Start with the business problem, then see which of NQRust Hypervisor, NQRust Backup and Restore, and NQRust Storage leads the solution and which platforms provide validated support.
Each path stays within the capabilities and validation boundaries of the three platforms currently available.
Primary: NQRust Hypervisor
Virtualization & Infrastructure Modernization
Organizations need a practical path away from aging or restrictive virtualization platforms while continuing to run the Windows and Linux virtual machines their operations depend on.
A validated modernization roadmapGreater control over infrastructure technology choicesMore consistent API-driven virtual machine operations
Completed backup jobs do not guarantee recovery. Teams must be able to identify what is protected, find the required version, understand where it is stored, control who can restore it, and prove that recovery works.
Searchable recovery points and file versionsA clearer path to precise recoveryReduced data-loss and downtime exposure
Storage capacity, data services, access controls, and day-two operational context are often managed through separate paths, leaving teams with fragmented workflows and unclear protection boundaries.
A clearer private-storage operating modelMore consistent service and access boundariesBetter operational context for day-two decisions
Recurring licensing pressure, closed platform dependencies, and fragmented infrastructure tools can limit technology choice and make modernization harder to plan.
A clearer current-to-target cost modelReduced platform dependency where NQRust is adoptedGreater control over infrastructure choices
Government institutions, state-owned enterprises, regulated organizations, and strategic industries need greater control over platform architecture, data placement, access boundaries, recovery procedures, and long-term vendor dependency.
Greater control over infrastructure and data placementClearer ownership of access and recovery responsibilitiesReduced reliance on restrictive platform stacks
AI initiatives are difficult to scale when compute capacity, data-access patterns, infrastructure lifecycle, and recovery requirements have not been validated for representative workloads.
Documented infrastructure-readiness gapsValidated capacity, access, and protection assumptionsA phased proof-of-concept plan for a representative workload