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Business Process OutsourcingTop 10 Best Integration Managed Services of 2026
Compare top Integration Managed Services providers in 2026, with ranking criteria and tradeoffs for enterprise integration teams.
How we ranked these tools
Core product claims cross-referenced against official documentation, changelogs, and independent technical reviews.
Analyzed video reviews and hundreds of written evaluations to capture real-world user experiences with each tool.
AI persona simulations modeled how different user types would experience each tool across common use cases and workflows.
Final rankings reviewed and approved by our editorial team with authority to override AI-generated scores based on domain expertise.
Score: Features 40% · Ease 30% · Value 30%
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Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Accenture
Contract-first schema governance with interface versioning across integration lifecycle.
Built for fits when enterprise teams need governed integration operations across multiple systems and data domains..
Capgemini
Editor pickRBAC-backed integration operations with auditable change tracking across API and workflow runs.
Built for fits when enterprise teams need controlled, API-driven integrations with strong governance..
IBM Consulting
Editor pickGoverned API and integration lifecycle operations with audit log support and RBAC-driven approvals.
Built for fits when enterprises need managed integration operations with auditability, schema control, and API automation..
Related reading
- Business Process OutsourcingTop 10 Best Integrated Managed Services of 2026
- Digital Transformation In IndustryTop 10 Best Integration Consulting Services of 2026
- Business Process OutsourcingTop 10 Best Cloud Integration Services of 2026
- Business Process OutsourcingTop 10 Best Business Process Integration Software of 2026
Comparison Table
This comparison table evaluates Integration Managed Services providers by integration depth, data model and schema alignment, and the scope of automation and API surface. It also compares admin and governance controls such as provisioning workflows, RBAC options, and audit log coverage to show how each platform supports extensibility and safe configuration changes. Readers can use the table to map throughput and operational tradeoffs to real integration delivery patterns across providers.
Accenture
enterprise_vendorProvides integration managed services that cover enterprise application integration, API and event-driven integration, middleware operations, and continuous monitoring for large-scale environments.
Contract-first schema governance with interface versioning across integration lifecycle.
Integration depth shows up in how Accenture typically structures delivery around canonical data models, schema mapping, and interface contracts that persist into operations. Automation and API surface are handled through managed connectors, custom API integrations, and repeatable deployment pipelines that support throughput targets and controlled rollouts. Admin and governance controls are exercised via role-based access patterns, change approvals, and audit log practices for integration configuration and runtime actions.
A tradeoff is that integration governance and model alignment add lead time before high-velocity changes reach production. A common usage situation is multi-team programs that require consistent data model enforcement across ERP, CRM, and data platform pipelines while maintaining controlled releases and traceability.
- +Structured integration delivery with contract-first schema mapping and change control
- +Managed automation for provisioning and deployment across dev, test, and production
- +Admin patterns with RBAC, audit logging support, and controlled configuration changes
- +Extensible integration patterns across API, event, and batch workloads
- –Governance and model alignment can slow early iterations
- –Custom integration work may require strong internal SME coordination
Best for: Fits when enterprise teams need governed integration operations across multiple systems and data domains.
More related reading
Capgemini
enterprise_vendorOperates integration platforms and middleware with managed services that include connectivity, integration monitoring, batch and streaming orchestration, and incident response.
RBAC-backed integration operations with auditable change tracking across API and workflow runs.
Capgemini fits teams that need managed integration across multiple applications, where throughput, schema consistency, and data model alignment drive day-to-day reliability. Integration work typically spans API connectivity, event or workflow orchestration, and integration testing tied to versioned schemas and contract changes. Governance controls tend to include role-based access, operational audit trails, and structured handoffs between build, test, and run activities.
A tradeoff is that deeper governance and integration depth often require more upfront design for schemas, interfaces, and ownership boundaries. This is a strong fit when environments include regulated data, multiple downstream consumers, and ongoing change cycles that need controlled deployment paths and repeatable automation runs.
- +Integration governance with RBAC and audit log support for controlled access
- +Deep schema and data model mapping for stable contracts across services
- +API and automation coverage for repeatable provisioning and configuration changes
- +Operational controls that support structured release, testing, and run handoffs
- –Upfront interface and data model design can be heavier than lightweight setups
- –Automation and controls add process overhead for small integration scopes
- –Heterogeneous platform coverage can increase validation cycles
Best for: Fits when enterprise teams need controlled, API-driven integrations with strong governance.
