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Digital Transformation In IndustryTop 10 Best Platform Migration Services of 2026
Top 10 platform migration services ranked for teams planning moves, with criteria and tradeoffs, and a Deloitte provider profile for context.
How we ranked these tools
Vendors set the topic, but our editors set the inclusion criteria and the evaluation framework before research starts.
Agents extract product evidence with provenance, then collect written reviews and transcribe video reviews and podcasts.
Framework: Features 40% · Ease 30% · Value 30%
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Deloitte is the best choice for large enterprises needing governed platform migration across many applications, since its wave-based cutover planning ties dependency mapping to rollback readiness for safer phased coexistence, whereas Valtech fits when you want coexistence-first wave plans that keep downtime risk and parallel-run complexity under control.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Deloitte
Wave-based migration wave planning with cross-domain cutover governance that ties dependency mapping to rollback planning.
Best for: Fits when large enterprises need governed platform migration across many applications, identity flows, and data domains.
Cognizant
Editor pickProgram-level governance that couples migration wave planning with test migration execution checkpoints to control risk across phased coexistence.
Best for: Fits when enterprises need large-program coordination for phased migration waves with identity, integration, and data workstreams.
Capgemini
Editor pickA migration factory operating rhythm links assessment artifacts to wave-level execution, cutover readiness, and reconciliation checkpoints across teams.
Best for: Fits when large enterprises need multi-app migration waves with strict governance, reconciliation, and integration planning.
Comparison Table
Deloitte
enterprise_vendorBig Four consultancy executing end-to-end platform migration and modernization engagements.
Wave-based migration wave planning with cross-domain cutover governance that ties dependency mapping to rollback planning.
Deloitte delivers enterprise platform migration services that combine current-state inventory work, migration planning, and execution governance across replatforming and refactoring programs. The delivery model typically includes detailed dependency mapping, target-state architecture alignment, and wave-based execution that supports coexistence periods with defined cutover plans.
Deloitte also provides data migration execution support, including extraction, transformation, validation, and reconciliation workflows. The differentiator for migration programs is the breadth of enterprise integration and control depth applied across application, identity, data, and operational readiness.
- +Strong migration governance with traceable decisions across waves and cutovers
- +Enterprise dependency mapping supports phased delivery with coexistence planning
- +Data migration delivery covers transformation, validation, and reconciliation workflows
- +Identity and access migration planning fits controlled enterprise rollouts
- –Heavier delivery process can slow small scope migrations
- –Ecosystem breadth increases coordination load across many teams
- –API integration depth depends on chosen partner tooling and delivery approach
- –Thick documentation and test artifacts require sustained stakeholder participation
Best for: Fits when large enterprises need governed platform migration across many applications, identity flows, and data domains.
Cognizant
enterprise_vendorIT services provider delivering cloud and application platform migration at scale.
Program-level governance that couples migration wave planning with test migration execution checkpoints to control risk across phased coexistence.
Cognizant supports large enterprise platform migrations with delivery programs built around application discovery, migration planning, and controlled execution across multiple workstreams. Integration is reinforced through engineering-led modernization for target-state architecture, including replatforming planning and execution governance for phased delivery.
The migration approach typically combines dependency mapping, test migration, and cutover planning to manage risk during coexistence. For enterprises needing strong orchestration across many teams, Cognizant brings program management depth and cross-domain engineering coverage for identity, configuration, and data flows.
- +Large-program orchestration for multi-team migration waves and governance artifacts
- +Engineering delivery supports dependency mapping across application and integration landscapes
- +Migration execution includes structured test migration and validation checkpoints
- +Strong cross-domain coverage for identity and configuration alongside application moves
- –Admin and governance artifacts can require heavy client participation
- –Automation depth varies by migration workstream and tooling choices
- –Complex integration inventories can stretch timelines when documentation is weak
- –Cutover and rollback planning often depend on prior readiness maturity
Best for: Fits when enterprises need large-program coordination for phased migration waves with identity, integration, and data workstreams.
Capgemini
enterprise_vendorEuropean-origin IT services leader running cloud and application platform migration programs.
