Decision summary
For teams repeatedly searching for approved information. The proposal is to help employees reach a verified answer, with a named content owner handling ambiguity. No deployed performance has been measured.
Business problem
Employees repeatedly ask colleagues where to find an approved process, policy, or product detail. The answer often exists, but it is scattered across systems.
Current process
People search shared drives, browse a wiki, and message an experienced colleague. The colleague interprets the question and sends a link, sometimes to an outdated version.
Why the current process is inefficient
Search depends on knowing the right vocabulary and location. Repeated interruptions consume specialist time, while duplicate and outdated documents erode trust.
Could this be solved without AI?
Improve source ownership, remove outdated documents and test existing search first. If employees can find the right source reliably, generated answers may add cost without enough benefit.
AI opportunity
Retrieve relevant, permission-appropriate passages and use AI to draft a concise answer with citations. The system should say when the evidence is missing or contradictory.
Proposed workflow
- Authenticate the employee.
- Retrieve only content they are permitted to access.
- Rank current, authoritative sources.
- Draft an answer using those passages.
- Show citations and uncertainty.
- Let the employee verify or escalate to a content owner.
Solution architecture
Source connectors feed a versioned document index. A retrieval service applies the employee’s access scope before returning passages. A generation service receives only authorised context. The interface links to original sources. Deleted documents and permission changes must invalidate cached content and search results.
Data requirements
Start with an owned, bounded collection of approved procedures. Store source IDs, versions, owners, update dates, and access groups. Build an evaluation set from real questions, including questions with no answer and questions from users with different permissions.
Human, AI and automation responsibilities
Content owners maintain approved sources. Employees verify consequential answers. AI drafts a synthesis of retrieved passages. Access controls and source-version checks run outside the model.
Human-in-the-loop
Employees verify important decisions against the cited source. Questions involving ambiguity or high business impact go to a named content owner. Feedback flags weak sources for maintenance rather than silently training on private conversations.
Implementation approach
Choose one team and a limited collection. Test retrieval separately from generated answers. Evaluate citation support, abstention, and access boundaries. Roll out in a read-only mode and measure whether employees finish their tasks faster.
Technology used
Existing document APIs, a search index, an embedding model when semantic search adds value, and a language model for grounded synthesis. Keyword or hybrid search may outperform a vector-only approach on exact product codes and policy names.
Cost considerations
Budget for source ingestion, index storage, model usage, and document maintenance. Re-index only changed documents where possible. Track cost per helpful answer and include the time people spend checking incorrect or incomplete responses.
Measurement
Measure answer support, retrieval success, appropriate abstention, permission leakage, and time to verified answer. Fewer repeated questions may be useful, but should not replace direct quality measurements.
Agree the baseline, representative evaluation sample and go/no-go criteria with the process owner before testing. Record failures and review effort as well as successful outputs.
Expected business impact
The hypothesis is less time spent searching and fewer interruptions to specialists. There are no observed productivity results; include verification time when evaluating benefit.
Risks and limitations
A fluent answer can still misread a source. Stale permissions, index lag, and malicious document instructions introduce risk. Enforce authorisation outside the model, isolate untrusted text, and retain a clear “I cannot find this” path.
Design considerations
Blueprint design takeaways: content ownership is a prerequisite for trustworthy answers. Access control must be tested as part of retrieval. This is an illustrative architecture, not a claim of deployed results.