IBM Consulting
enterprise_vendorRuns managed integration services that manage API lifecycles, integration middleware operations, message routing, and operational support for hybrid integration landscapes.
Governed API and integration lifecycle operations with audit log support and RBAC-driven approvals.
IBM Consulting brings integration depth through delivery teams that handle design-to-operations work, including API orchestration, data transformation, and integration monitoring. Managed services typically include operational governance like audit log review, change management, and incident workflows that keep throughput targets and error budgets visible. Data model attention shows up in mapping across schemas and versioning strategies that reduce breaking changes in downstream consumers. Automation and API surface coverage are reinforced by integration adapters, lifecycle automation for environments, and configurable pipelines that support extensibility.
A practical tradeoff is that integration breadth and control depth often require stronger upfront scoping for data models, API contracts, and RBAC roles. Teams with fast-moving schemas or limited contract ownership may see more iteration cycles to reach stable provisioning and governance. A strong usage situation is cross-platform integration where multiple applications share shared entities, require consistent schemas, and need managed rollout with traceable approvals and auditability.
- +Governance workflows with RBAC-aligned controls and audit log visibility
- +Managed operations for API orchestration, monitoring, and incident runbooks
- +Schema and data model mapping that supports versioned contracts
- +Automation for environment provisioning and controlled rollout patterns
- –Requires detailed upfront scoping for schemas, contracts, and governance roles
- –Iteration risk increases when data models change faster than version policies
- –Complex estates can increase coordination overhead across stakeholders
Best for: Fits when enterprises need managed integration operations with auditability, schema control, and API automation.
Tata Consultancy Services
enterprise_vendorProvides integration managed services spanning system integration operations, ETL and data movement support, API enablement runbooks, and production monitoring.
RBAC and audit log coverage across integration environments for traceable schema and deployment changes.
For integration managed services, TCS is distinctive for deep delivery across enterprise integration patterns, including data model mapping, schema provisioning, and controlled rollout. The service typically covers end-to-end integration delivery with documented API and automation interfaces for provisioning, monitoring, and lifecycle operations.
Governance is handled through admin controls such as RBAC, audit logging, and change traceability across environments, which supports regulated integration programs. Integration throughput is managed via operational runbooks and capacity planning for batch, streaming, and API traffic profiles.
- +Integration delivery spans API, batch, and event flows with consistent operations
- +Data model mapping and schema provisioning for controlled interface evolution
- +Automation and API surface for provisioning, deployments, and integration monitoring
- +Governance controls with RBAC and audit logs for change traceability
- +Extensibility through reusable integration components and configuration-driven patterns
- –Complex governance setup can add overhead for small integration scopes
- –API surface varies by engagement, requiring tighter scoping for automation depth
- –Environment promotion and rollback workflows may need explicit design upfront
- –Integration data model standardization can take time across multiple apps
Best for: Fits when enterprises need managed integration delivery with strong governance and controlled data model changes.
Wipro
enterprise_vendorDelivers managed integration services for enterprise connectivity, middleware operations, API management support, and steady-state and change support for connected applications.
Managed schema mapping with versioned transformation rules tied to controlled provisioning workflows.
Wipro delivers integration managed services that run from API and event ingestion through mapping, schema enforcement, and production provisioning. Integration depth shows up in data model work like canonical schemas, transformation rules, and lineage-ready payload definitions across connected systems.
Automation and API surface are handled through managed workflows, versioned deployment artifacts, and operational interfaces for monitoring, replays, and change control. Governance is addressed via RBAC-aligned administration, environment separation, and audit log practices that track configuration changes, access, and job execution outcomes.
- +End-to-end integration delivery from ingestion to mapping and production provisioning
- +Canonical data model and schema enforcement support consistent cross-system payloads
- +Managed automation workflows support replay and controlled redeployments
- +Operational interfaces cover monitoring, job outcomes, and change execution visibility
- +Governance controls include RBAC-aligned administration and audit logging
- –Integration depth depends on client target data model maturity and definitions
- –Extensibility still requires coordinated engineering for custom automation actions
- –API surface coverage can vary by integration pattern and target platform
- –Operational throughput tuning needs early capacity planning for peak loads
Best for: Fits when enterprise teams need managed API and data-model control across multiple integration patterns.
