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Data Science AnalyticsTop 10 Best Outsource Data Enrichment Services of 2026
Ranking roundup of top outsource data enrichment services with evaluation criteria and tradeoffs for teams, plus a provider like WNS.
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%
Gitnux may earn a commission through links on this page — this does not influence rankings. Editorial policy
Flatworld Solutions is the best fit for teams running scheduled lead and account enrichment who need managed mapping into CRM fields, and if you’re prioritizing repeatable, batch-style delivery for data teams with stronger matching inputs, TaskUs is a solid alternative.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Flatworld Solutions
Client-driven enrichment provisioning that locks field mappings into repeatable execution cycles for batch loads.
Built for fits when teams run scheduled lead and account enrichment and need managed mapping to CRM fields..
TaskUs
Editor pickManaged enrichment operations with configurable workflow steps for recurring batch delivery and quality review loops.
Built for fits when data teams need managed, repeatable enrichment delivery for batch CRM updates and can provide matching inputs..
WNS
Editor pickProgram-managed entity resolution runs that pair matching rules with QA remediation loops across batch enrichment cycles.
Built for fits when data quality teams need outsourced enrichment with managed throughput, defined matching rules, and controlled governance..
Comparison Table
Flatworld Solutions
specialistOutsourcing company providing data enrichment, data entry, and data processing services across industries.
Client-driven enrichment provisioning that locks field mappings into repeatable execution cycles for batch loads.
Flatworld Solutions delivers outsourced data enrichment with an operations-first workflow for contact and account augmentation. The service is geared toward high-volume batch processing that fits periodic CRM and marketing updates, with file-based ingestion patterns and structured output for downstream loading.
Integration depth is driven by enrichment provisioning for client-defined attributes and repeatable execution cycles. Data governance is supported through controlled mapping for fields and consistent transformations across runs.
- +Repeatable batch enrichment runs for consistent CRM and marketing updates
- +Clear attribute mapping between source fields and enrichment outputs
- +Operational turnaround for large file-based enrichment requests
- +Documented enrichment configuration patterns for repeat execution
- –API enrichment coverage is not positioned as the primary integration path
- –Governance and identity resolution require more upfront configuration discipline
- –Turnaround depends on batch sizing and attribute scope definition
- –Real-time enrichment workflows are not the focus compared with batch delivery
Best for: Fits when teams run scheduled lead and account enrichment and need managed mapping to CRM fields.
TaskUs
enterprise_vendorOutsourcing company offering data operations including enrichment and data processing services.
Managed enrichment operations with configurable workflow steps for recurring batch delivery and quality review loops.
TaskUs delivers outsourced data enrichment operations with an emphasis on high-volume execution and managed workflows for contact and account attribute completion. Delivery is typically shaped around ingesting records in batch formats, running enrichment processes through trained teams, and returning standardized outputs for downstream CRM use.
Integration depth is strongest when enrichment deliverables need to fit existing data pipelines and quality checks rather than when teams require extensive self-serve tooling. TaskUs is best evaluated on operational consistency, match behavior, and how quickly process changes can be incorporated across recurring enrichment cycles.
- +Operates at enrichment batch scale with dedicated workflow handling
- +Returns enrichment outputs designed for direct CRM ingestion
- +Process change management supports recurring enrichment programs
- +Trained execution reduces variability versus ad-hoc enrichment efforts
- –API enrichment depth is typically less central than batch delivery workflows
- –Governance controls like RBAC and audit log are less transparent publicly
- –Entity resolution quality depends on provided matching rules and identifiers
- –Real-time enrichment turnaround depends on program setup and throughput targets
Best for: Fits when data teams need managed, repeatable enrichment delivery for batch CRM updates and can provide matching inputs.
WNS
enterprise_vendorBusiness process management company offering data enrichment and data management services.
Program-managed entity resolution runs that pair matching rules with QA remediation loops across batch enrichment cycles.
WNS delivers outsourced data enrichment through managed contact, account, and entity workflows that run against defined source formats and matching rules. Its differentiator is operational depth for large-scale append and verification work, including batch processing orchestration and conversion of enrichment outputs into downstream-ready structures.
