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Gambling LotteriesTop 9 Best Keno Software of 2026
Top 10 Keno Software ranking for compliance and testing teams, comparing iTech Labs, BMM Testlabs, and Keno Edge on key requirements.
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
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
iTech Labs
RBAC plus audit log links configuration changes to executed runs for Keno workflow traceability in test and compliance evidence.
Built for fits when compliance and testing teams need API automation, RBAC governance, and audit-grade traceability for Keno workflows..
BMM Testlabs
Editor pickGoverned test asset lifecycle with RBAC and audit-oriented execution traceability across Keno test configurations.
Built for fits when compliance teams need traceable Keno testing with API automation and governed test assets..
Keno Edge
Editor pickSchema-driven provisioning and configuration APIs that keep event and results formats consistent across test environments.
Built for fits when compliance and testing teams need schema-consistent integrations with API-driven automation and RBAC governance..
Related reading
Comparison Table
This comparison table maps GLI Compliance, iTech Labs, BMM Testlabs, Keno Edge, LotteryHub, and other Keno Software tools across integration depth, data model design, and the automation plus API surface used for provisioning and extensibility. It also flags admin and governance controls such as RBAC scope, configuration boundaries, and audit log coverage so compliance and testing teams can assess throughput and change control without guesswork.
iTech Labs
compliance testingOffers regulated gambling testing and compliance services with test reports and evidence packages used to verify Keno systems against applicable GLI and jurisdictional requirements.
RBAC plus audit log links configuration changes to executed runs for Keno workflow traceability in test and compliance evidence.
iTech Labs supports a structured data model for Keno workflows, including event definitions, run state tracking, and operational metadata tied to each configuration and execution. The automation surface is designed around API-accessible provisioning and workflow triggers, which helps teams move from manual QA to scripted verification. Audit logging and RBAC controls provide traceability for configuration changes and user actions, which aligns with compliance test evidence needs.
A key tradeoff is that deeper configuration and schema control requires discipline in managing environments and test datasets to preserve deterministic outcomes. iTech Labs fits best when compliance and testing teams need throughput for repeated verification runs and want governance controls that keep audits tied to specific releases.
- +API-first automation for repeatable Keno workflow runs
- +Schema-driven data model for consistent event and state tracking
- +RBAC and audit log support compliance-grade change evidence
- +Environment provisioning supports controlled testing and release cycles
- –Schema and environment management needs tighter operational discipline
- –Complex workflow setups can increase setup time for new test squads
- –Extensibility depends on well-defined event and workflow contracts
GLI compliance testers
Run scripted Keno verification suites
Audit-ready traceability per run
Test automation engineers
Provision sandbox environments programmatically
Consistent regression throughput
Show 2 more scenarios
Operations governance leads
Control changes with RBAC
Reduced unauthorized configuration risk
RBAC limits access to configuration and workflow triggers while audit log records every change.
Release coordinators
Coordinate schema-controlled deployments
Fewer release-time inconsistencies
Schema versioning helps coordinate rollout steps with deterministic event processing for Keno.
Best for: Fits when compliance and testing teams need API automation, RBAC governance, and audit-grade traceability for Keno workflows.
BMM Testlabs
compliance testingDelivers regulated gaming testing programs with structured test documentation for Keno applications built to satisfy audit and certification workflows.
Governed test asset lifecycle with RBAC and audit-oriented execution traceability across Keno test configurations.
BMM Testlabs fits teams that need repeatable Keno software testing tied to evidence. The data model supports defining test cases, expected outcomes, and run metadata so results can be compared across executions. API and automation features are geared toward provisioning test environments, triggering runs, and exporting results for downstream reporting.
A tradeoff shows up in setup effort for custom schemas and integration paths because governance and data consistency come before speed. It works well when a compliance program requires traceability from test configuration through execution logs to sign-off artifacts. Teams with highly bespoke Keno rulesets benefit from configuration-driven scenarios that reduce ad hoc manual steps.
