CRM migration
Field-level mapping, validation, and rollback between Devi and Freshsales. We move data and schema; workflows are rebuilt natively in Freshsales.
Devi
Source
Freshsales
Destination
Compatibility
5 of 8
objects map 1:1 between Devi and Freshsales.
Complexity
CModerate
Timeline
3-5 weeks
Overview
Moving from Devi to Freshsales is a migration from an opaque, narrowly-focused social-lead tool to a full-stack sales CRM. Devi's research corpus contains no documented API, no confirmed data export mechanism, and no verifiable schema — we approach this migration with mandatory pre-engagement discovery to establish what records actually exist and in what format. Freshsales (Freshworks, NASDAQ: FRSH) operates over 60,000 customer accounts and provides a fully documented REST API with CSV import, Bulk API, and a published data model covering Contacts, Accounts, Deals, Leads, and Activity history. We do not migrate Devi's workflows, automations, or AI-generated content assets as code; we deliver a written inventory of these for the customer's admin to rebuild in Freshsales. The primary migration objects are person-level records (mapped to Freshsales Contact and Account), high-intent lead signals (mapped to Freshsales Lead or a custom lead-score field), and any historical timestamps that survived export.
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 Devi object lands in Freshsales, including any object-level transformations, lookup resolution, or schema-design dependencies.
Typical mapping — final map is confirmed during the sample migration step.
Devi
Person-level records (inferred)
Freshsales
Contact
1:1Devi's high-intent lead detection implies person-level records with name, social handle, and engagement signals. We treat these as Freshsales Contacts with a discovery-phase schema confirmation required. Any inferred social media identifiers map to a custom text field devi_social_handle__c. Email address, if present, maps to the standard Email field on Contact. If Devi's records include company affiliation, we split to Account with the AccountId resolved before Contact insert.
Devi
Company records (inferred)
Freshsales
Account
1:1Devi's social listening may capture company signals (employer, brand mentions). If company data is present in Devi's export, we map to Freshsales Account with Website, Industry, and Phone preserved. Account is created before Contact import so that the AccountId Lookup is satisfied at the moment of Contact insert. If no company data exists in Devi's export, we create a default Account placeholder to attach person-level contacts.
Devi
Lead signals (inferred)
Freshsales
Lead
1:1Devi's core value proposition is identifying high-intent leads on social media. We infer a lead-scoring or intent-signal field that maps to Freshsales Lead with a custom field devi_intent_score__c carrying the original signal value. Lead Status maps to a Freshsales Status field with values defined during scoping. If Devi's records are already qualified (Contact-stage), we map directly to Freshsales Contact instead of Lead.
Devi
AI-generated content assets (inferred)
Freshsales
Custom Object or Note attachment
lossyG2 reviewers mention AI-generated visual content as a Devi feature. If exported assets include image URLs, file references, or asset metadata, we store these as ContentDocument records linked via ContentDocumentLink to the parent Contact or Lead. If the asset count is high and the customer needs a structured content library, we pre-create a custom Asset__c object with Name, Type, URL, and OwnerId fields before migration.
Devi
User records
Freshsales
User
1:1Devi may include user seat records or assigned owner information on lead entries. We match by email against the Freshsales destination User table. Any Devi User without a matching Freshsales User goes to a reconciliation queue for the customer's admin to provision before record import resumes. Active/inactive status is preserved in a custom field devi_user_status__c.
Devi
Engagement timestamps
Freshsales
Task or Event
1:1Devi's lead detection runs on a schedule, producing timestamped events (lead identified, intent signal triggered). These migrate to Freshsales Task records with Subject, ActivityDate, and description preserved. The Task maps to the parent Contact or Lead via WhoId. We do not migrate social media message content as Freshsales EmailMessage records unless Devi's export includes full message bodies in a structured format.
Devi
Custom fields (unknown schema)
Freshsales
Custom fields on standard objects
lossyDevi's data model is unconfirmed. We allocate discovery time during Phase 1 to receive the customer's Devi export (CSV preferred), identify all columns, infer data types, and map each to a Freshsales standard or custom field. Custom fields in Freshsales are created as __c fields on the relevant object before any data import begins. We validate field types (text, number, date, picklist) against Freshsales API constraints before migration.