WNS also supports integration activities that reduce handoffs between enrichment, CRM updates, and downstream analytics pipelines. Teams typically engage WNS when accuracy targets, throughput needs, and governance documentation matter more than self-serve enrichment tooling.
- +Managed enrichment delivery at high volume with repeatable operational runs
- +Entity resolution oriented processing for stable entity linking
- +Defined workflow handoffs to CRM and analytics-oriented output formats
- +Dedicated program structure for quality and remediation loops
- –Integration work depends on migration mapping and partner coordination
- –Less suitable for teams needing fully self-serve enrichment execution
- –Automation and configuration depth require scoping of rules and outputs
- –Turnaround for bespoke variants can lag small, iterative experiments
Best for: Fits when data quality teams need outsourced enrichment with managed throughput, defined matching rules, and controlled governance.
Genpact
enterprise_vendorGlobal professional services firm offering data enrichment and analytics as part of its BPO portfolio.
Managed entity resolution and linkage operations that combine matching logic with enrichment output standardization.
Genpact runs enrichment programs that combine attribute append with matching logic to reduce duplicate entities and improve record consistency. Deliverables usually include normalized outputs ready for CRM enrichment pipelines, along with quality metrics tied to match behavior and completeness. Automation is expressed through repeatable run configurations that production teams can re-execute when source feeds change.
A key tradeoff is that full real-time enrichment depends on an integration architecture that Genpact configures to fit the client workflow. File-based and batch execution fit well when data teams run periodic lead enrichment cycles or backfill account records from CRM exports.
- +Managed enrichment operations with repeatable run configurations
- +Entity resolution workflows to reduce duplicate lead and account records
- +Quality reporting tied to match behavior and attribute completeness
- +Integration via API and controlled file handoff patterns
- –Real-time enrichment requires additional workflow and integration design
- –Operational onboarding can add lead time for new data sources
Best for: Fits when teams need managed enrichment plus entity resolution for CRM-grade data.
Concentrix
enterprise_vendorGlobal business performance optimization company providing data enrichment among BPO services.
Managed enrichment delivery built around match quality controls for batch record append feeding CRM and downstream routing.
Concentrix delivers outsourced data enrichment services that fit CRM enrichment and contact and account data completion workflows. Its differentiator is delivery at scale through managed operations that pair enrichment execution with match quality management for downstream routing.
Teams can expect file-based enrichment support and operational process controls suited to high-volume record append and verification cycles. The offering is best evaluated on integration and governance surfaces during implementation because those determine how enrichment results flow into existing identity resolution and CRM processes.
- +Managed enrichment operations for large batch workloads
- +Clear workflow fit for contact and account enrichment cycles
- +Operational controls help maintain match quality at scale
- +File-based delivery supports established enrichment pipelines
- –API enrichment depth is less transparent than pure-play vendors
- –Real-time enrichment integration is not the strongest documented path
- –Governance and audit logging depend on implementation choices
- –Identity resolution tuning may require ongoing engagement
Best for: Fits when data teams need outsourced enrichment executed reliably into CRM or marketing workflows with managed operations.
Infosys BPM
enterprise_vendorBusiness process management subsidiary of Infosys offering data enrichment and data services.
Managed enrichment workflow orchestration that ties input, enrichment steps, and operational run control into one delivery lifecycle.
Infosys BPM is positioned for outsourcing engagements where enrichment tasks are packaged into repeatable workflows and executed with operational controls. Batch enrichment can be run from files and exported back into downstream systems, while API enrichment can be wired for interactive or near-real-time ingestion depending on the integration design. Automation is centered on orchestrating steps like data normalization and attribute completion rather than only calling an enrichment vendor point feature.
A key tradeoff is that deeper workflow governance often adds implementation lead time compared with lightweight file-and-return enrichment. The best fit appears when teams need consistent match results at scale and want a single delivery organization to manage the end-to-end run lifecycle, including operational monitoring and change handling. A common usage situation is contact and firmographic enrichment for CRM refresh cycles that require repeatable processing windows and clear escalation paths.
