:1Mava team structures (name and member list) map directly to Freshdesk Groups. We preserve team-to-member assignments by resolving each member's email to the corresponding Freshdesk Agent. If Mava teams have routing rules tied to SLA policies, we document those during scoping and advise whether Freshdesk's Group-based routing supports the equivalent behavior.
Mava
Tags
Freshdesk
Tag
1:1Mava conversation tags transfer as-is to Freshdesk Tags. Tags are simple key-value strings on both platforms, so no transformation is required. If the customer uses tag-based reporting in Mava, we ensure tag names are preserved exactly so that Freshdesk reporting by tag reflects the original data.
Mava
Custom Webhooks
Freshdesk
Webhook (documented for rebuild)
1:1Mava webhook configurations (endpoint URLs, trigger conditions, and customer-defined payload structures) are extracted and documented in the migration manifest. Webhook payloads vary by customer and lack a standardized schema, so we cannot transform them automatically. We deliver a written webhook inventory listing each endpoint URL, trigger event, and payload sample so the customer's admin can recreate equivalent webhook integrations in Freshdesk's Outbound Webhooks app.
Mava
SLA Policies
Freshdesk
SLA Policies (Enterprise plan)
lossyMava SLA policies (first-response and resolution time targets tied to channels or teams) map to Freshdesk SLA Policies if the destination Freshdesk plan supports them. SLA policies are available on Estate and Forest tiers. If the customer is on a lower tier, we document the SLA configuration for rebuild once they upgrade or advise on Freshdesk's built-in business hours and time-based workflows as alternatives.
| Mava | Freshdesk | Compatibility | |
|---|---|---|---|
| Conversations | Ticket1:1 | Fully supported | |
| Conversations | Ticket Fieldslossy | Fully supported | |
| AI Bots | Scenario Builder / Freddy AI (documented for rebuild)1:1 | Mapping required | |
| Users/Members | Contact1:many | Mapping required | |
| Agents | Agent1:1 | Fully supported | |
| Teams | Group1:1 | Fully supported | |
| Tags | Tag1:1 | Fully supported | |
| Custom Webhooks | Webhook (documented for rebuild)1:1 | Mapping required | |
| SLA Policies | SLA Policies (Enterprise plan)lossy | 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.
Mava gotchas
Community identity linkage may be incomplete
Bot configurations are channel-specific
Webhook payloads lack standardized schema
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 data audit
We audit the Mava workspace across conversation volume, active channels (Discord, Telegram, web), agent count, team structures, tag taxonomy, SLA policy definitions, webhook configurations, and AI bot intent catalog. We pair this with a Freshdesk plan review to confirm API access (Blossom or above required) and whether the SLA Policy feature is available on the target tier. The discovery output is a written migration scope, a data quality assessment flagging unresolved community identities, and a Freshdesk plan recommendation.
Identity resolution and enrichment
We extract every Mava user record and attempt email resolution via any linked contact data in Mava. Records that cannot resolve to an email are flagged and grouped. We provide the customer with a report of unresolved Discord and Telegram identities and recommend an enrichment strategy before migration (such as linking community handles to verified email addresses in Mava if the platform supports it, or accepting external_id Contacts in Freshdesk with a follow-up enrichment process). Migration cannot proceed past identity resolution because Freshdesk requires an email for standard Contact records.
Freshdesk schema preparation
We configure Freshdesk before any data lands. This includes creating custom ticket fields matching Mava's metadata, provisioning Groups matching Mava's team structure, setting up Freshdesk Agents (with admin coordinating User provisioning for any Mava agents that do not yet have Freshdesk accounts), and configuring SLA Policies if the target plan supports them. Webhook endpoints are noted but recreated manually by the customer post-migration.
Bot intent catalog extraction and documentation
We extract Mava's AI bot configurations across all channels into a structured JSON manifest listing each intent, trigger condition, channel context, and automated response. This manifest is delivered as part of the migration package and serves as the reference document for the customer's Freshdesk admin to rebuild equivalent rules in Freshdesk's Scenario Builder or Freddy AI Copilot. We do not build Freshdesk automations inside the migration scope.
Ticket and Contact migration in dependency order
We migrate data in dependency order: Contacts (from resolved Mava user identities) first, then Freshdesk Agents and Groups, then Tickets (Conversations from Mava with thread history and tags preserved), then SLA associations. Tags transfer as-is. We run reconciliation row counts after each phase. Community identities that could not resolve to email land as Contacts with external_id set to the source platform identifier and a flag for enrichment.
Webhook manifest delivery and cutover
We deliver the webhook inventory documenting each Mava endpoint URL, trigger event, and payload sample. The customer's admin reconnects webhooks in Freshdesk using Freshdesk's Outbound Webhooks integration. We freeze Mava writes during cutover, run a delta migration of any records modified during the window, then confirm Freshdesk as the system of record. We support a three-day hypercare window for reconciliation issues. Workflow rebuild, automation redesign, and knowledge base setup are outside migration scope.
Platform deep dives
Mava
Source
Strengths
Weaknesses
Freshdesk
Destination
Strengths
Weaknesses
Complexity grading
Standard Helpdesk migration. All 7 core objects map 1:1 between Mava and Freshdesk.
Overall complexity
Standard migration
Derived from compatibility, mapping clarity, API constraints, and data volume across Mava and Freshdesk.
Object compatibility
All 7 core objects map 1:1 between Mava and Freshdesk.
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
Mava: Not publicly documented..
Data volume sensitivity
Mava 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
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