- +Test data model keeps scenarios, expectations, and results consistently mapped
- +API surface supports automation for provisioning, run triggering, and results export
- +RBAC and governance controls reduce uncontrolled edits to test assets
- +Audit-oriented change tracking supports evidence retention for compliance reviews
- –Custom schema integration can require more initial configuration work
- –Throughput depends on run orchestration design and environment capacity
Compliance test leads
Trace test evidence for Keno releases
Cleaner sign-off evidence packages
QA automation engineers
Trigger Keno test runs via API
Fewer manual test handoffs
Show 1 more scenario
Platform integration teams
Sync test configuration and results
Faster evidence-to-report turnaround
Integrate configuration, run status, and results into reporting pipelines through APIs.
Best for: Fits when compliance teams need traceable Keno testing with API automation and governed test assets.
Keno Edge
keno managementProvides a rules and game configuration focused Keno delivery toolset with operational controls for Keno variants and schedule management workflows.
Schema-driven provisioning and configuration APIs that keep event and results formats consistent across test environments.
Keno Edge is a strong fit for compliance and testing teams that need a clearly defined data model for fixtures, rules, and results handling across environments. Automation supports repeatable configuration changes and workload routing without manual intervention on each test run. The API surface is designed for provisioning and controlled updates so integration projects can run through repeatable steps.
A tradeoff appears in schema rigidity when connected systems expect different event shapes or field naming conventions. Teams gain the most when upstream and downstream schemas can be mapped once, then reused for high-throughput regression runs. A common usage situation is a QA lab that runs scripted test cases and needs deterministic outputs for audit-ready evidence trails.
- +Structured data model aligned to Keno workflows for repeatable test evidence
- +API supports provisioning and configuration updates for automated test runs
- +RBAC-style governance with permission boundaries for operational safety
- +Extensibility via schema mapping to connect results and event streams
- –Schema mapping can require upfront alignment work for mismatched event shapes
- –Automation changes may need coordinated releases across integrated systems
Compliance QA teams
Run audit-ready regression evidence
Consistent, reviewable evidence artifacts
Systems integration engineers
Connect Keno data to internal services
Lower integration drift risk
Show 2 more scenarios
Test operations leads
Coordinate multi-environment test schedules
Fewer configuration mistakes
Use RBAC governance to restrict access while automation triggers repeatable environment configurations.
Automation scripting teams
Drive high-volume Keno simulations
Faster regression cycles
Schema-aligned event routing supports high-throughput runs with predictable result structures.
Best for: Fits when compliance and testing teams need schema-consistent integrations with API-driven automation and RBAC governance.
Keno Software
game platformSupplies configurable Keno game systems for regulated operators with settings governing draws, odds mapping, and deployment artifacts for integration.
Audit log plus RBAC for traceable rule and schedule changes across environments
Keno Software supports Keno workflow management with an emphasis on automation-ready configuration and controlled execution. The product’s integration depth is driven by an explicit API surface for provisioning entities, pushing configuration changes, and syncing data between systems.
Its data model centers on schemas for game rules, schedules, and operational events, which helps keep test and compliance artifacts consistent across environments. Admin and governance controls focus on RBAC, audit log coverage, and change traceability for operations and configuration updates.
- +API-based provisioning for schedules, rules, and operational entities
- +Schema-driven data model keeps test artifacts consistent across environments
- +RBAC controls separate operator, reviewer, and administrator permissions
- +Audit logs record configuration changes and operational decisions
- –Automation depth depends on consistent schema mapping to external systems
- –Complex workflow changes can require careful versioning of configurations
- –Throughput under peak loads needs validation for high-volume event syncing
Best for: Fits when compliance and testing teams need API-driven automation, governed RBAC, and auditable configuration changes.
LotteryHub
data hubCentralizes lottery and Keno metadata and operational controls with schema driven configuration flows for draw events and reporting exports.
Audit-ready draw and ticket state schema that preserves configuration provenance for compliance reviews.
LotteryHub supports Keno lottery operations with configurable game rules, ticket generation, and results processing workflows. The product centers on an auditable data model for draws, games, and customer-facing ticket states, which matters for compliance evidence trails.
LotteryHub also provides integration paths for upstream suppliers and downstream channels through an automation and API surface aimed at repeatable provisioning. Administrative governance features cover user access control and operational monitoring to support controlled release of configuration changes.