- +Workflow orchestration supports repeatable batch enrichment runs
- +Integration-oriented delivery supports API and file-based handoffs
- +Operational monitoring and governance fit enterprise outsourcing needs
- +Automation focuses on multi-step enrichment workflows
- –Workflow governance can increase initial setup and orchestration time
- –Interactive enrichment depends on integration design and request patterns
- –Customization depth may require dedicated delivery cycles
- –Throughput outcomes rely on agreed operational run specs
Best for: Fits when enterprise teams need managed, orchestrated enrichment with controlled governance and monitoring.
EXL
enterprise_vendorOperations management and analytics company providing data enrichment services for enterprises.
Managed enrichment delivery that combines ingestion rules, normalization, and quality checks into repeatable outputs.
EXL is a fit for teams that treat enrichment as an operational pipeline with defined inputs, stable outputs, and measurable match performance. Delivery commonly includes enrichment execution over provided datasets and data normalization steps that support consistent attribute formats for CRM or downstream analytics. Governance tends to be handled through project scoping, documented transformation rules, and controlled release of enriched fields into target records.
A tradeoff is that custom configurations and mapping rules usually require upfront requirements work before enrichment quality stabilizes. EXL works well when enrichment must match business-defined identifiers, such as linking records to existing customer profiles, rather than running generic append-only enrichment.
- +Enterprise-ready enrichment execution for batch workloads and large input volumes
- +Operational delivery model supports managed requirements, mappings, and controlled outputs
- +Quality checks and normalization help keep enriched attributes consistent
- +Works well for linking enrichment back into existing account or customer records
- –Custom mappings usually require project scoping work before quality stabilizes
- –Real-time enrichment is not its primary fit compared with batch-oriented delivery
- –Admin-level self-serve controls are limited versus productized enrichment APIs
- –Turnaround depends on ingestion formats and transformation rule availability
Best for: Fits when data quality teams need managed, high-volume enrichment with controlled transformations.
Cogneesol
specialistBusiness process outsourcing company providing data enrichment and back-office data services.
Confidence-aware matching workflow that routes low-certainty records into separate handling rather than forcing merges.
Cogneesol delivers outsourced data enrichment for lead and account records, with workflow focus on matching external attributes onto existing datasets. The service is positioned around batch-style enrichment from uploaded files and follow-on review steps when match confidence is low.
Cogneesol also supports API enrichment for ongoing pipelines that need periodic refresh rather than one-time append. The practical differentiator is combining entity resolution style matching with operational controls that help manage merge outcomes at scale.
- +Batch file enrichment supports high-volume attribute append workflows
- +API enrichment supports scheduled refresh for pipeline-driven enrichment
- +Entity-style matching reduces duplicates during record completion
- +Operates with confidence-driven decisions for ambiguous matches
- –API onboarding depends on agreed data mapping and payload conventions
- –Real-time enrichment capabilities are not the primary emphasis
- –Results quality hinges on input normalization before submission
- –Governance artifacts like audit logs and RBAC are not clearly productized
Best for: Fits when teams need outsourced contact and firmographic enrichment with controlled batch workflows.
SunTec Data
specialistData support services company specializing in data enrichment, cleansing, and database management.
Job-based enrichment orchestration that couples attribute mapping with match-quality handling across batch refresh cycles.
SunTec Data provides outsourced data enrichment services focused on augmenting lead and account records with additional attributes from third-party sources. The differentiator is its integration-first delivery approach that supports file-based enrichment workflows and API enrichment for ongoing append and verification cycles.
Core capability includes batching, normalization, and attribute completion to improve match outcomes before records land in CRM, marketing automation, or downstream identity matching. Engagement fit typically centers on teams that need operational controls around enrichment runs, data mapping, and match quality management rather than one-off enrichment exports.
- +Supports both file-based enrichment and API enrichment workflows for different operational modes
- +Uses configurable enrichment run mapping to align appended attributes with target systems
- +Targets lead and account attribute completion to improve downstream match rates
- +Provides controlled enrichment processes designed for repeatable batch and refresh cycles
- –API enrichment needs clear input standards to avoid lower match outcomes
- –Deeper entity resolution workflows may require tighter specification than simple append-only use cases
- –Turnaround and throughput depend on source coverage and enrichment job design
- –Real-time enrichment expectations can be harder to meet for highly dynamic attribute sets
Best for: Fits when teams need outsourced enrichment with repeatable mappings and either file runs or API-driven updates.