A migration factory operating rhythm links assessment artifacts to wave-level execution, cutover readiness, and reconciliation checkpoints across teams.
Capgemini typically starts with platform assessment outputs like current-state inventory, dependency mapping, and target-state architecture alignment so teams can size waves and define technical constraints early. Delivery then follows migration strategy decisions such as lift-and-shift for low-risk components and refactoring for integration-heavy services, with a coordinated coexistence period and cutover plan. Data migration work includes extraction and transformation plus reconciliation reporting to detect mismatches before business signoff.
A tradeoff appears in the coordination overhead that comes with large program governance and parallel workstreams, which can slow early momentum on small scope migrations. Capgemini fits best for enterprises migrating many applications with shared integration patterns where automation and controlled rollout matter more than rapid single-app changes.
- +Migration factory delivery model supports repeatable wave execution
- +Dependency mapping and integration planning reduce late cutover surprises
- +Identity and configuration migration work is run as tracked streams
- +Reconciliation reporting improves data validation during migration phases
- –Governance-heavy programs add coordination overhead for narrow migrations
- –Early-stage change requests can impact dependency remapping cycles
- –Complex integration programs demand strong client ownership
- –Architecture alignment workshops require deliberate stakeholder attendance
CIO and architecture leadership
Migrate many apps with shared patterns
Fewer late integration issues
Platform engineering teams
Replatform with environment provisioning
Predictable rollout pacing
Show 2 more scenarios
Data engineering and analytics
Data migration with reconciliation
Higher data migration confidence
Extraction, transformation, and reconciliation reporting support mismatch detection before business acceptance.
Security and IAM teams
Identity migration across environments
Reduced authentication disruption
Identity migration is executed as a tracked workstream with cutover planning and acceptance gates.
Best for: Fits when large enterprises need multi-app migration waves with strict governance, reconciliation, and integration planning.
Infosys
enterprise_vendorIndian-origin IT services firm running enterprise platform migration and modernization programs.
Wave-based migration execution with API-centered provisioning and environment replication for coexistence periods.
Infosys mixes enterprise delivery capacity with repeatable migration engineering for large platform transitions. Migration work is typically anchored in structured current-state inventory, dependency mapping, and a target-state architecture workflow that supports multi-wave plans.
- +Large-scale migration engineering for complex enterprise dependency graphs
- +API-focused integration patterns for provisioning and cutover automation
- +Structured inventory and dependency mapping to reduce hidden coupling risk
- +Operational governance with RBAC-aligned access controls and audit trails
- –Delivery can become process-heavy for smaller migrations and short timelines
- –Depth in custom data transformation may depend on specific acceleration assets
- –Migration wave planning effort increases when app teams lack standardized interfaces
- –Coexistence period controls require disciplined configuration management by the client
Best for: Fits when enterprises need multi-wave platform migration with strong governance, integration, and controlled cutover orchestration.
Accenture
enterprise_vendorGlobal professional services firm delivering large-scale platform migration programs for enterprises.
Migration wave planning that ties dependency mapping, integration inventory, and cutover rehearsal into a single delivery rhythm.
Accenture delivers enterprise platform migration with program delivery depth, cross-domain engineering, and governance-heavy execution. Its migration support typically covers platform assessment outputs, migration strategy planning, and coordinated execution across application, data, and integration workstreams.
- +Strong end-to-end delivery for replatforming, refactoring, and phased waves
- +Detailed migration readiness assessment artifacts for portfolio prioritization
- +Governance controls with RBAC and audit log support for large programs
- +Automation and integration work built around documented APIs
- –Heavier program management overhead for smaller scope migrations
- –Dependency mapping depth varies by engagement team and tools used
- –Data migration execution can require additional specialist capacity
Best for: Fits when large enterprises need controlled migration waves across apps, data, and integrations.
Publicis Sapient
enterprise_vendorDigital business transformation consultancy focused on commerce and CX platform migrations.
Cross-discipline migration program governance that coordinates cutover planning, test cycles, and post-release hypercare across engineering and operations.
Publicis Sapient is an enterprise migration services provider that builds migration strategy and execution plans around replatforming and modernization programs. Delivery commonly includes application portfolio analysis, dependency mapping, and migration wave planning for large portfolios with coexistence periods.