- +Configuration-driven keno rules reduce manual changes during draw cycles
- +Documented automation paths support repeatable provisioning of game settings
- +Audit-friendly draw and ticket state model helps compliance evidence capture
- +RBAC controls limit who can modify operational configuration
- –Automation and API depth require mapping an internal data schema to its model
- –High-throughput draw windows can stress integration coordination and throttling
- –Governance workflows may need extra process tooling for multi-team approvals
- –Sandbox-like test environments may not mirror production validation rules
Best for: Fits when compliance and testing teams need controlled keno configuration changes, auditable state, and API-based automation.
BettingOps
operator opsProvides operational tooling for betting and lottery launches with administrative controls for Keno configurations and environment promotion workflows.
API-driven provisioning with audit logging that ties configuration edits to runtime event and market behavior.
BettingOps fits teams that need disciplined betting workflow automation around Keno software controls, not ad hoc spreadsheets. The data model centers on event, game, and market objects with configuration-driven rules that map cleanly into provisioning workflows.
Integration depth is expressed through an API-first automation surface that supports validation, schema-aligned payloads, and consistent throughput between operations and systems. Admin and governance controls can be structured around RBAC and audit logging so compliance and testing teams can trace configuration changes to runtime effects.
- +API-first automation supports schema-aligned provisioning and validation
- +Configuration-driven workflows reduce manual operator variance
- +Audit-ready change trails help compliance teams trace config impacts
- +RBAC model supports separation between ops, QA, and governance roles
- –Deep customization depends on schema and workflow configuration discipline
- –High-volume updates require careful rate and throughput management
- –Testing requires dedicated sandbox data and repeatable environment setup
- –Complex market mappings can increase implementation effort upfront
Best for: Fits when compliance and testing teams need API-driven Keno provisioning with RBAC and traceable configuration changes.
Jira Software
traceabilitySupports project configuration, workflow automation, and audit-ready histories for requirement-to-test traceability using issue schemas, custom fields, and API-driven integration pipelines.
Workflow Designer with conditions, validators, and post-functions backed by REST API and automation triggers.
Jira Software from Atlassian differentiates with a highly explicit workflow data model and a mature automation and API surface. Issue types, fields, screens, and transitions form a configurable schema that supports granular process modeling across teams.
Jira automation rules integrate with webhooks, REST APIs, and marketplace apps, enabling event-driven updates and controlled throughput for change-heavy programs. Admin controls cover RBAC via project permissions and granular governance options like audit logging and scheme management for consistent deployments.
- +Workflow schema uses screens, transitions, and issue fields with clear governance
- +REST API supports automation, provisioning, and bulk operations on issues and schemes
- +Webhook and automation triggers support event-driven synchronization across systems
- +RBAC via project permissions and groups supports controlled access boundaries
- +Audit log captures administrative and workflow changes for traceability
- +Extensibility via Connect and Forge enables custom UI and business logic
- –Complex schemes increase configuration risk without strong change management
- –Automation rules can become hard to reason about without strict naming standards
- –Cross-project reporting depends on consistent fields and taxonomy discipline
- –Large instances can require careful indexing and workflow design to maintain throughput
- –Workflow transition conditions and validators can be difficult to test at scale
Best for: Fits when compliance and testing teams need workflow control with API-driven integration and auditable governance.
Confluence
documentationHosts spec, test plans, and evidence as structured pages with permissions, page-level history, and automation via APIs for linking requirements to certification evidence.
Audit log plus granular space permissions that record access and configuration changes for compliance evidence.
Confluence from Atlassian is built around a page-based data model with linked content, labels, and permissions. It supports deep integration with Jira and other Atlassian products through documented APIs and automation rules, which helps compliance and testing teams coordinate evidence, requirements, and defect tracking.
Admin and governance features include granular space permissions, role-based access control through Atlassian identity, and audit-log visibility for key actions. Automation and extensibility include REST APIs, webhooks, and Connect or Forge app interfaces for controlled workflows and schema-adjacent indexing needs.
