Cloud architecture

On-premises and cloud environments are integrated into a unified hybrid architecture, enabling secure data flows and deployment of new solutions without destabilizing core systems.

• On-prem to cloud integration. Data and model synchronization between on-premises systems and the cloud.
• Secure connectivity. Dedicated connections (VPN / ExpressRoute) with encryption and access control.
• Data movement control. Data classification, DLP, and masking mechanisms applied before information is transferred to the cloud.
• Cloud governance & operating model. Clear roles, operational processes, and policies for cost management and model lifecycle governance.
• Third-party vendor risk management. Vendor assessments, SLA oversight, and contractual safeguards aligned with regulatory requirements.

Benefits:

• Integration of AI solutions with core systems without destabilizing architecture
• Gradual modernization of the IT environment
• Reduced operational risk during transformation

Production-ready environment for AI systems, with full control over security, availability, and model management.

• Secure compute environments for AI. Isolated compute environments (e.g., GPU clusters) with access control and data encryption.
• Business continuity & disaster recovery. Automated backups, model versioning, and regular testing of recovery procedures.
• RTO / RPO modelling. Definition of acceptable recovery times for services and data across critical systems.
• Security monitoring & incident management. Continuous security monitoring, vulnerability scanning, and incident response procedures.
• AI model governance. Model registry, approval workflows, and ongoing monitoring of model quality and drift.

Benefits:

• Stable operation of AI systems in production (up to 99.9% availability)
• Compliance with regulatory requirements for business continuity and disaster recovery (BC/DR)
• Reduced risk of security incidents
• Faster incident response (MTTR < 1h)

FinOps and cost management mechanisms ensure full transparency of cloud spending as cloud adoption grows.

• Usage monitoring & forecasting. Monitoring resource usage and forecasting project costs.
• FinOps & cloud cost governance. Cost management policies, resource tagging, and budget controls.
• Resource optimization. Optimization of instance utilization, reserved capacity, and pricing models.
• Chargeback / showback models. Transparent allocation of cloud costs to projects and cost centers.

Benefits:

• Predictable cloud costs (variance approx. ±5%)
• Cost control as the number of AI models grows
• Improved forecasting of resource usage
• Build vs buy decisions based on cost data
• Infrastructure cost optimization of 20–40%