Infosys
enterprise_vendorOperates integration and connectivity managed services that include middleware support, enterprise integration monitoring, and managed change for multi-application workflows.
Schema-driven integration management with governance, audit logging, and controlled rollout processes.
Infosys fits enterprises that need managed integration delivery across multiple apps, vendors, and environments. It provides integration depth through lifecycle governance, schema-driven interface work, and operational controls tied to delivery and monitoring.
Teams get automation and API surface coverage through documented integration patterns and managed connectivity that supports provisioning, versioning, and controlled rollout. Admin and governance controls center on RBAC-aligned access patterns, audit logging, and change management for predictable throughput and reduced rework.
- +Managed integration delivery with lifecycle governance and operational monitoring
- +Schema-first approach supports consistent data model mapping across services
- +Automation patterns for provisioning, versioning, and controlled deployment
- +API integration support with extensibility for interface evolution
- +Admin controls include RBAC-aligned access and audit log coverage
- –Integration work depends on clear target data model contracts
- –Deep governance can add process overhead for small change scopes
- –API automation requires disciplined configuration management
- –Extensibility may be constrained by agreed delivery standards
Best for: Fits when large enterprises need controlled, schema-governed integration across many systems and environments.
NTT DATA
enterprise_vendorOffers integration managed services that cover application integration operations, workflow orchestration support, and production monitoring with defined service management processes.
RBAC and audit log integration governance for managed API and integration configuration changes.
NTT DATA operates as an integration managed services provider with delivery patterns built around enterprise integration, not just project handoff. Teams get managed work across integration design, schema and data model mapping, and API-based automation for provisioning and ongoing throughput management.
Governance artifacts focus on RBAC, audit log coverage, and change control needed to run integration fleets across multiple environments. Extensibility is delivered through documented API interfaces and controlled configuration so integration logic can evolve without destabilizing connected systems.
- +Managed integration delivery with schema and data model mapping governance
- +API surface supports automation for provisioning and operational workflows
- +RBAC and audit log controls support governed integration administration
- +Change control processes support controlled deployments across environments
- –Integration governance artifacts can require extra upfront design alignment
- –API-first extensibility depends on consistent data model standards
- –Throughput tuning often needs dedicated integration performance profiling
Best for: Fits when large enterprises need governed, API-driven integration operations across many systems.
DXC Technology
enterprise_vendorProvides managed services for integration workloads including middleware operations, data pipeline support, and operational control for enterprise integration and connectivity.
Governed provisioning with RBAC-aligned access controls and audit logging for integration changes.
DXC Technology delivers integration managed services focused on enterprise integration depth, including application, data, and process orchestration across heterogeneous systems. The delivery model emphasizes governed provisioning, configuration management, and API-led integration work with explicit data model mapping and schema handling.
DXC’s automation and API surface is typically exercised through repeatable runbooks, monitored workflows, and controlled change paths tied to admin governance such as RBAC and audit log practices. This combination fits teams that need throughput-aware operations, integration schema control, and extensibility through documented interfaces rather than one-off builds.
- +Integration delivery includes data model and schema mapping across systems
- +API-led workflows support controlled extensibility and consistent integration patterns
- +Governance supports RBAC and audit log practices for regulated environments
- +Automation favors monitored workflows and repeatable runbooks for operations
- –Automation maturity depends on the specific integration stack in use
- –Extensibility design can require early alignment on schema contracts
- –Throughput tuning is process and tooling specific, not universal across projects
- –Admin and governance controls need clear target-state definitions upfront
Best for: Fits when enterprises need governed integration operations with controlled data models and API contracts.
Sopra Steria
enterprise_vendorDelivers application and integration managed services with run support, middleware administration, and production stabilization for enterprise connectivity programs.
RBAC and audit log coverage tied to release and interface change control
Sopra Steria delivers integration managed services that cover system onboarding, interface buildout, and ongoing operations for enterprise landscapes. Delivery emphasizes integration depth through governed middleware workflows and managed mappings between source and target data models.
