AI Sandbox

Test a technical knowledge assistant against representative questions

Engineers and technicians search across manuals, tickets and scattered instructions where sources and versions matter. A sandbox measures whether controlled retrieval can produce useful, referenced answers.

Intended result: Measured evidence about answer quality, source coverage, access boundaries and operational usefulness.
Human approval: Required
Integration: Not necessarily

Situation

Current problem

Technical staff spend time locating the correct instruction while document versions and access rights matter.

Desired change

The prototype answers a defined question set with references and refuses when evidence is insufficient.

Possible workflow

Prepare

Select sources and questions

Choose approved manuals, tickets and representative questions with expected evidence.
Prototype

Retrieve and answer

Test parsing, retrieval, citations, access constraints and fallback behavior.
Evaluate

Review quality and risk

Score correctness, relevance, citation support, omissions and unsafe confidence.

Human control

Technical owners judge correctness, approve sources and remain responsible for operational decisions.

Technology and data

Controlled sources: Approved manuals, tickets and instructions with version metadata.
Private retrieval: Document parsing, indexing and retrieval within agreed boundaries.
Access control: Tests that verify users only receive permitted evidence.

Boundaries

References do not compensate for outdated source material.
Representative questions must include difficult and unanswerable cases.
Users need an explicit route when evidence is insufficient.
Production security and operations require a separate implementation decision.
The experiment does not replace technical accountability
Outdated or conflicting sources reduce answer quality
Production integration is outside the sandbox scope