- +Tight Jira integration maps work items to evidence pages
- +REST API supports programmatic page, permission, and attachment management
- +Webhooks notify external systems on content and workflow events
- +Space-level permissions provide enforceable RBAC boundaries
- +Audit log covers configuration and content access changes
- –Page-centric data model makes cross-entity schema validation harder
- –Automation rules can require careful governance to avoid workflow drift
- –Bulk content operations can stress throughput and indexing latency
- –Some admin changes require workspace restarts or staged rollout planning
Best for: Fits when compliance and testing teams need auditable documentation flows tied to Jira and external systems.
Test Management
work trackingUses Azure DevOps test plans to structure test suites, run results, and work item traceability with role-based access and audit history for regulated delivery workflows.
Azure DevOps work item schema for tests and execution results, governed by project RBAC and exposed through automation APIs.
Test Management on azure.microsoft.com provides test case management and test execution tracking with tight integration into Azure DevOps. It maps tests, runs, results, and defects to a structured data model and supports configuration through Azure DevOps project settings and work item types.
Automation and extensibility come from Azure DevOps services APIs that can create, query, and update test artifacts and execution records. Admin controls rely on Azure DevOps RBAC and audit capabilities to govern access to test artifacts and execution history.
- +Azure DevOps integration keeps tests, runs, and defects in one work item model
- +Azure DevOps APIs support automation for test artifacts and execution result ingestion
- +RBAC restricts who can view and modify test plans, suites, and execution records
- +Audit visibility covers key changes to test-related artifacts in project context
- –Automation requires Azure DevOps API workflows and schema awareness of work item types
- –Test planning and execution tooling is bounded by Azure DevOps process configuration
- –Cross-project reporting depends on Azure DevOps data access patterns and permissions
- –Complex customizations often require coordinated work item type configuration and tooling
Best for: Fits when teams already run test planning and execution inside Azure DevOps need API-driven traceability and governance.
Frequently Asked Questions About Keno Software
How do GLI Compliance teams validate Keno rule and schedule changes with audit-grade traceability?
Which Keno tool provides a schema-first data model for Keno events and operational outcomes?
What API surfaces support automated provisioning and configuration changes for Keno workflows?
Which option best supports RBAC governance and audit logging across Keno test environments?
How do teams migrate existing Keno test assets or data models into a new system?
What integrations matter most for compliance test coordination and evidence workflows?
How do these tools handle environment provisioning for repeatable Keno runs?
Which platform is better when Keno integrations must preserve event and results formats across systems?
What common failure points occur in Keno automation, and how do the tools mitigate them?
How do teams integrate Keno test execution with broader test planning and execution systems?
Conclusion
After evaluating 9 gambling lotteries, iTech Labs 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.
How to Choose the Right Keno Software
This buyer’s guide covers Keno Software tools used for regulated Keno operations and compliance testing workflows. It compares iTech Labs, BMM Testlabs, Keno Edge, Keno Software, LotteryHub, BettingOps, Jira Software, Confluence, and Test Management inside Azure DevOps.
The focus is integration depth, data model fit, automation and API surface, and admin and governance controls. Each section maps evaluation criteria to concrete mechanisms like RBAC, audit logs, schema contracts, and environment provisioning.
Keno Software for governed game configuration, event data, and auditable testing runs
Keno Software covers systems that configure Keno rules and schedules, generate and process draw or game events, and move those event and result records between operational and test environments.
In regulated programs, these tools solve traceability problems by coupling configuration changes to executed runs and evidence packages. Tools like iTech Labs and Keno Software model game rules and operational events with schemas and expose API-driven provisioning for repeatable compliance and testing cycles.
Evaluation criteria for Keno integration, schema control, and compliance-grade governance
Integration depth determines whether configuration and event data can move through controlled pipelines instead of manual exports. That matters most when compliance teams need repeatable runs, evidence retention, and deterministic mapping between configuration and outcomes.
Data model design governs how well schemas align across systems and how reliably audit trails can reconstruct what changed. Automation and API surface decides whether orchestration can scale during test cycles and draw windows without fragile operator steps.