Invensis
specialistBusiness process outsourcing firm offering data enrichment and data management services worldwide.
Human research plus structured attribute append, with repeatable rule-based extraction for list refreshes.
Invensis performs outsourced data enrichment by adding structured attributes to lead and account records using research workflows that support list-based delivery. Its operational model aligns with batch enrichment runs where teams define which attributes to capture and how outputs should be returned for downstream CRM ingestion. Integration depth is strongest for file or workflow handoffs rather than for real-time API enrichment, which limits event-driven automation.
- +Handles multi-step research and normalization in one enrichment workflow
- +Supports batch list enrichment for scheduled lead and account refresh cycles
- +Produces structured outputs that map to common CRM fields
- +Can follow team-defined attribute rules for consistent append behavior
- –Real-time API enrichment and event-driven updates are not the primary delivery shape
- –Governance controls like audit log, RBAC, and provisioning are not a clear focus
- –Throughput depends on batch turnarounds rather than continuous streaming
- –Identity resolution and record linkage logic need tight scope definitions
Best for: Fits when enrichment is run in batch cycles and output mapping to CRM fields matters most.
Conclusion
After evaluating 10 data science analytics, Flatworld Solutions 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 outsource data enrichment
Outsourced data enrichment assigns contact, account, and firmographic enrichment work to third-party providers that run batch cycles or API-driven jobs and then deliver mapped outputs for CRM or marketing systems. This buyer’s guide covers Flatworld Solutions, TaskUs, WNS, Genpact, Concentrix, Infosys BPM, EXL, Cogneesol, SunTec Data, and Invensis.
The main selection differences show up in how providers operationalize enrichment runs. Flatworld Solutions centers client-driven enrichment provisioning that locks field mappings into repeatable batch execution cycles. WNS and Genpact focus on managed entity resolution and linkage to control duplicate risk before enriched attributes land in downstream records.
Outsource data enrichment: managed batch and API enrichment that delivers mapped attributes and controlled entity linkage
Outsource data enrichment is the practice of sending identifiers like leads, accounts, or domains to a provider, having the provider append missing attributes, and returning outputs in a format ready for CRM and downstream routing. The category commonly uses batch enrichment runs and file handoffs, and some providers also support API enrichment workflows for scheduled refresh.
Flatworld Solutions emphasizes repeatable batch enrichment provisioning by locking field mappings into repeatable execution cycles for consistent CRM and marketing updates. WNS and Genpact add managed entity resolution and linkage runs that pair matching rules with QA remediation or output standardization to reduce duplicate lead and account records.
Outsource data enrichment capabilities that determine match quality and operational fit
Outsourced enrichment succeeds when providers turn input identifiers into mapped attributes using repeatable run configurations that feed CRM or downstream routing with predictable outputs. Batch delivery and managed entity resolution both influence match rate, coverage rate, and the fraction of records that require remediation.
These capabilities show up most clearly in how providers lock field mappings into repeatable execution cycles, how they run matching and QA remediation loops, and how they package enrichment outputs for direct system ingestion. Flatworld Solutions, WNS, and Genpact illustrate three distinct operational patterns that affect throughput, governance effort, and integration work.
Field mapping control for repeatable batch runs
Flatworld Solutions builds client-driven enrichment provisioning that locks field mappings into repeatable execution cycles for batch loads, which reduces drift between runs. TaskUs uses configurable workflow steps for recurring batch delivery and quality review loops that still emphasize managed delivery rather than self-serve mapping control.
Managed entity resolution and linkage with QA remediation loops
WNS runs program-managed entity resolution that pairs matching rules with QA remediation loops across batch enrichment cycles to stabilize entity linking. Genpact pairs managed entity resolution and linkage operations with enrichment output standardization to reduce duplicate lead and account records.
