Helpdesk migration

Migrate from Gmelius to Intercom

Field-level mapping, validation, and rollback between Gmelius and Intercom. We move data and schema; workflows are rebuilt natively in Intercom.

Gmelius logo

Gmelius

Source

Intercom

Destination

Intercom logo

Compatibility

82%

9 of 11

objects map 1:1 between Gmelius and Intercom.

Complexity

CModerate

Timeline

2-4 weeks

Rollback included Accuracy guarantee Field-level validation

Overview

What this migration involves

Moving from Gmelius to Intercom is a platform-category shift: Gmelius is a Gmail extension that layers shared inbox functionality onto existing email threads, while Intercom is a dedicated multi-channel helpdesk with its own conversation model, team inbox, and AI layer. Gmelius stores no public API, so we extract all data via the Gmail API and Google Contacts API, reconstruct Gmelius Shared Inboxes as Intercom Inboxes with team assignments, map email threads to Intercom Conversations with full message threading, translate Shared Labels to Intercom Tags, and convert Shared Templates to Intercom Macros. Automation Rules and Kanban board configurations have no export path — we document the rule logic and board layout during discovery and hand off a written rebuild specification for the customer's admin. SLA configurations and analytics are tier-gated in Gmelius and migrate as metadata rather than live dashboards. We do not migrate workflows, sequences, or browser-extension configurations as code.

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

Gmelius logo

Gmelius

What's pushing teams away

  • Slow email loading times (6+ mentions on G2) damage productivity for high-volume support teams who need sub-second response, pushing them toward dedicated helpdesk platforms.
  • Gmail-only constraint eliminates teams using Outlook or mixed email environments, forcing an either/or decision that enterprise IT departments often cannot make.
  • Steep learning curve for Automation Rules and Kanban boards means new team members require guided onboarding before they can operate independently.
  • No public API documentation on lower tiers and limited mobile app functionality frustrates technical teams needing programmatic access or mobile support workflows.
  • Extension conflicts with other Gmail add-ons (documented in Gmelius own help center) cause UI glitches that require disabling competing extensions.

Choosing

Intercom logo

Intercom

What's pulling them in

  • Instant chat and message threading on websites and apps gives support teams a single inbox without context-switching, according to reviewers on Capterra and G2 who highlight fast response times as a primary benefit.
  • Fin AI handles repetitive inbound queries automatically, reducing agent workload measurably — G2 reviewers report fewer escalations and faster first-response times once Fin is configured.
  • Automation workflows (Outbound, Operator, and custom bots) allow teams to qualify leads and route tickets without manual intervention, appealing to growth-stage SaaS companies managing high ticket volumes.
  • Help center articles and self-service deflection are natively integrated, so knowledge base content and chat conversations live in the same workspace, simplifying reporting.
  • Multi-channel support (live chat, email, SMS, WhatsApp, Phone) consolidates customer touchpoints into one inbox, reducing the operational overhead of managing separate tools.

Object mapping

How Gmelius objects map to Intercom

Each row shows how a Gmelius object lands in Intercom, including any object-level transformations, lookup resolution, or schema-design dependencies.

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

Gmelius

Shared Inbox

maps to

Intercom

Inbox + Team

1:1
Fully supported

Gmelius Shared Inboxes map 1:1 to Intercom Inboxes. During discovery we capture each Shared Inbox's member list, assignment rules, and SLA configuration. We create corresponding Intercom Teams (Settings > Inbox > Teams) and assign the migrated teammates to the matching team. The Gmelius inbox name becomes the Intercom Inbox name. Note: Intercom Inboxes are workspace-scoped, not user-scoped, so Gmelius team members who previously accessed a shared inbox individually will access the Intercom Inbox as team members.

Gmelius

Email Conversation (thread)

maps to

Intercom

Conversation

1:1
Fully supported

Full email threads export from Gmelius via the Gmail API. Each thread becomes one Intercom Conversation with all messages preserved in chronological order as Conversation Parts. The original email headers (Message-ID, In-Reply-To, References) map to Intercom's internal thread tracking. Attachments are downloaded from Gmail and re-uploaded as Intercom Conversation attachments. Assignee, status, and tags from Gmelius migrate as conversation metadata. Email addresses on the From/To/CC fields map to Intercom Contacts (created if they do not exist).