API-driven provisioning and configuration sync
Tools like iTech Labs, BMM Testlabs, and Keno Software expose API surfaces for provisioning environments and pushing configuration changes. This supports repeatable test workflows and governed release cycles where schedules, rules, and operational entities move programmatically.
Schema-driven event and state modeling
Keno Edge and Keno Software emphasize schema-driven data models that keep event and results formats consistent across environments. LotteryHub pairs an audit-ready draw and ticket state schema with configuration provenance so compliance teams can trace state transitions back to rule settings.
RBAC governance tied to executed runs
iTech Labs and BMM Testlabs combine RBAC with audit logging to restrict who can change Keno workflow artifacts. iTech Labs links configuration changes to executed runs for evidence-grade traceability, while BMM Testlabs ties changes to a governed test asset lifecycle.
Audit log coverage for configuration and access changes
Keno Software and iTech Labs use audit logs to record configuration changes and operational decisions across environments. Confluence also provides audit-log visibility for key actions and pairs it with granular space permissions, which helps teams keep evidence access and edits attributable.
Environment provisioning for controlled test and release cycles
iTech Labs and Keno Software support environment provisioning so controlled testing can mirror the release path. BettingOps also targets disciplined automation and environment promotion workflows that reduce operator variance across ops, QA, and governance roles.
Automation and extensibility surface for orchestration
Jira Software and Confluence provide mature REST APIs and automation triggers that integrate evidence and workflow steps into an API-driven pipeline. For teams that already standardize orchestration in tooling like Jira, these integrations can connect requirement-to-test traceability with Keno evidence artifacts.
Pick the Keno tool that matches the integration contract and governance depth
Selection should start with the integration contract needed for the Keno program. If API-driven provisioning and schema-consistent event exchange are required, iTech Labs, BMM Testlabs, and Keno Edge align directly with that model.
Next evaluate governance depth for compliance testing. RBAC plus audit logs that link changes to executed runs matters more than generic access control, because evidence packages depend on reconstructing who changed what and when it impacted results.
Map the integration endpoints that must be automated
List which entities need API automation such as schedules, rules, environment provisioning, results export, and configuration updates. iTech Labs and BMM Testlabs are built around API-driven run triggering and results export tied to governed test assets, while Keno Software focuses on API-based provisioning for schedules, rules, and operational entities.
Validate data model fit for your Keno event and state records
Confirm whether the tool uses schema-driven models that match the event shapes and state transitions used by upstream and downstream systems. Keno Edge and Keno Software emphasize schema alignment for consistent event and results formats, while LotteryHub uses an audit-ready draw and ticket state schema that preserves configuration provenance.
Check governance mechanisms for change traceability
Require RBAC plus audit log coverage that connects configuration edits to executed runs or test configurations. iTech Labs links configuration changes to executed runs, while BMM Testlabs provides governed test asset lifecycle with RBAC and audit-oriented execution traceability.
Plan for environment promotion and throughput constraints
Define how test squads and operators promote configuration across environments and how the system handles high-volume updates. iTech Labs supports controlled environment provisioning, and BettingOps includes API-driven provisioning and audit logging designed to tie configuration edits to runtime event and market behavior, but high-volume updates still require throughput planning.
Choose evidence and workflow coordination tooling based on existing systems
If requirement-to-test traceability and workflow governance already run through Jira, Jira Software and Confluence can coordinate evidence pages and access control using REST APIs, webhooks, and audit logs. If teams run test execution inside Azure DevOps, Test Management connects test case and execution records to Azure DevOps RBAC and automation APIs.
Who benefits from Keno Software built for regulated automation and evidence control
Keno programs that must certify or demonstrate compliance need tooling that couples configuration changes to test execution and evidence artifacts. These needs show up across regulated Keno testing teams, governed QA pipelines, and compliance documentation workflows.
The strongest fit depends on whether the organization already standardizes orchestration and evidence in Jira or Azure DevOps, or whether the primary requirement is a Keno-native API and schema contract.
Compliance and testing teams that require API automation plus audit-grade run evidence
iTech Labs fits teams that need RBAC and audit log linkage between configuration changes and executed Keno workflow runs. Keno Software also targets auditable rule and schedule changes with RBAC and audit logs, but iTech Labs is positioned for repeatable compliance-grade evidence packages.