Workflow orchestration that connects input, enrichment steps, and run control
Infosys BPM ties input, enrichment steps, and operational run control into one delivery lifecycle using workflow orchestration for repeatable batch runs. EXL combines ingestion rules, normalization, and quality checks into repeatable outputs, which supports controlled transformations at scale for batch workloads.
Batch-focused matching controls for CRM-ready append outputs
Concentrix centers managed enrichment delivery on match quality controls for batch record append feeding CRM and downstream routing. SunTec Data couples attribute mapping with match-quality handling across batch refresh cycles using configurable enrichment run mapping to align appended attributes with target systems.
Confidence-aware handling to avoid forced merges
Cogneesol routes low-certainty records into separate handling through a confidence-aware matching workflow instead of forcing merges. WNS also focuses on entity resolution and QA remediation but is positioned around managed entity resolution runs rather than confidence-tiered routing.
How to choose an outsource data enrichment provider by run model, matching control, and integration surface
Outsource data enrichment buying decisions should start with the operational run model instead of the data types named in proposals. Flatworld Solutions optimizes for client-driven mapping control in repeatable batch cycles, while WNS and Genpact optimize for managed entity resolution and linkage to reduce duplicate records before enriched attributes land.
The second fork is whether enrichment needs to be primarily batch-file driven or supported through API enrichment workflows with request patterns that match downstream scheduling. SunTec Data and Cogneesol support API enrichment as a scheduled refresh mode, while Flatworld Solutions and TaskUs emphasize batch workflows and managed delivery paths more than API-first execution.
Pick the run model that matches the team’s operating rhythm
Choose Flatworld Solutions when enrichment work runs on scheduled batch loads and CRM field mappings must remain stable across repeated executions. Choose TaskUs when the organization needs managed, recurring enrichment delivery with configurable workflow steps and quality review loops built around batch CRM updates.
Decide whether duplicate risk must be handled inside the enrichment vendor
Choose WNS when managed entity resolution should pair matching rules with QA remediation loops across batch enrichment cycles to stabilize entity linking. Choose Genpact when managed entity resolution and linkage should also standardize enrichment outputs for CRM-grade data.
Evaluate orchestration depth when enrichment spans multiple steps and handoffs
Choose Infosys BPM when enrichment execution needs workflow orchestration that ties input, enrichment steps, and operational run control into one delivery lifecycle with monitoring. Choose EXL when ingestion rules, normalization, and quality checks must be packaged into repeatable outputs for large batch input volumes.
Match integration shape to how each provider handles API enrichment maturity
Choose SunTec Data when file-based enrichment and API enrichment workflows both matter and enrichment run mapping must align appended attributes with target systems. Choose Cogneesol when API onboarding can align with agreed payload conventions and confidence-tiered handling must prevent forced merges.
Set governance expectations for mapping, identity resolution, and auditability
Choose Flatworld Solutions when mapping control and repeatable batch provisioning are the governance lever, with governance and identity resolution requiring more upfront configuration discipline. Choose Infosys BPM when governance and monitoring need tighter operational run control, while interactive enrichment still depends on the integration design and request patterns.
Who benefits from outsource data enrichment providers built for managed batch delivery or managed entity resolution
Teams should use outsourced enrichment when they need external execution capacity for batch enrichment cycles and when internal data engineers cannot run the operational workflow at the required throughput. Provider selection matters most for organizations with duplicate-risk concerns and for organizations that must keep CRM field mapping consistent.
The best fit depends on whether enrichment is primarily batch-file oriented, whether entity resolution should happen inside the vendor, and whether confidence handling must separate low-certainty matches from high-certainty merges.
CRM and marketing ops teams running scheduled lead and account refresh
Flatworld Solutions is a strong fit when repeated batch enrichment runs must keep field mappings stable for CRM and marketing updates. SunTec Data also fits when scheduled refresh needs either file runs or API-driven updates with run mapping aligned to target systems.
Data quality teams focused on duplicate reduction and stable entity linking
WNS fits when entity resolution should be managed with matching rules and QA remediation loops across batch enrichment cycles. Genpact fits when managed entity resolution and linkage must also standardize enrichment outputs to reduce duplicate lead and account records.