Gmelius

Shared Label

maps to

Intercom

Tag

1:1
Fully supported

Gmelius Shared Labels are Gmail-native and export via the Gmail API label list. We recreate them as Intercom Tags (Settings > Tags) and apply them to the corresponding Conversations. Label hierarchy (parent label / child label) is flattened to a dot-notation tag namespace (e.g., billing.high-priority becomes a tag named 'billing.high-priority') because Intercom Tags are flat. The customer chooses whether to keep the full taxonomy or consolidate during scoping.

Gmelius

Shared Email Template

maps to

Intercom

Macro

1:1
Fully supported

Gmelius Shared Email Templates store text with variable placeholders. We export the full template library including subject line, body, and merge field syntax. At Intercom we create Macros (Settings > Macros) using the same content. Variable placeholders in Gmelius syntax (e.g., {{contact.first_name}}) are translated to Intercom's {{token}} syntax. HTML-formatted templates are preserved; plain-text templates are migrated as-is.

Gmelius

Automation Rule

maps to

Intercom

Rule (documentation only)

lossy
Fully supported

Gmelius Automation Rules define conditional routing, auto-assignment, and follow-up sequences stored as extension-local configuration. There is no export mechanism. We capture every active rule during the discovery walkthrough via screen recording and structured intake, document the trigger condition, action sequence, and exception path, then hand off a written rule specification to the customer's admin for rebuild in Intercom Rules. Multi-step rules with AI dispatching (Gmelius Pro tier) require the most reconstruction effort. We do not migrate Automation Rules as executable code.

Gmelius

Kanban Board

maps to

Intercom

Inbox View (custom filter)

lossy
Fully supported

Gmelius Kanban boards visualise email pipelines by status columns. Board columns map to Intercom Inbox Views with custom conversation filters per column (e.g., filter by assignee + status = 'Open'). Card-to-conversation associations are preserved during migration by applying the corresponding conversation status on import. Custom board layouts with non-standard column logic are documented as filter specifications for the customer's admin to configure in Intercom. Kanban card metadata (due dates, priority) migrates as conversation-level custom attributes.

Gmelius

Contact (via Google Contacts)

maps to

Intercom

Contact

1:1
Fully supported

Gmelius does not maintain its own contact database — contacts live in Gmail and Google Contacts. We export contacts via the Google Contacts API, preserving name, email, phone, company association, and any Gmelius-specific contact tags applied to threads. Contacts are created as Intercom Contacts (Contacts > Import > CSV) with external_id set to the Google Contact ID for deduplication. Duplicate contacts (same email, different Google Contact ID) are merged at import.

Gmelius

SLA Configuration

maps to

Intercom

SLA (Pro+ tier) + Custom Attribute

1:1
Fully supported

SLA & Email Analytics is a Gmelius Growth and Pro tier feature. SLA rules (first response time, next response time, resolution time) are exported as custom conversation attributes in Intercom (Conversation Attributes or custom attributes on the Contact). Intercom's native SLA feature is available on the Pro and Enterprise tiers and requires manual configuration post-migration with the migrated SLA values. Dashboard-level analytics from Gmelius are not importable and are documented for rebuild in Intercom Reports.

Gmelius

User / Team Member

maps to

Intercom

Teammate

1:1
Fully supported

Gmelius users correspond to Google Workspace accounts. We extract the user list (name, email, role within Gmelius) and map them to Intercom Teammates. Inactive Gmelius users are created as inactive Intercom teammates. Permissions mapping: Gmelius Admin becomes Intercom Admin; Gmelius Member becomes Intercom Agent. The customer's Intercom admin provisions the teammates before migration and we reconcile any gaps in a user provisioning queue.

Gmelius

Email Note / @mention

maps to

Intercom

Conversation Part (internal note)

1:1
Fully supported

Email notes and @mentions applied to Gmelius threads are exported as Intercom internal notes (Conversation Parts with part_type = 'note'). Note authorship and timestamps are preserved. The note author maps to the corresponding Intercom Teammate. Attachments on notes migrate as Intercom Conversation attachments linked to the note.

Gmelius

Shared Draft

maps to

Intercom

Macro

1:1
Fully supported

Gmelius Shared Drafts are collaborative email drafts stored as draft objects in the Gmelius extension layer. Since Intercom does not have a shared-draft concept, we export Shared Drafts as Intercom Macros using the draft content. The customer chooses which drafts to preserve as reusable macros versus discarding. Variable placeholders are translated to Intercom token syntax.

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.

