Migrate your AI data and models to air-gapped private clouds or sovereign providers in under 8 weeks, ensuring all processing remains within mandated borders.
Service
Sovereign Cloud AI Migration
Migrate existing AI workloads and data pipelines from global public clouds to sovereign cloud providers or air-gapped private infrastructure, ensuring full jurisdictional control and compliance with national mandates.
Migrate AI workloads from global clouds to sovereign infrastructure for full jurisdictional control and compliance.
We execute a zero-downtime migration of your existing AI workloads, including:
- Vector databases and RAG pipelines from services like Pinecone or Weaviate
- Training and inference endpoints for models like Llama 3 or GPT-4
- Data pipelines built on Apache Airflow or Kubeflow
- Monitoring and governance stacks (MLflow, Weights & Biases)
This transition locks your proprietary contextual data within sovereign borders while maintaining operational performance.
Our migration delivers:
- Full compliance with the EU AI Act, China's Data Security Law, and other national mandates
- 99.9% uptime SLA during and after the cutover
- A 60% reduction in cross-border data transfer risks
- Seamless integration with existing Federated Learning Systems for global intelligence without data export
We provide the technical architecture to replace global cloud dependencies with sovereign control, a critical step in Geopatriated Data Lake Design.
TANGIBLE RESULTS
Business Outcomes of Sovereign AI Migration
Migrating AI workloads to sovereign infrastructure is a complex technical undertaking. We deliver measurable business value by ensuring compliance, enhancing security, and maintaining operational excellence.
01
Guaranteed Jurisdictional Compliance
Achieve full compliance with data residency mandates like the EU AI Act, China's DSL, and India's DPDPA. We architect systems where data and processing remain within sovereign borders, eliminating regulatory risk and enabling market access.
0%
Cross-border data leakage
100%
Audit readiness
02
Reduced Latency & Operational Costs
Deploy AI inference closer to your regional users and data sources. By leveraging local sovereign clouds, we eliminate the latency and egress costs associated with global hyperscalers, improving application performance and reducing TCO.
< 50ms
Regional inference latency
40-60%
Lower egress costs
03
Enhanced Data Security Posture
Mitigate supply chain and geopolitical risks by air-gapping critical AI models and training data. Our migration designs incorporate confidential computing and hardware security modules (HSMs) to protect intellectual property from external threats.
TEE/HSM
In-use data protection
ISO 27001
Architecture aligned
04
Accelerated Time-to-Market
Leverage our pre-built blueprints and automation for sovereign cloud providers like OVHcloud, Gaia-X, and Yandex Cloud. We streamline the migration of complex data pipelines and ML workloads, moving from assessment to production in weeks, not months.
2-4 weeks
Pilot deployment
Automated
Pipeline migration
From Assessment to Full Sovereignty
Phased Migration Timeline & Deliverables
A structured, risk-managed approach to migrating your AI workloads from global public clouds to sovereign infrastructure. Each phase delivers specific, measurable outcomes.
| Phase & Key Activities | Timeline | Primary Deliverables | Success Metrics |
|---|---|---|---|
Phase 1: Discovery & Compliance Mapping | 2-3 weeks | Sovereignty Gap Analysis Report, Data Lineage Map, Jurisdictional Risk Assessment | 100% of data assets cataloged, Legal requirements mapped to technical controls |
Phase 2: Architecture & Landing Zone Design | 3-4 weeks | Sovereign Cloud Blueprint, Security & Access Control Matrix, Data Residency Gateway Design | Architecture approved by legal & security teams, All data flows defined |
Phase 3: Pilot Migration & Validation | 4-6 weeks | 1-2 Critical Workloads Migrated, Performance Baseline Report, Rollback Playbook | Pilot workloads operational with ≤5% latency increase, 99.9% uptime SLA met |
Phase 4: Full Production Migration | 6-10 weeks | All AI Models & Pipelines Migrated, Automated Compliance Monitoring Dashboard, Operational Runbooks | Zero data sovereignty violations, Full cutover with <2 hours downtime |
Phase 5: Optimization & Federated Integration | Ongoing | Cost-Optimized Resource Scaling, Federated Learning Node Setup (Optional), Continuous Compliance Auditing | 20-40% reduction in sovereign cloud spend, Secure model sharing enabled |
Ongoing Support & Governance | Post-Migration | Dedicated Technical Account Manager, Quarterly Security Reviews, Access to Sovereign AI Updates | Proactive issue resolution, Adherence to evolving regional mandates |
HIGH-COMPLIANCE SECTORS
Industries Requiring Sovereign Cloud AI Migration
Global enterprises in regulated sectors face mounting pressure to relocate AI workloads from public clouds to sovereign infrastructure. These industries require proven migration expertise to maintain innovation while ensuring full jurisdictional control over data and models.
Enabling Efficiency, Speed & Accuracy
Intelligent Analysis, Decision & Execution
We build AI systems for teams that need search across company data, workflow automation across tools, or AI features inside products and internal software.
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Search across company data
Give teams answers from docs, tickets, runbooks, and product data with sources and permissions.
Useful when people spend too long searching or get different answers from different systems.
Enterprise searchRAGPermissions
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Automate internal workflows
Use AI to route work, draft outputs, trigger actions, and keep approvals and logs in place.
Useful when repetitive work moves across multiple tools and teams.
AI agentsWorkflow automationGovernance
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Add AI to products and internal tools
Build assistants, guided actions, or decision support into the software your team or customers already use.
Useful when AI needs to be part of the product, not a separate tool.
AI integrationDecision supportModel routing
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Sovereign Cloud AI Migration FAQ
Answers to common questions about migrating AI workloads to sovereign or private infrastructure, ensuring compliance and control.
Our standard migration framework delivers a fully operational sovereign AI environment in 2-4 weeks. This includes assessment, data pipeline re-engineering, model porting, and validation. Complex multi-model deployments or legacy system integrations may extend to 6-8 weeks. We provide a detailed project plan with weekly milestones during the initial discovery phase.
About the author
Prasad Kumkar
CEO & MD, Inference Systems
Prasad Kumkar is the CEO & MD of Inference Systems and writes about AI systems architecture, LLM infrastructure, model serving, evaluation, and production deployment. Over 5+ years, he has worked across computer vision models, L5 autonomous vehicle systems, and LLM research, with a focus on taking complex AI ideas into real-world engineering systems.
His work and writing cover AI systems, large language models, AI agents, multimodal systems, autonomous systems, inference optimization, RAG, evaluation, and production AI engineering.
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How We Work
Custom AI workflows for your Business
One-fit-all AI don't work for modern businesses. At Inferensys, we aim to understand your business & custom requirements; which we use to define most efficient agentic workflows, the data, and the tools for your business.
01
Review the use case
We understand the task, the users, and where AI can actually help.
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Pick the right approach
We define what needs search, automation, or product integration.
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Build the first useful version
We implement the part that proves the value first.
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Improve from there
We add the checks and visibility needed to keep it useful.
Read moreThe first call is a practical review of your use case and the right next step.
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