AI / AI-07
Private AI hosting and data-lifecycle control
Deploy or scope AI in an environment with controlled hosting, access and processing. The service examines model, inference, indexes, logs, backups and subprocessors; private hosting is not automatically secure.
WHEN IT HELPS
A focused response
to a defined need.
Highly confidential data, residency requirements, isolated operation needs or restrictions on transfers to external services.
SCOPE & OUTCOMES
What the engagement covers.
Scope
- Architecture selection
- model provenance and licensing
- compute capacity
- network and egress
- access
- storage/indexes
- secrets
- logs
- retention
- updates
- backups
- deletion
Deliverables
- Architecture file
- data-flow map
- secure configuration
- provenance register
- egress and access tests
- update procedures
- cost and operating model
Acceptance evidence
Approved flows are known; unexpected egress is controlled; access is tested; retention and deletion are verified across selected components; performance and costs are measured on representative use.
DELIVERY
How the work is structured.
Approach
Choose a use case; classify data and access; design and pilot; test privacy, actions and cost; decide rollout and monitoring.
Prerequisites & responsibilities
Customer: business sponsor, data owners, identity team, DPO/legal where needed and budget. Provider: architecture and tests; customer retains approval of sensitive use.
Scope factors
Uses, users, models, data, connectors, permissions, actions, volumes and hosting. Separate project, licenses, tokens, search, storage and operations; no claimed savings without measurement.
Questions to clarify
What isolation level is actually required? Who maintains models and infrastructure? Which data remain in logs, indexes, caches and backups after document deletion?
IMPORTANT BOUNDARIES
An open or local model can carry supply-chain, licensing and operational risks. Location, confidentiality, sovereignty and compliance are not interchangeable concepts.
Permissions, provider data use, retention, residency and cost enforcement are assessed separately. Technical features and applicable obligations are checked for the chosen offering and use case.
IN PRACTICE
Illustrative situations.
These examples describe possible engagements and target outcomes. They are not customer references or achieved results.
Scenario 01
An engineering firm wants AI on private infrastructure. Project: compare requirements, size a pilot and test egress. Target outcome: a documented choice between private hosting and a managed offering based on actual risks and costs.
Scenario 02
An organisation removes a sensitive corpus from an assistant. Project: delete documents and check indexes, caches, logs and backup rules. Target outcome: an explicit deletion lifecycle; copies retained for justified periods remain identified and protected.
Technology and reference context
Examples: self-hosted inference, private hosting or a managed offering meeting requirements; model selection and support require technical and contractual validation.
The final technology set is agreed during scoping, based on interoperability, licensing, access rights and operating requirements.
CONNECTED SERVICES
Build the next step.
These services can complement the engagement. They are not automatically included.
START A CONVERSATION
Make the scope clear.
We will clarify the objective, dependencies and responsibilities of this service before proposing delivery.