AI / AI-01
Secure enterprise AI deployment
Provide useful AI to teams within a controlled framework: approved uses, identities, data, integrations, costs and operations. Security covers the whole service, not merely the selected model.
WHEN IT HELPS
A focused response
to a defined need.
Employees using personal accounts, demand for an internal assistant, business automation or a desire to adopt AI without exposing sensitive documents or allowing uncontrolled spending.
SCOPE & OUTCOMES
What the engagement covers.
Scope
- Business scoping
- eligible data
- hosting and offering selection
- SSO/roles
- connectors
- exchange protection
- budgets
- pilot
- quality/security testing
- training
- operations
Deliverables
- Architecture
- permissions matrix
- usage policy
- provider and processing register
- configurations
- pilot report
- tests
- support and offboarding procedures
Acceptance evidence
Access is limited to approved users; data and connectors are approved; privacy and quality tests are completed; spending controls are understood; prohibited uses and human fallback are documented.
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
Which specific work should AI support? Which data must never be transmitted? Who validates responses, spending and access rights?
IMPORTANT BOUNDARIES
Training use, retention, residency, subprocessors and connectors are distinct issues to verify per offering. No blanket guarantee of accuracy, absolute confidentiality or automatic compliance.
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
A company wants to replace personal AI use with a business workspace. Project: select the offering, connect identity and train teams. Target outcome: governed use without automatically equating a business subscription with zero data retention.
Scenario 02
A support team wants answers generated from its procedures. Project: pilot an approved corpus with human validation before sending. Target outcome: useful, measurable assistance; insufficiently reliable answers remain drafts requiring review.
Technology and reference context
Examples: business AI offerings, APIs or hosted models; selection based on requirements, contracts and tests rather than a single mandated provider.
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.