Data classification determines which controls are required.

Public-sector and defense technology services cover architectures where data classification, mission continuity, supply chain, and authority boundaries precede technology selection. Sanal Çekirdek sets the control level by workload and designs private deployment and open-model options together with operating responsibility.

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Data classification and sovereign infrastructure

Workloads are separated according to data class, access authority, location, connectivity and mission impact. Management planes, keys, logging and supplier access are designed for the required level of control.

On-premises or private-cloud options
Segregated network and security zones
Customer-controlled access and keys
Auditable administration and change

Zero Trust and cyber resilience

Identity, device, network and workload trust are verified for each access request, with permissions limited to mission need. Incident response and trusted recovery are planned around critical-service dependencies.

Identity and privileged access
Microsegmentation and secure exchange
SOC visibility and response
Cyber recovery and exercises

Private and governed AI

RAG systems and task agents that use organizational knowledge are designed with data-flow control, attribution, permissions, logging and human approval. Model deployment is selected according to data and mission sensitivity.

Private model deployment
Permission-aware retrieval
CPT/SFT and data usage rights
Approval and logging for agent actions

Critical public services and integration

Continuity for citizen, workforce and field services is addressed across identity, applications, data, networking and inter-agency integration. Modernization can proceed incrementally around existing systems.

Digital service and identity integration
APIs and inter-agency data flows
Legacy modernization
Capacity, DR and service monitoring

How we work

Establish data classes and applicable regulation together
Define on-premises, private cloud and enclave boundaries
Design identity, privileged access and segmentation
Pilot one service with its audit trail already in place
Extend in stages, including inter-agency flows

How success is measured

Critical-service and mission availability
Authorized access, privilege and logging coverage
Recovery exercises and dependency variance
AI answer/action quality and human approval

Frequently asked questions

Can AI run in an isolated network?

With suitable models, hardware, update methods and data flows, offline or restricted-connectivity deployment is possible. Model supply, patching, evaluation and ongoing service require separate planning.

Are open models inherently more secure?

No. Access to code or weights may improve control and inspection, but deployment, dependencies, vulnerabilities, data and day-to-day running still need to be managed.

Does this page cover the full scope for defense projects?

No. It describes a general approach. Classification, authority, law, facility and supplier conditions must be assessed per engagement through appropriate security processes.

Define the required control level, mission impact and operating responsibility together.

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