Use-case blueprint

Building an approved-content AI assistant for product and distribution teams

A use-case blueprint for answering internal product questions from permissioned, approved sources with citations, evaluation, and escalation.

Firm profile

An asset manager with a growing library of factsheets, presentations, commentaries, product FAQs, investment-process documents, disclosures, and internal operating guidance.

Operating trigger

Distribution and client-service teams spend time searching across repositories or asking a small number of product experts. General-purpose AI can draft plausible answers but cannot reliably identify the firm’s current approved position.

Systems in scope

The workflow crosses system boundaries.

Current state

What makes the workflow break down.

  1. Employees search several repositories and often begin from the first plausible document rather than the current approved source.

  2. Product specialists repeatedly answer similar questions and manually attach supporting materials.

  3. Superseded factsheets and disclosures remain discoverable alongside current versions.

  4. Answers copied into email or presentations lose their connection to source passages and effective dates.

Solution architecture

A controlled operating design.

Approved source registry

Index only authorized repositories and capture product, audience, effective date, approval status, document type, and superseded status.

Permission-aware retrieval

Apply the user’s source permissions before retrieval so the assistant cannot surface restricted material.

Cited answer contract

Require the response to distinguish sourced facts, synthesis, missing information, and questions requiring an expert.

Evaluation and feedback

Test retrieval, citation validity, completeness, abstention, and prohibited behavior against a maintained question set.

Implementation sequence

Prove the workflow before expanding it.

Choose a bounded corpus

Begin with one product family and a small number of authoritative document types.

Define answer policy

Specify who can ask what, which sources are authoritative, when the assistant must decline, and how feedback is handled.

Build evaluations

Create normal, ambiguous, outdated, restricted, and unanswerable questions before the pilot.

Pilot in context

Place the assistant in an internal portal or workflow and review real questions, citations, overrides, and escalations.

Controls

What keeps the workflow dependable.

  • User-level access enforcement
  • Current-versus-superseded source handling
  • Citations to the supporting passage and document version
  • Prompt, source, model, and output logging consistent with firm policy
  • Human escalation for external communication or uncertain answers

Target state

What changes after implementation.

  • Users receive a concise answer with supporting sources rather than an uncited generated response.
  • The assistant abstains or routes the question when approved material is incomplete or conflicting.
  • Product owners can see recurring questions and gaps in the content library.
  • The firm can measure answer quality using evaluations and reviewed feedback.

Measurement

Metrics to baseline and track.

Answer acceptance without material correction

Citation validity and source freshness

Abstention accuracy on unanswerable questions

Time required to locate an approved answer

Question volume escalated to product specialists

Evidence note

The assistant supports internal retrieval and drafting. The asset manager determines whether any output may be used externally and what legal, compliance, privacy, security, and recordkeeping controls apply.

Have a version of this workflow inside your firm?

We can map the current state, identify a credible first release, and define the controls and measures required to operate it.

Discuss this use case