Use a fictional assistant to examine where business information is processed and retained, from documents and model input to search indexes, logs and backups.
The spoken explanation, organised by chapter.
Private AI needs specific requirements for access, processing and storage, rather than a label.
A fictional company wants staff to ask questions about project documents. The files are restricted. But the application also creates a search index, sends context to a model and may retain execution records.
Identify what each component receives and where information may persist. Include answers, logs and backups. A restricted document folder alone does not establish how the rest of the chain is configured.
Who may read information? Which parties process it? What storage and retention are allowed? Make these questions explicit and separate. Hosting your own system does not automatically settle user permissions or administrator access.
A business service, restricted cloud environment and self-hosted model may have different conditions. Compare the complete data journey, required controls, answer quality and maintenance your organisation can support.
Pass only permitted information into the task. Check what enters sessions, search results and logs as well. A general instruction to remain confidential does not replace technical permission enforcement.
Try different user roles and revoked permissions. Investigate deletion and recovery. Also assess quality, speed and maintenance effort with your tasks; a restricted environment still needs to work in practice.
Classify information and assign owners. Record data flows and responsibilities. Then choose an arrangement that fits those requirements, identifying what still needs to be checked.
Read OXIAE’s guide to assessing private AI across the data journey and its maintenance requirements.
1:52Follow a fictional work instruction through its lifecycle and see how source owners, versions, access permissions and deletion keep an AI knowledge base manageable.
Source articleAI knowledge base
1:59See how model output becomes controlled application input. An illustrative report explains field validation, content checks, error handling and permissions.
Source articleOpenAI integration
2:00An illustrative recovery question separates missing evidence from a demonstrated defect. Make scope, impact, follow-up action and verification clear in an audit.
Source articleSoftware audit