Models & serving
Run the model and control its version.
- Open-weight models
- Inference endpoints
- Model versioning
DATA / MODELS / DEPLOYMENT
Bring AI to your data. Keep authority over both.
Choose the environment for your sensitive workloads. Design private model serving, controlled data access, and an operating model that your teams can maintain.
THE PRIVATE STACK
Four layers. One boundary you define.
Data, models, access control and the people who use them are designed together. Requests move up the stack only through the controls agreed for each layer.
- 01Your data
Documents, databases and search, with their access rules.
- 02Private models
Served and versioned inside your approved environment.
- 03Governed gateway
Identity, policy and limits on every connected request.
- 04Teams and agents
Work within the permissions agreed for each task.
YOUR APPROVED ENVIRONMENT
Knowledge & data
Provide the business context it is allowed to use.
- Document stores
- Databases
- Search & retrieval
Identity & control
Decide who and what can access each capability.
- Enterprise identity
- Access policies
- Human approvals
Infrastructure & operations
Keep the environment available and recoverable.
- Compute & storage
- Network boundaries
- Monitoring & recovery
PRIVATE AI / WITHIN YOUR ENVIRONMENT
Your models. Your data. Your sovereign infrastructure.
Bring AI to sensitive workloads without making an external model API the default. sden designs private inference environments with the access controls, governance, and operational tooling your organization needs.
Discuss your private AI requirementsORGANIZATIONAL CONTROL BOUNDARY
A clear path for sensitive workloads
- 01Authorized users
A team, application, or agent makes a request.
- 02Policy gateway
Check identity, permissions, and usage limits before routing.
- 03Private inference
An approved model uses permitted internal knowledge inside the boundary.
Evaluation / monitoring / controlled release
ORGANIZATIONAL CONTROL BOUNDARYExplore the perimeter
Within this scope
Keep sensitive inference in your environment
Design prompts, retrieved documents, and model responses to remain within a defined boundary. Review connectors, telemetry, backups, and support access so the complete data path matches that intent.
Within this scope
Turn residency requirements into architecture
Map processing locations, administrative access, retention, and contractual dependencies. Work with your security and legal teams to translate applicable obligations into technical and operational requirements.
Within this scope
Choose models on your terms
Evaluate open-weight models against your workloads, hardware, licensing terms, and quality requirements. Establish a replacement path and a release policy instead of relying on a single external inference API.
Within this scope
Operate beyond the initial deployment
Define model versioning, evaluation gates, staged releases, rollback, capacity planning, and monitoring. Configure scaling where the infrastructure supports it, with named responsibility for ongoing operation.
Within this scope
Apply policy at the point of access
Use a shared gateway to enforce team permissions, model access, rate limits, and usage budgets. Add task-specific guardrails and human approval where the consequences warrant them.
Within this scope
Trace activity without over-collecting data
Design audit records around identity, model version, policy decisions, and operational events. Configure prompt and response logging selectively, with redaction, access restrictions, and retention rules.
WHAT THE ARCHITECTURE SHOULD ENABLE
- Defined data and inference boundaries
- Deliberate model and provider dependencies
- Consistent access policies across teams
- Controlled model releases and recovery
- Operational visibility with proportionate logging
Model selection is workload-specific. Self-hosting does not by itself guarantee quality, security, availability, or independence from every supplier.
SOVEREIGNTY IS A SET OF DECISIONS
Specify the boundary. Then test the whole data path.
A hosting address cannot answer every sovereignty question. Model access, administration, contracts, telemetry, and recovery need to be assessed together.
Data and processing
Where prompts, retrieved content, responses, and backups may be processed or stored.
Administrative access
Who can administer the systems, from where, and under which approval and logging requirements.
Model and supplier choices
Which licenses, dependencies, support arrangements, and replacement paths are acceptable.
Evidence and recovery
What is logged, for how long, who can inspect it, and how service is restored.
INFRASTRUCTURE OPTIONS
The right deployment. For your requirements.
Architecture follows your data sensitivity, integration needs, performance objectives, operating capacity, and procurement constraints.
Private cloud
A dedicated environment with defined administrative boundaries, identity controls, and connectivity to your data estate.
On-premise
Infrastructure within your facilities, with compute, storage, networking, and lifecycle responsibilities designed as one system.
Hybrid
Place workloads according to their requirements and connect environments through documented interfaces and data boundaries.
Hosting location is one design choice. Sovereignty also depends on access, contracts, dependencies, and operations.
START WITH YOUR REQUIREMENTS
Define what your organization needs to control.
Start with your workloads, data constraints, and existing architecture. Establish the scope before selecting the tools.