Data location
Where are source data, copies, backups and logs stored? Where does data travel, including during AI processing?
Data Sovereignty & AI Architecture
Your data.
Your choices.
An AI architecture that fits.
Where is your data stored? Who can access it? And where does AI process your information? We clarify the trade-offs before you commit to a platform.
Discuss your sovereignty assessment Explore the approach
Control starts with insight
A location is not the same as control.
Data residency concerns where data is stored and processed. Data sovereignty goes further: who has access, who manages the keys, which parties and jurisdictions are involved, and can you operate independently or switch providers?
A European data location does not automatically answer every question about control or compliance. We examine technology, operations and agreements together. Legal conclusions are reviewed with your legal and privacy leads.
Four questions. One coherent design.
What do you need to control?
Access & keys
Who can access data and administrative functions? We examine roles, vendor and support access, encryption and actual control over keys.
Operational control
Who operates, restores and maintains the environment? Which dependencies remain and what is needed for continuity and a practical exit?
AI processing
Which data may be sent to which model? We define choices for prompts, retrieval, model hosting, logging, retention and any use for model training.
Start with your requirements, not the cloud.
Three directions. No default winner.
We compare options for each workload. The considerations below are not product guarantees: the outcome depends on the services, configuration, agreements and operating organisation.
Azure public cloud
Managed services and scalability can reduce operational work. We assess regions and data flows for each service, access, key management, AI endpoints and dependencies on platform features.
Hybrid architecture
Keep selected data or processing in your own environment and connect it selectively to cloud services. We examine data boundaries, identity, network connections and the additional operational complexity.
Client-managed private cloud
More direct control also requires your own capacity for security, updates and recovery. We assess feasibility, hardware and AI capacity, vendor dependencies and the operating model.
Sovereignty and deployment assessment
From difficult questions to clear choices.
At the start of a new data platform initiative, or when an existing architecture needs a fresh look. Together with data owners, IT, security and privacy, we turn the choices into a well-founded decision.
Map the landscape
Data, sensitivity, workloads, access rights, AI usage and dependencies. We make explicit what is known and what still needs investigation.
Make requirements testable
Document requirements for data location, access, operations, continuity, AI processing and exit. Include owners, priorities and acceptance criteria.
Compare the options
Compare Azure public cloud, hybrid and client-managed private cloud for each workload. Make risks, operational burden, cost drivers and missing evidence visible.
Choose a practical direction
Develop the preferred architecture with data flows, trust boundaries, responsibilities and a prioritised path to validation and implementation.
What will you take away?
Not a pile of buzzwords, but decision-ready information your team can use. We agree the depth of the assessment and the systems in scope beforehand.
- An overview of data, AI workloads, access and dependencies.
- A requirements and trade-off matrix for the deployment options.
- An architecture sketch showing data flows, boundaries and responsibilities.
- A risk and decision log with assumptions and open questions.
- A prioritised next-step plan, including validation and exit considerations.
For data that deserves careful handling.
Research & laboratories
Share research data without losing sight of access, provenance and reproducibility.
Water organisations
Connect measurement data, models and collaboration with clear agreements on data usage, operations and AI processing.
Industry
Put sensitive process data and intellectual property to work, with attention to continuity, network boundaries and vendor dependency.
Governance and architecture belong together.
We connect data ownership, classification and access policies to concrete design choices. In an AquaCore initiative, for example, the assessment can determine which deployment direction fits the integration and process layer for research data. We assess and validate in advance which deployment options are feasible for your AquaCore initiative.
Get clarity first. Then build smart.
Tell us about your data or AI challenge. We will discuss the decisions ahead and whether a sovereignty assessment is the right first step.
Discuss your sovereignty assessment