Migrate your Synerise data
AI-first behavioral data platform for enterprise marketing teams that want real-time personalization and automation built on proprietary infrastructure rather than third-party components.
In its favor
Why people choose Synerise
The signal that keeps Synerise on the shortlist. Sourced from G2, Capterra, and customer scoping calls.
Customers choose Synerise for its real-time behavioral AI engine — sub-50ms latency from event capture to profile enrichment to AI decision, not batch-processed.
The platform's in-house AI foundation models (BaseModel.ai for behavioral prediction, Cleora.ai for embedding generation) avoid third-party AI vendor lock-in, appealing to enterprises with strict data sovereignty requirements.
Synerise's multi-channel marketing automation — email, SMS, push, WhatsApp, and webhooks — runs on a single workflow canvas, reducing tool sprawl for mid-market marketing teams.
The schema builder (Brickworks) lets teams define arbitrary custom data structures, enabling vertical-specific use cases without waiting for platform roadmaps.
Customers cite exceptional customer segmentation capabilities as a top differentiator, with AI-driven personalization that adapts to individual behavioral patterns rather than static rules.
Building dashboards and reporting views requires starting from scratch every time — the flexibility that enables creative reporting also creates significant time investment for common visualization needs.
Custom attribute names cannot be renamed or deleted after creation, which creates technical debt for organizations that evolve their data model over time.
Pricing is entirely custom and opaque — no public per-seat or per-feature tiers, requiring lengthy sales cycles and making cost predictability difficult for growing teams.
Reasons to switch
Why people leave Synerise
The recurring reasons buyers give for replacing Synerise. Presented as facts, not knocks.
Platform scorecard
Strengths, weaknesses, and where Synerise fits
Grades across six dimensions, plus a SWOT-style view of where the platform shines and where it falls short.
SWOT — strengths, weaknesses, and use-case fit
Strengths
Weaknesses
Where it works
Where it struggles
Pricing tiers
Synerise pricing overview
Synerise does not publish pricing tiers on its website. All plans are custom enterprise agreements negotiated through sales. Pricing is likely based on data volume (profile count, event volume), API call volume, and module access rather than per-seat or per-feature linear tiers.
Custom Enterprise
Tier 1 of 1
Not publicly documented — contact sales
What's included
Need help selecting your CRM?
Book a free 30 minute consultationPricing is informational. FlitStack AI does not bill on Synerise's schedule — see our quote-based pricing →
What gets migrated
Synerise object support
Object-by-object support for Synerise migrations. Per-pair details surface during scoping.
Profiles
Fully supportedThe primary customer identity object in Synerise. Accessed via the Profile Management API (89 endpoints). Exportable to CSV/JSON/JSONL with a 10M record cap per job. Default attributes are email, firstName, lastName, city, birthDate, phone. Custom attributes are fully supported but names become immutable after creation.
Events
Fully supportedBehavioral signals tracked per profile — page.visit, product.view, added-to-cart, transaction, and 40+ other event types. Batch event ingestion is supported via POST /v4/events. Events are assigned to the client's clientId or UUID. Historical event export is available through the Analytics Suite API.
Companies/Accounts
Mapping requiredCompanies are linked to Profiles via the profile.assigned-to-company event. There is no standalone Company object — company data lives as profile attributes or schema records in Brickworks. We map these by tracking the assignment event and merging company fields into a structured schema.
Transactions
Fully supportedTransaction records are created via POST /v4/transactions or POST /v4/transactions/batch. They contain line items, totals, and timestamps. Exportable via Data Management API. Transaction events (transaction, cancelled-transaction) are automatically tied to the profile that made the purchase.
Catalogs
Fully supportedProduct/item feeds managed in the Data Modeling Hub. Exports available as CSV, JSON, or JSON lines. Item feeds are used by AI recommendation models (personalized, visual similarity, top items). Catalog records can include arbitrary custom fields per catalog schema.
Segments
Mapping requiredSegmentation returns true/false values per profile. Export includes segment membership flags. Custom segments built in the Segmentation builder may have complex rule logic that requires expression evaluation during import to reproduce membership on the destination platform.
Custom Attributes
Mapping requiredAny profile attribute beyond the defaults can be custom-named. The critical constraint is that custom attribute names cannot be changed after creation. We audit all custom attribute names during scoping and flag immutability risks before migration begins.
Automation Workflows
Mapping requiredWorkflows are defined in Automation Hub with trigger nodes, conditions (Profile Filter), and actions (Send Email, Send SMS, webhook calls). Workflows are fire-and-forget — completion of an action node does not gate workflow progression. Active workflow state cannot be migrated; we export workflow definitions and re-activation is a separate step post-cutover.
AI Recommendations
Mapping requiredRecommendation configurations (personalized, visual similarity, last seen, top items, item comparison) are trained on catalog feeds and profile event history. We export recommendation model configurations and re-import them to the destination's recommendation engine where equivalents exist. Visual similarity models trained on Synerise's proprietary image embeddings require re-training on the destination platform.
Schemas (Brickworks)
Fully supportedBrickworks schemas are arbitrary record structures that store any data type. Exportable from the Data Modeling Hub. Schema definitions (field names, types, constraints) must be recreated on the destination. Singleton schemas and 'one to many filtered' field types have specific handling requirements.
Campaigns
Mapping requiredCampaign definitions — email, SMS, push, WhatsApp — are accessible via the Campaigns API (100 endpoints). We export campaign configurations including templates, audience rules, and scheduling. Active campaign state (sends in progress, queue depth) cannot be migrated atomically.