Gmelius logo

Gmelius gotchas

High

Gmail-only lock-in is irreversible for mixed email environments

High

No formal public API on lower tiers limits programmatic data export

Medium

Automation Rules are extension-local state with no export mechanism

Medium

All team members must share the same plan tier

Low

Extension conflicts with other Gmail add-ons cause UI instability

Intercom logo

Intercom gotchas

High

S3 JSON export omits conversation transcripts

High

Workspace isolation prevents workflow migration

Medium

Fin AI resolution fees compound with automation success

Medium

Two-year conversation history limit on historical export

Low

Private app rate limits share workspace quota

Pair-specific challenges

  • Gmelius exposes no public REST API — extraction via Google Workspace

    Gmelius on the Meli and Growth tiers has no documented public REST API endpoint. We extract all data via the Gmail API (threads, messages, attachments, labels) and Google Contacts API (contacts). This extraction approach requires the customer to authorise FlitStack AI with Google Workspace OAuth scopes, and it is constrained by Gmail API quotas (1,000,000,000 quota units/day, with per-method limits). Large conversation histories require batch extraction with pagination. Customers who need programmatic access to Gmelius for integrations will encounter this limitation permanently; Intercom's API solves that problem post-migration.

  • Automation Rules have no export mechanism and require manual rebuild

    Gmelius Automation Rules are stored as extension-local configuration in the browser, not as data in any cloud API. There is no documented endpoint to list, export, or retrieve rule definitions. During discovery we screen-record the full rules UI and capture the trigger, conditions, actions, and exceptions in a structured intake form. We hand off a written automation specification document listing every active rule and its recommended Intercom Rules equivalent. The customer's admin rebuilds the rules in Intercom post-migration. We do not migrate automation configurations as executable code.

  • Kanban board card-to-status mapping requires manual column design

    Gmelius Kanban boards store card metadata and column definitions in the extension layer with no export. Board column names (e.g., 'Waiting on Customer', 'In Progress', 'Escalated') must be captured during discovery intake and manually mapped to Intercom conversation statuses or custom conversation attributes. If the team uses non-standard column names or multi-dimensional board views, the mapping requires a design decision from the customer's admin. We flag this during scoping and document the board structure for manual reconstruction.

  • Intercom's conversation model differs structurally from Gmail threads

    Gmelius operates on Gmail's threading model where each email chain is a thread. Intercom creates a Conversation per customer contact (by email address or user ID) and adds every subsequent message as a Conversation Part on that same Conversation. This means that if the same customer contacts the team from multiple email threads, they will merge into a single Intercom Conversation. We document this merge behavior during scoping. Teams that rely on keeping separate threads as separate records (e.g., separate cases per email subject) must decide whether to suppress the merge or accept the unified conversation view.

  • Intercom API campaigns can throttle migration writes

    Intercom's API enforces rate limits (default 283 API calls/minute on standard plan; higher on Advanced and Enterprise). Automated email campaigns running during migration consume API quota and can slow down write throughput. We disable active Intercom Outbound campaigns before running the migration import and re-enable them after cutover. This is a pre-migration configuration step the customer performs or approves during the cutover window.

Migration approach

Six steps for a successful Gmelius to Intercom data migration

  1. Discovery and Google Workspace authorisation

    We conduct a discovery session with the customer's admin to enumerate all Shared Inboxes, Kanban boards, Shared Templates, Automation Rules, and SLA configurations. We capture the Gmelius plan tier, user list, and conversation volume estimate. We then set up Google Workspace OAuth 2.0 scopes for Gmail API and Google Contacts API access, scoped to the specific Gmelius user accounts in use. We export a full list of Gmelius users and map them to Intercom teammates for provisioning.

  2. Data extraction via Google Workspace API

    We extract all email threads (messages, headers, attachments, labels) via the Gmail API in paginated batches. Attachments are downloaded to local storage and re-uploaded to Intercom during import. Google Contacts are extracted via the People API. Gmelius-specific metadata (assignee, tags, SLA status) is extracted from the extension configuration captured during discovery. All extraction runs read-only against the source environment.

  3. Intercom workspace provisioning and schema design

    We create the Intercom workspace structure before importing data. This includes provisioning Teams (mapped from Gmelius Shared Inboxes), creating Inbox Views (mapped from Kanban board columns), creating Tags (mapped from Shared Labels), and creating Macros (mapped from Shared Email Templates). SLA configurations are documented as custom conversation attributes for manual configuration on Intercom Pro or Enterprise. Custom Objects are not required for this migration unless the customer has Gmelius Pro features that reference external CRM data.