- +Strong cross-functional delivery for replatforming, data work, and engineering execution
- +Migration wave planning supports coordinated releases across large dependency graphs
- +Dependency mapping reduces surprises during coexistence and phased transitions
- +Hypercare operating support helps stabilize services after cutover
- –Engagements require heavy technical input for dependency mapping and readiness alignment
- –Automation surface depends on agreed integration patterns and tooling choices
- –Refactoring-heavy programs need deeper engineering bandwidth than lift-and-shift
- –Governance artifacts and RBAC-style controls may be tailored per client architecture
Best for: Fits when enterprises need end-to-end migration execution planning with engineering, data, and operational stabilization across waves.
Thoughtworks
enterprise_vendorGlobal technology consultancy known for modernization and platform migration engineering.
Architecture refactoring support that produces migration-ready runbooks and operational guardrails, not just designs.
Thoughtworks brings a multidisciplinary migration approach that ties current-state inventory and migration strategy to implementation artifacts such as runbooks, test plans, and rollback planning. Engagements often emphasize dependency mapping across services, configuration migration readiness, and integration inventory so that migration waves match real system coupling. Delivery quality shows in how architecture decisions, API compatibility constraints, and operational controls are treated as migration deliverables rather than post-migration cleanup.
- +Engineering-led delivery that converts migration strategy into executable artifacts
- +Dependency mapping focus helps control coupling across services during migration waves
- +Strong test and reconciliation workflows for data validation
- +Clear operational plans for rollback and cutover handling
- –Identity migration decisions require sustained client ownership and fast approvals
- –Phased migration coordination can add process overhead for small teams
- –Deep architecture work may not fit pure lift-and-shift timelines
- –Automation and API surface coverage depends on target platform maturity
Best for: Fits when enterprises need architecture-guided migration with coordinated cutover, rollback, and data validation.
EPAM Systems
enterprise_vendorDigital platform engineering firm delivering commerce and content platform migrations.
Migration delivery factories that convert target-state architecture into coordinated migration waves with reusable automation scripts for environment provisioning and interface validation.
EPAM Systems executes large-scale platform migration programs that combine application portfolio assessment with engineering delivery across replatforming, refactoring, and lift-and-shift. The provider’s migration work leans on repeatable delivery factories that turn target-state architecture into implementable waves with dependency mapping and test migration support.
- +Engineering delivery integrates assessment outputs into migration wave planning
- +Strong throughput across phased migrations with parallel-run support
- +API-centric integration work reduces interface drift during cutover
- +Governed rollback plan design supports controlled downtime windows
- –Heavier process can add friction for small-scope migrations
- –Effective governance depends on client ownership of acceptance criteria
- –Legacy-to-cloud dependency mapping can expand discovery timelines
- –Automation depth varies by workload and integration complexity
Best for: Fits when enterprise portfolios need managed migration execution across phases, with tight integration control.
IBM Consulting
enterprise_vendorConsulting arm of IBM specializing in hybrid cloud and legacy platform migration services.
End-to-end migration wave planning that ties dependency mapping to cutover, rollback, and parallel run execution for shared services.
IBM Consulting works well for organizations that need a controlled migration program across many applications, since dependency mapping and migration wave planning reduce ordering conflicts. The service can drive lift-and-shift migration for selected workloads while coordinating replatforming and refactoring workstreams under one architectural target-state direction. Delivery artifacts commonly include rollback plan and cutover plan inputs that support coordinated parallel run and user acceptance testing cycles.
- +Migration program governance supports cutover and rollback planning across many apps
- +Dependency mapping helps order migration waves and reduce integration breakage
- +Enterprise delivery model supports hybrid environments and coexistence periods
- +Structured test migration and parallel run coordination for shared services
- –Requires substantial client decision throughput for target-state architecture choices
- –Automation and API surface depth can vary by technology stack engagement
- –Migration wave planning overhead can be high for small portfolios
- –Identity migration work needs early access to client IAM environments
Best for: Fits when enterprise teams need coordinated wave execution with governance across hybrid applications.
Valtech
agencyDigital agency delivering commerce and experience platform migration programs.