Tags
Fully supportedProfile tags are exported as true/false boolean attributes in the profile export. Tag names are free-form strings. We preserve full tag sets per profile and import them as tag fields or custom properties on the destination platform.
Aggregates and Expressions
Mapping requiredSynerise supports computed aggregates and expression results attached to profiles. These are exported as scalar values. Since aggregates are computed from underlying events, destination recomputation may produce different values if the event history is not fully replicated.
| Object | Support | Notes |
|---|---|---|
| Profiles | Fully supported | The primary customer identity object in Synerise. Accessed via the Profile Management API (89 endpoints). Exportable to CSV/JSON/JSONL with a 10M record cap per job. Default attributes are email, firstName, lastName, city, birthDate, phone. Custom attributes are fully supported but names become immutable after creation. |
| Events | Fully supported | Behavioral signals tracked per profile — page.visit, product.view, added-to-cart, transaction, and 40+ other event types. Batch event ingestion is supported via POST /v4/events. Events are assigned to the client's clientId or UUID. Historical event export is available through the Analytics Suite API. |
| Companies/Accounts | Mapping required | Companies are linked to Profiles via the profile.assigned-to-company event. There is no standalone Company object — company data lives as profile attributes or schema records in Brickworks. We map these by tracking the assignment event and merging company fields into a structured schema. |
| Transactions | Fully supported | Transaction records are created via POST /v4/transactions or POST /v4/transactions/batch. They contain line items, totals, and timestamps. Exportable via Data Management API. Transaction events (transaction, cancelled-transaction) are automatically tied to the profile that made the purchase. |
| Catalogs | Fully supported | Product/item feeds managed in the Data Modeling Hub. Exports available as CSV, JSON, or JSON lines. Item feeds are used by AI recommendation models (personalized, visual similarity, top items). Catalog records can include arbitrary custom fields per catalog schema. |
| Segments | Mapping required | Segmentation returns true/false values per profile. Export includes segment membership flags. Custom segments built in the Segmentation builder may have complex rule logic that requires expression evaluation during import to reproduce membership on the destination platform. |
| Custom Attributes | Mapping required | Any profile attribute beyond the defaults can be custom-named. The critical constraint is that custom attribute names cannot be changed after creation. We audit all custom attribute names during scoping and flag immutability risks before migration begins. |
| Automation Workflows | Mapping required | Workflows are defined in Automation Hub with trigger nodes, conditions (Profile Filter), and actions (Send Email, Send SMS, webhook calls). Workflows are fire-and-forget — completion of an action node does not gate workflow progression. Active workflow state cannot be migrated; we export workflow definitions and re-activation is a separate step post-cutover. |
| AI Recommendations | Mapping required | Recommendation configurations (personalized, visual similarity, last seen, top items, item comparison) are trained on catalog feeds and profile event history. We export recommendation model configurations and re-import them to the destination's recommendation engine where equivalents exist. Visual similarity models trained on Synerise's proprietary image embeddings require re-training on the destination platform. |
| Schemas (Brickworks) | Fully supported | Brickworks schemas are arbitrary record structures that store any data type. Exportable from the Data Modeling Hub. Schema definitions (field names, types, constraints) must be recreated on the destination. Singleton schemas and 'one to many filtered' field types have specific handling requirements. |
| Campaigns | Mapping required | Campaign definitions — email, SMS, push, WhatsApp — are accessible via the Campaigns API (100 endpoints). We export campaign configurations including templates, audience rules, and scheduling. Active campaign state (sends in progress, queue depth) cannot be migrated atomically. |
| Tags | Fully supported | Profile tags are exported as true/false boolean attributes in the profile export. Tag names are free-form strings. We preserve full tag sets per profile and import them as tag fields or custom properties on the destination platform. |
| Aggregates and Expressions | Mapping required | Synerise supports computed aggregates and expression results attached to profiles. These are exported as scalar values. Since aggregates are computed from underlying events, destination recomputation may produce different values if the event history is not fully replicated. |
Gotchas
What to watch for in Synerise migrations
Issues we've hit on past Synerise migrations, tagged by severity. FlitStack AI handles every one — surfacing them up front because buyer engineering teams want to know.
Immutable custom attribute names cause migration mapping failures
Active automation workflow state cannot be preserved at cutover
5GB file and 10M record export caps require chunked migration planning
Visual similarity AI recommendations require full model retraining
Reserved attribute names cannot be used in custom field creation
| Severity | Issue |
|---|---|
| High | Immutable custom attribute names cause migration mapping failures |
| High | Active automation workflow state cannot be preserved at cutover |
| Medium | 5GB file and 10M record export caps require chunked migration planning |
| Medium | Visual similarity AI recommendations require full model retraining |
| Low | Reserved attribute names cannot be used in custom field creation |
Leaving Synerise?
Where Synerise customers move next
12 destinations Synerise can migrate to.
How a Synerise migration works
Four steps, Synerise-specific
Connect
API key-based authentication with JWT tokens issued per workspace into Synerise. Scopes limited to read-only on the data we move.
Map
We translate Synerise-specific structures (custom fields, objects, value lists) to the destination's model.
Sample
Test with a 50–200 record subset to validate Synerise quirks before production.
Migrate
Full migration with Synerise rate-limit handling. Rollback available throughout.
FAQ
Synerise migration FAQ
Answers to the questions buyers ask most during Synerise migration scoping. Not seeing yours? Book a call.
Can't find your answer?
Walk through your Synerise migration with a real engineer — 30 minutes, free, written quote within 24 hours.
Book a free 30 minute consultationReady when you are
Migrate Synerise.
Without the rebuild.
Free scoping call with a migration engineer. Tell us about your Synerise setup and destination — written quote back within a business day.