The engagement typically includes automation and API surface work like provisioning, scheduled syncs, and adapter extensibility for new partners and systems. Admin controls focus on RBAC, change control, and audit-ready operation logs to support governance across releases and environments.
- +Integration delivery spans onboarding, interface buildout, and managed operations
- +Governed workflows reduce schema drift across source and target models
- +Provisioning and scheduled automation support repeatable throughput targets
- +RBAC and change control support multi-team governance and release discipline
- –API surface depth can require contract-specific scoping for each integration type
- –Data model ownership boundaries can be unclear without a defined schema steward
- –Extensibility paths may depend on the selected middleware or adapter pattern
Best for: Fits when enterprises need controlled integration operations with documented schema and governance artifacts.
Atos
enterprise_vendorRuns managed integration services for enterprises with operations support across middleware, integration monitoring, and change governance for connected business processes.
Enterprise governance and audit log practices integrated into managed delivery and integration operations.
Atos fits teams needing enterprise integration management with governance controls across many systems and environments. It delivers integration services that cover mapping, provisioning, and orchestration around a defined data model, with attention to auditability and operational controls.
Automation is supported through documented integration interfaces and API-driven workflows, enabling repeatable schema and configuration changes. Governance is handled via role controls, change management practices, and tracking that supports controlled throughput and safer release cycles.
- +Enterprise integration management across multiple landscapes and environments
- +Governance focus with auditability tied to delivery and operational controls
- +API-driven automation for provisioning, orchestration, and workflow execution
- +Schema and mapping discipline that supports consistent downstream contracts
- –Integration depth can increase dependency on Atos delivery workflows
- –API and automation coverage may require architecture alignment per engagement
- –Extensibility often depends on agreed configuration and change process
Best for: Fits when regulated enterprises need managed integration plus schema control and audit trail governance.
How to Choose the Right Integration Managed Services
This guide covers Accenture, Capgemini, IBM Consulting, Tata Consultancy Services, Wipro, Infosys, NTT DATA, DXC Technology, Sopra Steria, and Atos for integration managed services.
It focuses on integration depth, data model governance, automation and API surface coverage, and admin and governance controls that control schema and change across environments.
Integration managed services that run governed integrations across API, events, and data flows
Integration managed services operate enterprise integrations from interface design through production operations across API, event, and batch workloads with monitoring, provisioning, and change control. The core value is consistent schema and data model evolution with controlled deployments and auditable administration. Providers like Accenture and Capgemini show this pattern by pairing interface versioning and RBAC-backed operations with monitoring and workflow run governance.
Teams typically use these services when multiple systems and data domains must stay coordinated under release discipline and when schema drift can break downstream contracts. Enterprises also use them when provisioning, environment promotion, and replay workflows must be automated through an explicit automation and API surface.
Evaluation criteria for governed integration operations and controlled schema change
The evaluation should map integration depth to how the provider controls schema, interface versions, and transformation rules across environments. It should also confirm that automation and API surfaces exist for provisioning, configuration updates, and operational workflows.
Admin and governance controls need to support RBAC-aligned access, audit log visibility, and approval-driven change paths for integration lifecycle operations. This matters because schema work and contract changes drive most integration failure modes in regulated release cycles.
Contract-first schema governance with interface versioning
Accenture delivers contract-first schema mapping with interface versioning across the integration lifecycle, which reduces schema drift risk when multiple data domains evolve. Wipro also ties managed schema mapping with versioned transformation rules to controlled provisioning workflows.
RBAC-aligned administration with audit log coverage
Capgemini operates integration operations with RBAC-backed access and auditable change tracking across API and workflow runs. IBM Consulting, Tata Consultancy Services, NTT DATA, DXC Technology, Sopra Steria, and Atos all emphasize RBAC-aligned workflows plus audit logging to support governance and traceable configuration changes.
Automation and API surface for provisioning, deployment, and environment promotion
Accenture provides managed automation for provisioning and deployment across dev, test, and production, which is critical when the integration estate must be promoted safely. Tata Consultancy Services and Infosys also focus on documented API and automation interfaces for provisioning and lifecycle operations.