Compliance teams that manage governed test assets and requirement mapping to scenarios
BMM Testlabs fits teams that need traceable Keno testing where scenarios, expectations, and results map through a structured test data model. It adds RBAC and audit-oriented execution traceability across Keno test configurations, which matches certification and evidence retention workflows.
Engineering teams needing schema-consistent Keno integrations across connected systems
Keno Edge is a strong match when integration pipelines must keep event and results formats consistent using schema-driven provisioning and configuration APIs. Keno Software can also work when teams require schema-driven rules and schedules paired with RBAC and audit logs.
Teams already running traceability and approvals in Jira or Azure DevOps ecosystems
Jira Software fits compliance and testing teams that want workflow control with REST APIs, automation triggers, and audit-ready histories using configured issue schemas. Test Management fits when test planning and execution already live in Azure DevOps and automation must create and update test artifacts through Azure DevOps services APIs.
Operations and QA teams managing draw and ticket state with auditable configuration provenance
LotteryHub fits when governed Keno configuration changes must preserve an auditable draw and ticket state schema for compliance evidence trails. BettingOps fits when API-driven provisioning and audit logging must tie configuration edits to runtime event and market behavior while promoting disciplined workflows across ops and QA roles.
Common failure modes when selecting Keno Software for regulated automation
Several pitfalls repeat across Keno tooling choices when integration and governance are not validated early. Data schema mismatch and under-scoped governance are the two most common reasons testing workflows become hard to certify.
Automation that depends on fragile manual steps also breaks repeatability during peak draw cycles, because throughput constraints and orchestration design determine whether runs stay deterministic.
Choosing a tool without confirming schema alignment for event and results records
Keno Edge and Keno Software focus on schema-driven provisioning and configuration APIs that keep event and results formats consistent across environments. LotteryHub uses an audit-ready draw and ticket state schema, while Keno Software also depends on consistent schema mapping to external systems, so mismatches must be addressed before automation goes live.
Relying on basic RBAC without audit log linkage to executed runs or test configurations
iTech Labs and BMM Testlabs connect governance to evidence by linking configuration changes to executed runs or by tracing results through a governed test asset lifecycle. Tools like Keno Software also provide audit logs plus RBAC, but teams should verify that the audit trail can reconstruct which change impacted which executed run.
Underestimating operational discipline needed for workflow setup and environment management
iTech Labs notes that schema and environment management needs tighter operational discipline, and complex workflow setups can increase setup time for new test squads. BettingOps also requires careful rate and throughput management for high-volume updates, so environment promotion and orchestration design must be validated early.
Using document-only evidence tools as a substitute for executable traceability
Confluence provides auditable documentation flows with audit logs and granular space permissions, but it is page-centric and makes cross-entity schema validation harder. Jira Software can model workflows with REST-backed automation triggers, but Keno data exchange and run execution still require Keno-native provisioning and schema control from tools like Keno Software, Keno Edge, or iTech Labs.
Confusing task management with Keno run ingestion and test execution data model requirements
Test Management inside Azure DevOps governs test plans and execution results using the Azure DevOps work item schema, which is strong for teams already inside that platform. For Keno-specific event and state models, iTech Labs, BMM Testlabs, Keno Software, or LotteryHub provide Keno schemas and provisioning APIs that better match regulated Keno evidence needs.
How We Evaluated and Ranked These Keno Software Tools
We evaluated iTech Labs, BMM Testlabs, Keno Edge, Keno Software, LotteryHub, BettingOps, Jira Software, Confluence, and Test Management using feature coverage, ease of use, and value as scored criteria, with features carrying the largest impact. Ease of use and value each influenced the totals strongly because compliance and testing teams need automation that runs reliably under real process constraints.
We ranked the top outcomes by how directly each tool supports integration depth, schema control, automation and API surface, and admin governance mechanisms like RBAC and audit log traceability. iTech Labs separated itself from the lower-ranked options by linking RBAC-controlled configuration changes to executed Keno workflow runs using audit log evidence, which raised its features factor and supports audit-grade traceability for compliance testing cycles.
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