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sDEN

Operating institutional AI

Turn an institutional AI pilot into an owned service with clear responsibilities, repeatable checks and an operable handover.

An institutional IT specialist checking an operations runbook beside modest campus server equipment

An institutional AI pilot can answer a carefully prepared set of questions and still be difficult to operate. Someone has to maintain its connections, review access changes, handle unanswered questions and decide whether a model update is acceptable. Those responsibilities often sit across IT, records management and the teams using the service. If they remain implicit, a successful demonstration can become an unsupported dependency.

Treat operational ownership as part of the initial design. The institution should know who can change the system, what evidence is required before a change and how staff obtain help when a response looks wrong. A useful service is one that the institution can inspect and maintain, including when the original project team is unavailable or the first enthusiastic sponsor moves on.

Step 1

Name owners for the complete service

Separate responsibility for infrastructure, connected sources, identity rules, knowledge quality and the user experience. One service owner should coordinate these responsibilities, but that person need not perform every task. Record who approves a new repository, who can correct a relationship and who decides that a document family is outside the supported scope. Define an escalation route for disagreements rather than leaving them in an informal project chat.

Write a short service description in terms staff can use. State which questions it supports, which sources it covers and when a person must check the evidence or consult an expert. Explain how to report a misleading answer without requiring the user to understand the technical pipeline. The intake process should capture enough source context to reproduce an issue while respecting the same confidentiality boundaries as the service.

Step 2

Make changes reviewable and reversible

Keep a representative evaluation set covering retrieval, citations, permissions and questions the service should decline. Run it before changing a model, extraction rule or retrieval configuration. Compare the actual answers and evidence, not only a single aggregate score. A change that improves routine questions but weakens access boundaries is not an acceptable trade without an explicit decision by the responsible owners.

Maintain a record of the configuration in use and a practical route back to the previous working version. Plan for source outages, incomplete ingestion and unexpected document formats. Staff should be able to distinguish a service with limited coverage from one that is operating normally. NIST's AI Risk Management Framework is a useful reference for organizing governance and monitoring across the lifecycle, rather than treating evaluation as a one-time launch activity.

Step 3

Rehearse the handover through real tasks

Ask the receiving team to carry out ordinary operations using the delivered documentation: connect an approved collection, investigate a failed update, remove access and review a questionable citation. Observe where they need undocumented knowledge from the delivery team. Those gaps are part of the handover work. A folder containing configuration files is helpful, but it does not demonstrate that anyone can operate the service.

Include a recovery exercise appropriate to the deployment. Confirm that the institution can locate the relevant backups, understand dependencies and identify who authorizes restoration. Set a review schedule for source coverage and user feedback. Training should follow the responsibilities of administrators, knowledge owners and everyday users; each group needs different information to make its part of the service dependable over time.

How sDEN approaches it

Connected knowledge. Inspectable evidence.

Apply these principles to a defined collection and a practical decision.

Connected knowledge. Inspectable evidence.Explore the perimeter

Within this scope

Institutional control

sDEN makes deployment, processing and administration choices explicit. Private models operate within an approved environment instead of leaving the processing boundary undefined.

Within this scope

Connected evidence

A governed knowledge graph connects institutional documents and systems. Answers retain their sources so staff can inspect the evidence and report problems with specific records.

Within this scope

Skills to run the service

sDEN transfers configuration, documentation and operational skills. The institution keeps the knowledge needed to maintain the service and make informed choices about its evolution.

Illustrative map. Scope, responsibilities and controls are agreed for each engagement.

A useful first delivery

What your team should be able to use

A completed handover leaves a named service owner, trained operators, an evaluation set, a change process and working documentation. The receiving team can perform routine tasks and explain the service's limitations without relying on undocumented assistance. That gives the institution a more durable foundation for expanding coverage and a clear basis for deciding when a proposed capability is ready for everyday use.

Questions

Institutions & research, answered.

Should the research team or IT own the service?

A named service owner should coordinate both. IT can own infrastructure and identity integration while research or records teams own source meaning and quality. Responsibilities must be explicit.

When is the handover complete?

When the receiving team can carry out agreed operational tasks, investigate representative failures and apply the change process using the delivered documentation and access. Attendance at a presentation is insufficient evidence.

Sources

Where this comes from.

  1. NIST: AI Risk Management Framework

Ready to build AI you can govern, audit and own?

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