Private & Sovereign AI Exploration
GenAI Protos provides private AI consulting and hands-on prototypes to help you assess on-premises AI and private cloud options. Explore locally hosted models, test data boundaries, and check offline operation where required before choosing your next step.
How We Help
Our private and sovereign AI exploration services help you test local models, assess deployment options, and evaluate your data and operational-control requirements.
Assess Private AI Deployment
Assess private LLM deployment and private cloud AI deployment options against your use case, infrastructure, and operational requirements.
Build a Private AI Prototype
Test a focused workflow in your target environment using representative data and agreed access controls.
Evaluate Local AI Models
Compare locally hosted models, including self-hosted LLM options, for task quality, response time, memory use, and hardware requirements.
Test Offline AI Operation
Assess whether the complete application can perform its agreed tasks without external connectivity.
Validate AI Data Boundaries
Assess AI data residency and data flows: where documents, prompts, outputs, and logs are processed, stored, and accessed, including external connections.
Explore Sovereign AI Requirements
Our sovereign AI consulting assesses technical dependencies against your jurisdiction, ownership, and operational-control needs, identifying gaps beyond local hosting.
Benefits of Working With Us
Resolve Deployment Questions Early
Test AI in your target environment to uncover infrastructure and integration constraints before a larger rollout.
Access Private AI Expertise
Work with engineers who can assess local models, deployment dependencies, and technical control requirements.
Plan Infrastructure Spend With Evidence
Measure resource needs and performance before committing to hardware, hosting, or software licences.
Validate Performance and Data Control
Test output quality, response times, and data flows against agreed requirements so you understand both capability and remaining gaps.
What You Get
Deployment Feasibility Assessment
Review the use case, available infrastructure, data boundaries, and access requirements. Compare suitable options and identify unresolved model, hardware, software, and operating dependencies.
Deliverables:
- Requirements and constraint summary.
- Deployment options and tradeoffs.
- Model and infrastructure shortlist.
- Feasibility findings and recommended next steps.
Private AI Prototype
Build a private AI proof of concept on agreed on-premises or private cloud infrastructure. Test the core workflow with representative inputs and measure quality, response time, and resource use within the scoped environment.
Deliverables:
- Working prototype in the agreed environment.
- Model and application configurations.
- Quality, performance, and resource findings.
- Setup documentation and handover.
Data-Boundary and Dependency Testing
Map the prototype's data flows, including prompts, source documents, outputs, retrieval indexes, logs, and storage. Review external connections and access controls. Where required, test offline operation and record remaining dependencies.
Deliverables:
- Data-flow and access overview.
- External connection and dependency findings.
- Results from the agreed boundary and offline tests.
- Known gaps and recommendations for the next deployment stage.
Scope and costs
We agree on the target environment, access requirements, test scope, deliverables, milestones, and price before starting. Timing depends on infrastructure readiness, model access, and the testing required.
Hardware, hosting, licences, and any on-site work are identified separately. The engagement focuses on exploration and the agreed prototype; requirements for a wider implementation are assessed through the findings.
Common Questions About Private and Sovereign AI
We assess on-premises or private cloud deployment options and prototype a workflow within your intended data boundaries. We check how documents, prompts, outputs, and logs are processed, stored, and accessed, including any external connections.
Yes, we assess your workload, model options, expected usage, and performance requirements, including LLM hardware requirements where relevant. Where practical, we measure resource consumption and document hardware, hosting, and software cost assumptions before you purchase.
Yes, we test whether the complete AI application performs its agreed tasks without external connectivity. The findings document offline performance, supporting dependencies, and any changes needed for the intended deployment.
Yes, we first review your available infrastructure and agree on a focused private AI use case. Our engineers assess whether the environment can support the prototype and identify resource or integration gaps before building.
Yes, we assess where data is processed and stored, which technical dependencies exist, and who controls the deployment. We map these findings against your stated jurisdiction, ownership, and operational requirements, identifying gaps that require further review.
Related services
Explore adjacent AI capabilities tailored to solve your technical and operational challenges.
Where does your AI need to run?
Tell us the use case, where your data must stay, and the infrastructure available. We will help define a focused assessment or prototype.
Let's Explore Your Idea
Tell us what you want to build, test, or improve. You don't need a detailed brief to get started.