Data model mapping depth across API, event, and batch workloads
Capgemini and IBM Consulting support deep schema and data model mapping for stable contracts across services and orchestration workflows. Tata Consultancy Services and Accenture add breadth by delivering integration patterns across API, batch, and event flows with governed mapping and rollout controls.
Governed integration lifecycle operations with policy enforcement
IBM Consulting emphasizes governed API and integration lifecycle operations with audit log support and RBAC-driven approvals, which adds control depth for release discipline. NTT DATA and Sopra Steria similarly center change control artifacts and release-linked governance that supports controlled deployments across environments.
Throughput-aware operational controls for steady-state and change
Tata Consultancy Services manages integration throughput via operational runbooks and capacity planning for batch, streaming, and API traffic profiles. DXC Technology also emphasizes throughput-aware operations through monitored workflows and repeatable runbooks tied to admin governance.
Decision framework for selecting an integration managed services provider
Selection should start with integration breadth and integration depth alignment to the target workload mix across API, events, and batch. Accenture fits when contract-first schema governance and interface versioning across the lifecycle are required, while Capgemini fits when RBAC-backed auditable operations and stable contract mapping are the primary need.
Next, the provider’s automation and API surface should be validated against the required operational activities like provisioning, environment promotion, configuration change, and replay or redeploy workflows. Governance controls then need to be tested against real admin workflows for approvals, audit trails, and RBAC-aligned access control.
Map workload mix to provider integration breadth and depth
List required integration patterns across API calls, event orchestration, and batch or ETL data movement. Accenture covers API, event, and batch interfaces with end-to-end design through production operations, while Tata Consultancy Services spans API, batch, and event flows with controlled rollout and monitoring.
Require an explicit data model and schema governance approach
Confirm whether the provider uses contract-first schema governance with interface versioning and change traceability. Accenture offers contract-first schema governance with interface versioning, and Wipro provides managed schema mapping with versioned transformation rules tied to controlled provisioning.
Validate automation and API surface for operations, not just builds
Ask how provisioning, deployment, configuration changes, and environment promotion are automated through documented APIs or workflow interfaces. Accenture automates provisioning and deployment across dev, test, and production, while IBM Consulting and Infosys emphasize automation interfaces tied to controlled rollout.
Score admin and governance controls for RBAC and auditability
Check for RBAC-aligned administration and audit log visibility tied to integration lifecycle actions. Capgemini supports RBAC and auditable change tracking across workflow runs, and IBM Consulting supports RBAC-driven approvals plus audit trails.
Stress-test change workflows against schema churn and stakeholder coordination
If data models change quickly, insist on version policy handling that prevents breaking downstream contracts. IBM Consulting and Accenture both use governed lifecycle operations, but IBM Consulting requires detailed upfront scoping for schemas and governance roles, which can increase coordination overhead when data models change faster.
Confirm throughput operations include monitoring and tuning runbooks
Demand operational controls and runbooks that manage steady-state throughput and capacity for batch, streaming, and API traffic profiles. Tata Consultancy Services handles throughput via runbooks and capacity planning, while DXC Technology ties monitored workflows and repeatable runbooks to governed provisioning and configuration changes.
Which teams should contract integration managed services
Integration managed services fit organizations that need controlled change across schemas, environments, and operational workflows. The right providers depend on whether the main constraint is governance depth, data model discipline, or API-led automation for operations.
Accenture, Capgemini, IBM Consulting, Tata Consultancy Services, Wipro, Infosys, NTT DATA, DXC Technology, Sopra Steria, and Atos each target slightly different mixes of integration lifecycle control and admin governance depth.
Enterprise teams that must govern schema and interface versions across multiple data domains
Accenture fits because contract-first schema governance with interface versioning aligns with controlled change across integration lifecycle stages. Tata Consultancy Services also fits because RBAC and audit log coverage is tied to traceable schema and deployment changes across environments.
Enterprises that need auditable API-driven integration operations with RBAC administration
Capgemini excels with RBAC-backed integration operations and auditable change tracking across API and workflow runs. IBM Consulting also fits because governed API and integration lifecycle operations include audit log support and RBAC-driven approvals.