Migration wave planning built around coexistence design to minimize downtime and manage parallel run risk.
Valtech is an enterprise platform migration services firm that brings delivery teams skilled in replatforming and integration-heavy migrations. Work is typically organized around dependency mapping, migration wave planning, and coexistence design so applications can run through a staged cutover.
- +Clear migration wave planning that supports phased coexistence periods
- +Strong dependency mapping for application and integration sequencing
- +Practical API compatibility testing during migration readiness assessments
- +Governance-oriented delivery artifacts for controlled cutover planning
- –Migration tooling and automation depth can vary by program team
- –Requires disciplined input from client teams for configuration and identity migrations
- –Identity and configuration migration coverage may need extra specialist resources
- –Data validation and reconciliation reports can become detailed and time-intensive
Best for: Fits when enterprises need phased migration execution across many dependencies and integrations.
Conclusion
After evaluating 10 platform migration, Deloitte stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
How to Choose the Right Platform Migration
Enterprise platform migration work turns application moves, integration changes, and data relocation into a single governed program. This guide focuses on delivery models and control depth across Deloitte, Cognizant, Capgemini, Infosys, Accenture, Publicis Sapient, Thoughtworks, EPAM Systems, IBM Consulting, and Valtech.
The selection criteria used after the provider writeups center on migration wave planning mechanics, dependency mapping-to-cutover governance, and how teams operationalize automation through API and provisioning patterns. The buying path also weighs where programs slow down because governance artifacts demand active client participation, especially during phased coexistence and cutover rehearsal.
Platform Migration services: governed waves that connect dependency mapping to cutover, rollback, and operations
Platform migration is the coordinated movement from a current platform state to a target-state architecture across multiple applications, identity flows, and data domains. In practice, Deloitte ties wave-based migration planning to cross-domain cutover governance and connects dependency mapping to rollback planning so leadership can control what changes when and how failure recovery is executed.
Cognizant similarly couples wave planning to test migration execution checkpoints for phased coexistence, which shifts risk control from late-stage defects to earlier validation gates. The practical difference across providers shows up in how migration readiness artifacts become executable runbooks, how environment provisioning and interface validation are orchestrated across parallel streams, and how much client governance throughput is required to keep target-state architecture decisions from stalling waves.
Governed migration waves, dependency-to-cutover control, and automation surfaces
Platform migration services succeed when teams can plan migration waves with dependency mapping that explicitly drives cutover, rollback, and parallel run decisions. Deloitte, Cognizant, Capgemini, Infosys, Accenture, Publicis Sapient, Thoughtworks, EPAM Systems, IBM Consulting, and Valtech all describe wave planning, but the differentiator is how governance turns into executable delivery checkpoints.
The next buying hinge is integration depth through provisioning and API-based automation. Infosys emphasizes API-centered provisioning and environment replication, while EPAM Systems describes reusable automation scripts that support environment provisioning and interface validation across phased waves.
Wave planning tied to cutover governance and rollback
Deloitte connects cross-domain dependency mapping to rollback planning through wave-based migration wave planning with cutover governance across dependency graphs. IBM Consulting also ties dependency mapping to cutover, rollback, and parallel run execution for shared services across hybrid applications.
Test-gated coexistence execution checkpoints
Cognizant couples migration wave planning with test migration execution checkpoints to control risk during phased coexistence. Publicis Sapient coordinates cutover planning, test cycles, and post-release hypercare across engineering and operations for replatforming and data work.
Migration factory delivery rhythm and repeatable wave execution
Capgemini runs a migration factory rhythm that links assessment artifacts to wave-level execution, cutover readiness, and reconciliation checkpoints across teams. EPAM Systems delivers migration factories that convert target-state architecture into coordinated migration waves using reusable automation scripts for provisioning and interface validation.
API-centered provisioning and environment replication for phased coexistence
Infosys emphasizes API-centered provisioning and environment replication for coexistence periods to reduce cutover friction. Accenture ties migration wave planning to integration inventory and cutover rehearsal so teams can sequence apps, data, and integrations in controlled waves.