Devi
Tags or labels (inferred)
Freshsales
Multi-select picklist
lossySocial media lead tools commonly use tags to segment by platform (Twitter, LinkedIn), intent level, or content type. If Devi's export contains tag columns, we map to Freshsales multi-select picklist fields on Contact or Lead. Tag values are preserved as individual picklist entries, and the migration validates that total tag string length does not exceed Freshsales' 40,000-character field limit.
| Devi | Freshsales | Compatibility | |
|---|---|---|---|
| Person-level records (inferred) | Contact1:1 | Fully supported | |
| Company records (inferred) | Account1:1 | Fully supported | |
| Lead signals (inferred) | Lead1:1 | Fully supported | |
| AI-generated content assets (inferred) | Custom Object or Note attachmentlossy | Fully supported | |
| User records | User1:1 | Fully supported | |
| Engagement timestamps | Task or Event1:1 | Fully supported | |
| Custom fields (unknown schema) | Custom fields on standard objectslossy | Fully supported | |
| Tags or labels (inferred) | Multi-select picklistlossy | 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.
Devi gotchas
Platform identity is ambiguous in search results
No documented export or API access
Thin review corpus makes due diligence difficult
Freshsales gotchas
Freddy AI is Pro-tier only despite heavy marketing
Post-migration emails and sequences are disabled
Bot session credits are a one-time 500-session allocation
Phone credits charged per minute with no cap
File storage limits scale with plan tier
Pair-specific challenges
Migration approach
Pre-engagement export confirmation
We request written confirmation from the customer that Devi has a data export mechanism (CSV, JSON, API) and that they have access to export credentials. If no export exists, we document the manual extraction path and adjust the discovery timeline accordingly. We also confirm the exact product name and domain used by the customer's team to rule out platform identity ambiguity.
Discovery and schema inference
We receive a sample export or schema description from the customer and identify all columns, inferred data types, record counts, and object relationships. We cross-reference Devi's inferred model against Freshsales' documented data model and produce a written schema map with field-level type assignments. Any column that cannot be typed from the export goes to a clarification queue with the customer. This phase produces the migration specification that both parties sign off on before migration begins.
Freshsales destination setup
We create the destination Freshsales account structure: standard objects are enabled and validated, custom fields are created on Contact, Account, Lead, and any custom object with __c API names matching Devi's field names where possible. We configure Record Types and Sales Processes if multiple pipelines exist on the source. Territory assignment rules are set up per Freshsales best practices. Owner mapping is validated against the customer-provided Freshsales User list.
Test migration and reconciliation
We run a test migration using a subset of Devi's exported data into a Freshsales trial or sandbox environment. We reconcile record counts, spot-check 25-50 records field-by-field, and validate that custom field data appears correctly in Freshsales. Any mapping corrections are applied to the migration specification. The customer reviews the test output and signs off before production migration proceeds.
Production migration in dependency order
We run production migration in dependency order: Accounts (from Devi's company signals, or a default placeholder), Contacts (with AccountId resolved), Leads (with intent score in devi_intent_score__c), Tasks and Events (with WhoId pointing to Contact or Lead), and custom asset records last. Each phase emits a row-count reconciliation report. If Devi's export produces new records during the migration window, we run a delta sync before cutover.
Cutover, validation, and automation handoff
We freeze Devi writes during cutover, run a final delta migration, and enable Freshsales as the system of record. We deliver a written inventory of Devi's inferred workflows, automation rules, and content assets requiring rebuild in Freshsales (using Freshsales Workflows, Automation Rules, or Freddy AI configurations). We support a one-week hypercare window for reconciliation issues. We do not rebuild Devi's automations as Freshsales workflows inside the migration scope; that is a separate engagement.
Platform deep dives
Devi
Source
Strengths
Weaknesses
Freshsales
Destination
Strengths
Weaknesses
Complexity grading
Moderate CRM migration. 3 of 8 objects need a manual workaround.
Overall complexity
Moderate migration
Derived from compatibility, mapping clarity, API constraints, and data volume across Devi and Freshsales.
Object compatibility
3 of 8 objects need a manual workaround.
Field mapping clarity
Field mapping is derived from defaults — final spec confirmed during the sample migration.
Timeline complexity
8-object category — typical timelines run 2–7 days end-to-end.
API constraints
Devi: Not publicly documented.
Data volume sensitivity
Devi 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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