Large enterprises with multi-application estates that require API automation and configuration governance
NTT DATA fits when governed, API-driven integration operations must run across many systems with RBAC and audit log integration governance. Infosys also fits because schema-driven integration management includes governance, audit logging, and controlled rollout processes across many environments.
Regulated enterprises that need audit trail governance integrated into integration operations
Atos fits when enterprise governance and audit log practices must be integrated into managed delivery and integration operations. DXC Technology fits when governed provisioning includes RBAC-aligned access controls and audit logging for integration changes that support regulated release cycles.
Pitfalls that cause integration managed services engagements to drift
Common pitfalls come from mismatches between schema governance expectations and the provider’s required upfront scoping for contracts and governance roles. Another pitfall is assuming automation depth exists for every integration pattern without aligning data model standards and admin governance workflows.
Several cons across providers point to planning gaps in environment promotion, rollback design, schema standardization, and throughput tuning runbooks.
Treating schema governance as a build-time task instead of a lifecycle control
Accenture’s contract-first schema governance and interface versioning work across the integration lifecycle, while Tata Consultancy Services and Infosys tie RBAC and audit logging to schema and controlled rollout. Skipping lifecycle governance design leads to slowed early iterations in Accenture and heavier upfront interface and data model design overhead in Capgemini and IBM Consulting.
Under-scoping governance roles and approval workflows before provisioning automation begins
IBM Consulting requires detailed upfront scoping for schemas, contracts, and governance roles, which becomes a coordination risk when stakeholders are not aligned early. Sopra Steria and NTT DATA also rely on extra upfront design alignment to define RBAC-linked governance artifacts that support release and interface change control.
Assuming automation and API surface coverage matches every operational workflow
Tata Consultancy Services notes that API surface varies by engagement, and Wipro states that API surface coverage can vary by integration pattern and target platform. DXC Technology also ties automation maturity to the specific integration stack, so operational automation should be validated against provisioning, replay, and change paths before delivery.
Delaying data model standardization and contract alignment until after environment promotion is underway
Tata Consultancy Services calls out that integration data model standardization can take time across multiple apps, which affects environment promotion and rollback workflows unless explicit design happens upfront. Wipro and Infosys depend on canonical schemas and schema-first approaches, so late data model alignment slows controlled redeployments.
Ignoring throughput tuning requirements tied to monitoring and capacity planning
Tata Consultancy Services manages throughput with operational runbooks and capacity planning for batch, streaming, and API traffic profiles, while DXC Technology flags that throughput tuning is process and tooling specific. Planning should include performance profiling and runbook definition early to avoid late operational instability.
How We Selected and Ranked These Providers
We evaluated Accenture, Capgemini, IBM Consulting, Tata Consultancy Services, Wipro, Infosys, NTT DATA, DXC Technology, Sopra Steria, and Atos on integration depth, data model governance controls, automation and API surface coverage, and admin controls like RBAC and audit logging. Each provider received a combined score using separate editorial criteria for capabilities, ease of use, and value, with capabilities carrying the most weight at forty percent while ease of use and value each contributed thirty percent. The ranking reflects criteria-based scoring across the provided provider profiles and stated strengths, not hands-on lab testing.
Accenture set the pace by combining contract-first schema governance with interface versioning across the integration lifecycle and by delivering managed automation for provisioning and deployment across dev, test, and production. That combination lifted both governance control depth and operational automation coverage, which carried the highest weight in the overall ranking.
Frequently Asked Questions About Integration Managed Services
How do integration managed services handle API versioning and contract changes across environments?
Which providers are strong at RBAC-aligned administration and audit logging for integration operations?
What delivery model best fits onboarding to a new integration program with schema governance and controlled rollout?
How do these services manage data model mapping and transformation consistency at scale?
How is data migration handled when moving integration logic and configurations to new middleware or platforms?
What mechanisms reduce integration downtime when replays, backfills, or scheduled syncs fail?
Which providers offer stronger extensibility for integration logic without destabilizing connected systems?
How do integration managed services support security controls like least-privilege access to configuration and runtime jobs?
How do teams request and validate operational readiness for high-throughput integration workloads?
Conclusion
After evaluating 10 business process outsourcing, Accenture 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.
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
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