Architecture-guided runbooks and operational guardrails
Thoughtworks produces migration-ready runbooks and operational guardrails that convert migration strategy into executable artifacts. Deloitte also focuses on governed decisions across waves and cutovers, which helps leadership track what changes and when across many applications.
Client throughput requirements for governance-heavy programs
Cognizant flags that admin and governance artifacts can require heavy client participation to keep phased wave work moving. Valtech similarly notes that disciplined client input is required for configuration and identity migrations to sustain coexistence and parallel run planning.
Select by migration-wave mechanics and by where automation and governance must connect
A platform migration engagement should be judged by where its migration wave planning becomes decision control during cutover. Deloitte is strongest when dependency mapping must directly drive rollback planning and cross-domain cutover governance across many waves and domains.
A second decision fork should be whether the delivery model treats execution as a governed factory with repeatable wave cycles or as architecture-guided runbooks with operational guardrails. Capgemini and EPAM Systems lean toward factory rhythm, while Thoughtworks leans toward engineering-led runbooks that specify execution and guardrails for rollback and data validation.
Trace dependency mapping to rollback and cutover decisions
Choose Deloitte when dependency mapping across domains must tie directly into rollback planning and cutover governance during wave delivery. Choose IBM Consulting when rollback, cutover, and parallel run planning must be handled as shared services decisions across hybrid applications.
Match your coexistence risk profile to test-gated checkpoints
Choose Cognizant when phased coexistence needs test migration execution checkpoints that sit inside the wave plan. Choose Publicis Sapient when coordinated cutover planning must include engineering and operations stabilization with post-release hypercare across large dependency graphs.
Decide whether wave execution needs a migration factory cadence
Choose Capgemini when repeatable wave execution and reconciliation checkpoints must connect assessment artifacts to delivery rhythm across teams. Choose EPAM Systems when throughput across phased migrations matters and environment provisioning must run from reusable automation scripts plus interface validation.
Verify that automation hinges on API and environment replication where it matters
Choose Infosys when API-centered provisioning and environment replication are needed to keep coexistence periods controlled and consistent. Choose Accenture when migration wave planning must fuse integration inventory with cutover rehearsal so apps, data, and integrations move together on a controlled timeline.
Ensure the runbook artifacts match operational execution needs
Choose Thoughtworks when architecture refactoring must produce executable runbooks and operational guardrails that support coordinated cutover, rollback, and data validation. Choose Deloitte when leadership needs traceable decisions across waves and cutovers with governance artifacts tied to execution outcomes.
Size client participation expectations for governance artifacts and identity work
Choose Cognizant when the organization can sustain governance artifact review cycles across multi-team migration waves and phased coexistence. Choose Valtech when the organization can provide disciplined input for configuration and identity migrations to manage parallel run risk.
Which enterprises should buy these services for Platform Migration
These providers fit enterprise platform migration programs where multiple applications, identity flows, and data domains must move under a controlled migration wave plan. The differentiator is how much governance and client decision throughput the program can support during phased coexistence and cutover rehearsal.
The highest fit also depends on whether execution needs factory rhythm and provisioning automation or architecture-guided runbooks and operational guardrails.
Large enterprises with cross-domain dependency graphs
Deloitte fits when dependency mapping must connect to cross-domain cutover governance and rollback planning across many applications and waves. IBM Consulting also fits when coordinated wave execution must manage shared services across hybrid applications with governance.
Programs running phased coexistence with high integration and identity coupling
Cognizant fits when risk control requires migration wave planning plus test migration execution checkpoints across identity, integration, and data workstreams. Valtech fits when coexistence design must minimize downtime while sequencing dependencies across applications and integrations.
Enterprises that need repeatable migration wave execution across many applications
Capgemini fits when a migration factory model links assessment artifacts to wave execution, cutover readiness, and reconciliation checkpoints for repeatable delivery. EPAM Systems fits when reusable automation scripts must support environment provisioning and interface validation for parallel-run throughput.
Organizations requiring API-centered provisioning and environment replication
Infosys fits when automation depends on API-centered provisioning and consistent environment replication across coexistence periods. Accenture fits when integration inventory and cutover rehearsal must be integrated into a single delivery rhythm for phased waves.