  4. Demo migration and reconciliation

    We run a sample migration of 50-100 conversations into a staging Intercom environment. The customer's admin reviews the conversation threading, tag application, assignee mapping, and attachment fidelity. We reconcile row counts against the source extraction log and correct any mapping issues before the production migration. This step also surfaces whether Intercom's conversation-merge behavior for multi-thread customers requires a suppression strategy.

  5. Production migration in dependency order

    We run the production migration in record-dependency order: Teammates first (validated by the customer's Intercom admin), Contacts (from Google Contacts), then Conversations (with assignee, tags, and SLA metadata applied). Attachments upload in parallel with message imports. Automation Rule specifications and Kanban board column mapping are delivered as written documentation for the customer's admin to rebuild in Intercom Rules and Inbox Views.

  6. Cutover, delta sync, and rebuild handoff

    We freeze writes on the Gmelius source, run a final delta migration capturing any new conversations during the migration window, then enable Intercom as the system of record. Active Intercom Outbound campaigns are re-enabled post-cutover. We deliver the Automation Rule inventory, Kanban board mapping document, and SLA rebuild specification to the customer's admin. We support a three-day hypercare window for reconciliation issues raised by the team. Workflow rebuilds and Rule recreation are outside migration scope.

Platform deep dives

Context on both ends of the pair

Gmelius logo

Gmelius

Source

Strengths

  • Gmail-native shared inbox means no new application to launch — team members stay in their existing email workflow.
  • AI assistant Meli handles reply drafting, email sorting, and meeting scheduling directly inside Gmail without additional tools.
  • SOC 2 Type II certified with Swiss privacy-by-design, meeting enterprise security procurement requirements.
  • Per-user pricing model with no per-conversation or per-channel fees makes cost predictable as teams grow.
  • Collaboration features including shared labels, Kanban boards, and real-time email notes reduce inbox clutter for support and sales teams.

Weaknesses

  • Gmail-only platform — no Outlook support eliminates teams in mixed or Microsoft-first email environments entirely.
  • Extension-delivered model means performance depends on browser extension loading times, with documented slow email loading on G2.
  • No permanent free plan and no free tier creates a billing commitment before teams can validate fit for their workflow.
  • Limited mobile app functionality means mobile support teams operate with reduced feature parity versus desktop.
  • Automation Rules and complex workflow configuration requires a learning investment that slows initial team adoption.
Intercom logo

Intercom

Destination

Strengths

  • Integrated AI agent (Fin) for automated resolution with per-resolution billing that rewards high automation rates.
  • Multi-channel inbox consolidating live chat, email, SMS, WhatsApp, and Phone into a single threaded view.
  • Native help center with articles, collections, and self-service deflection capabilities.
  • Workflow automation for routing, qualification, and proactive outbound messaging across channels.
  • Strong API ecosystem with 10,000 req/min rate limits for private apps enabling high-throughput migration pipelines.

Weaknesses

  • Pricing model compounds with seat count, AI resolution fees, channel costs, and multiple add-ons, making total cost hard to predict.
  • Workspace-level isolation prevents moving workflows or content between environments, requiring manual rebuilds.
  • S3 JSON export deliberately excludes conversation transcripts, necessitating REST API calls for full message history.
  • Outages are reported as frequent enough to be a concern for always-on support operations.
  • Setup complexity means teams often require internal guidance or professional services to configure bots and automation correctly.

Complexity grading

How hard is this migration?

Moderate Helpdesk migration. 3 of 7 objects need a mapping; the rest are 1:1.

C

Overall complexity

Moderate migration

Derived from compatibility, mapping clarity, API constraints, and data volume across Gmelius and Intercom.

  • Object compatibility

    C

    3 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

    Gmelius: Not publicly documented.

  • Data volume sensitivity

    B

    Gmelius doesn't expose a bulk API — REST + parallelization used for high-volume runs.

Estimator

Estimate your Gmelius to Intercom 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 Gmelius to Intercom data migrations

Answers to the questions buyers ask most during Gmelius to Intercom migration scoping. Not seeing yours? Book a call.

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Most migrations land between two and four weeks for teams with under 10,000 email conversations, up to 5 Shared Inboxes, and a straightforward Kanban board layout. Migrations with large engagement histories (over 50,000 email threads), multiple Kanban boards, extensive Shared Template libraries, or Gmelius Pro features (AI Dispatching, CRM integrations) move to five to eight weeks. The additional time is driven by Google Workspace API pagination for large volumes, manual capture of Automation Rule logic, and the board-design review with the customer's admin.

Adjacent paths

Related migrations to explore

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