# Permission-Aware Enterprise Knowledge — Reference Architecture

> An internal AI search and answer system that treats access control as an architectural requirement.

Canonical URL: https://marmation.com/lab/permission-aware-knowledge/

## Implementation boundary

The reference architectures are concepts, not completed client systems. Intelligent Document Operations includes an implemented local browser demonstration with 15 fabricated text fixtures and deterministic rules. It uses no AI provider, real authentication, persistent destination or external business write. Its role controls illustrate guards; they are not production authorization.

A common enterprise AI request is deceptively simple: let employees ask questions about company knowledge. In a large organization, knowledge is not a single pile of text. It is an overlapping network of source systems, versions, permissions, ownership and retention policies.

This reference design tests whether an AI assistant can answer a user from only the information that person is actually entitled to see, cite its sources, and clearly say when it does not have an answer.

## The user journey

An employee asks a question in a simple search-first interface. The assistant identifies its authorized retrieval scope, searches indexed and live sources where appropriate, returns a concise answer with verifiable citations, and shows last-updated information. Clicking a citation opens a source document only if the user's existing access permits it.

The same question asked by two employees can legitimately produce different answers. That must not be treated as a retrieval bug. It is a consequence of access rules.

## System design

**Identity:** SSO identity and group membership are carried through to retrieval; the model itself never decides permission.  
**Sources:** Synthetic policy, maintenance and product documents with version and ownership metadata.  
**Ingestion:** Connectors normalize and chunk documents, carry source IDs, metadata and ACL references, record indexing failures and maintain deletion/revocation propagation.  
**Retrieval:** Query rewriting and hybrid search as appropriate, filtered by current authorized source permissions before any restricted text reaches inference.  
**Generation:** A replaceable model adapter constructs responses from authorized evidence, surfaces uncertainty and allows a no-answer result.  
**Observability:** Trace retrieval IDs, grounding and citation consistency using redactable logs without exposing restricted content in analytics.

## Test identities and content

Create three fictional users: a field technician, a regional supervisor and a finance administrator. Create 30 synthetic documents with carefully different permissions. Include two identical document titles in different departments, a policy superseded by a new version, one deleted page and a confidential memo that never appears to the field technician.

## Negative tests

- A user who cannot access a source must not receive a summary of that source, even when the question includes its exact title.  
- Revoking a permission must prevent retrieval according to a documented synchronization SLA.  
- A source citation must point to the exact authorized version and page or document anchor.  
- A document with malicious instructions must not change the assistant's data-access scope.  
- Queries that lack authorized evidence should receive a safe insufficient-evidence response.  
- Logs and monitoring should not create a secondary exposure path for restricted content.  
- Search caching must preserve user and tenant boundaries.

## The make-or-buy test

A Microsoft 365 environment may already have a governed way to answer many of these questions. Before building a custom retrieval stack, inspect existing entitlements, connector support, licensing, UX needs, provenance requirements and policy behavior. Custom engineering may be warranted for mixed systems, specialized workflows, tenant boundaries or product experiences not served by an existing platform.

## Related reading

- [Proof has a structure.](https://marmation.com/lab/)
- [From working prototype to dependable system](https://marmation.com/review/engineering/)
- [AI Product Review Workspace — Reference Architecture](https://marmation.com/lab/ai-product-review-workspace/)