Engineering-led teams that want migration-ready runbooks and operational guardrails
Thoughtworks fits when architecture refactoring must turn into executable runbooks that include operational guardrails for coordinated cutover, rollback, and data validation. Publicis Sapient fits when cross-functional coordination must align engineering delivery with operations stabilization and post-release hypercare.
Common Platform Migration buying mistakes and how to avoid them
Mistakes usually happen when governance artifacts remain undocumented as execution checkpoints or when dependency mapping does not drive cutover and rollback decisions during wave delivery. Another frequent failure is picking a delivery model that assumes too much client participation when governance-heavy artifacts become gating items.
A third pattern is treating automation as generic tooling instead of matching API-centered provisioning and environment replication needs to the organization’s coexistence plan.
Expecting wave planning to stay advisory without tying dependency mapping to rollback planning
Deloitte’s wave-based cutover governance explicitly ties dependency mapping to rollback planning, so the engagement should request that traceability as a deliverable. IBM Consulting similarly ties dependency mapping to cutover, rollback, and parallel run decisions, which prevents late-stage recovery gaps.
Underestimating how much client participation governance artifacts require during phased coexistence
Cognizant flags that admin and governance artifacts can require heavy client participation, so the program should budget named reviewers for wave checkpoints. Valtech also notes that disciplined input is required for configuration and identity migrations, so identity and configuration decision owners should be staffed before kickoff.
Selecting a delivery model that does not convert architecture work into operational runbooks
Thoughtworks converts migration strategy into executable migration-ready runbooks and operational guardrails, so the buyer should require those artifacts to include rollback and data validation workflows. Accenture provides end-to-end delivery tied to cutover rehearsal and readiness assessment artifacts, which helps prevent runbooks from staying design-only outputs.
Assuming automation depth will be uniform across migration workstreams
Infosys emphasizes API-centered provisioning and environment replication, so automation requirements should be stated in terms of provisioning and replication outcomes for coexistence periods. Cognizant cautions that automation depth can vary by migration workstream and tooling choices, so the engagement should define which workstreams must use automation and where manual steps are acceptable.
Choosing a delivery cadence that cannot support reconciliation and readiness checkpoints
Capgemini links assessment artifacts to reconciliation checkpoints and cutover readiness across teams, so the buyer should confirm that reconciliation gates sit inside the wave plan. EPAM Systems adds throughput via environment provisioning and interface validation scripts, so teams should verify that the scripts cover the interfaces that actually change during wave execution.
What analysts checked to build this Platform Migration shortlist
Analysts gathered the provider coverage by opening the original publication and copying each provider figure that appears next to passages describing platform migration scope, wave planning mechanics, and governance control. Analysts then compared each captured figure with official documentation and changelogs, and they included an independent review only when an independent review was cited for the same claim.
Analysts kept figures when the wording and numbers aligned with provider materials and they used published benchmark citations only when the benchmark source itself was explicitly tied to the claim. Deloitte stood out in the selection set because its wave-based planning explicitly connects cross-domain dependency mapping to cutover governance and ties dependency mapping to rollback planning.
Frequently Asked Questions About Platform Migration
What integration and API checks prevent downtime during a platform migration wave?
How should identity and SSO be handled across coexistence periods without breaking RBAC?
What data migration artifacts and validation steps keep extracted data consistent with the target data model?
Which service providers use API-centered provisioning and environment replication for repeatable waves?
How do teams choose lift-and-shift versus refactoring when shared integrations are tightly coupled?
What tradeoff appears when migration governance adds coordination overhead across many teams?
How do rollback and cutover plans differ between wave-based programs and big-bang style migrations?
Where does API compatibility fall short when configuration migration changes the runtime behavior?
What common onboarding tasks should teams complete before migration waves start?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
Funding and competing interests
This study was co-funded by several of the vendors assessed in it. No single vendor funded it. Funders could propose the market studied.
They had no role in selecting vendors, setting or weighting criteria, analysing data or drawing conclusions, and they received the same factual-accuracy check as every other vendor assessed.
Market definition, inclusion rules and criteria weights were fixed by an editor before research began and did not change afterwards. Editorial process →
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