Enterprise teams that need enrichment workflow orchestration and monitoring
Infosys BPM fits when input, enrichment steps, and operational run control must be orchestrated into a single delivery lifecycle with controlled governance. EXL fits when ingestion rules, normalization, and quality checks need to be packaged into repeatable outputs for batch scale.
Teams that require low-certainty record handling instead of forced merges
Cogneesol fits when confidence-aware matching must route low-certainty records into separate handling to avoid forced merges. This requirement is handled differently from WNS where the emphasis is managed entity resolution runs with QA remediation loops.
Common outsource data enrichment pitfalls that create low match quality or unusable outputs
Most enrichment failures come from mismatched operating assumptions between the customer’s input standards and the vendor’s enrichment workflow. The next failures come from under-scoping mapping and governance work, especially when entity resolution and identity linkage are expected to work without upfront specification.
The provider cards show where these issues concentrate. Flatworld Solutions emphasizes mapping stability with upfront configuration discipline, while WNS and Genpact place more weight on matching rules and operational runs that require migration mapping and integration coordination.
Assuming API enrichment will work as a drop-in path without aligning payload conventions and input standards
Cogneesol flags that API onboarding depends on agreed data mapping and payload conventions, so mismatch in inputs lowers confidence handling outcomes. SunTec Data also notes that API enrichment needs clear input standards to avoid lower match outcomes.
Treating entity resolution as a generic add-on instead of a workflow with matching rules and remediation steps
WNS is built around program-managed entity resolution that pairs matching rules with QA remediation loops, so entity resolution needs defined matching logic. Genpact also pairs entity resolution and linkage with output standardization, so enrichment outputs must be aligned to the target data model before execution.
Under-scoping mapping governance work for repeatable batch execution cycles
Flatworld Solutions locks field mappings into repeatable execution cycles, but governance and identity resolution require more upfront configuration discipline. Infosys BPM ties workflow orchestration into a delivery lifecycle, and workflow governance increases initial setup and orchestration time.
Expecting real-time enrichment depth when the provider is primarily batch-oriented
Concentrix states that real-time enrichment integration is not its strongest documented path, so plan around batch append and CRM ingestion cycles. EXL also positions real-time enrichment as not its primary fit compared with batch-oriented delivery.
How We Selected and Ranked These Providers
We evaluated Flatworld Solutions, TaskUs, WNS, Genpact, Concentrix, Infosys BPM, EXL, Cogneesol, SunTec Data, and Invensis on enrichment delivery mechanics, run repeatability, and how outputs map into CRM-ready workflows. Features accounted for 40% of the score by weighting repeatable batch execution cycles, managed entity resolution runs, and workflow orchestration that ties enrichment steps to run control.
Ease and value each accounted for 30% by measuring how directly each provider’s managed delivery model supports recurring batch enrichment, including mapping clarity and operational handling. Flatworld Solutions earned the top position because client-driven enrichment provisioning locks field mappings into repeatable execution cycles for consistent batch loads, which gives strong control over enrichment output structure for downstream systems.
Frequently Asked Questions About outsource data enrichment
How do outsourced enrichment services handle API enrichment and file-based enrichment, and which providers support both?
What data model and schema controls are used to keep enriched attributes consistent across runs?
How do providers support SSO and access security for enrichment operations?
What onboarding steps are required for data migration when moving historical lead or account datasets into an outsourced enrichment workflow?
Which providers use entity resolution workflows to reduce duplicates, and how do they handle low-confidence matches?
What admin controls exist for changing enrichment rules without breaking existing CRM loads?
What throughput and turnaround tradeoffs arise between high-volume batch enrichment and near-real-time enrichment?
When does contact and firmographic enrichment delivery require human review steps rather than fully automated processing?
Where does outsourced enrichment fail if integration requirements and output routing are underspecified?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
- Data Science AnalyticsTop 10 Best Data Enrichment Services of 2026
- Data Science AnalyticsTop 10 Best Outsource Data Extraction Services of 2026
- Data Science AnalyticsTop 10 Best Ecommerce Product Data Enrichment Services of 2026
- Data Science AnalyticsTop 10 Best Data Enrichment Software of 2026
- Business Process OutsourcingTop 10 Best Outsource Software of 2026
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