Build a Product Q&A Assistant Limited to Approved Docs with Prismfy

The pattern here is docs-first assistance with public-web verification, so support workflows stay grounded in approved documentation while still checking current public pages when needed.

Problem framing

A product Q&A assistant seems straightforward until the edge cases show up. A user asks about a setting, a limit, a plan, or a workflow detail, and the model has to choose between confident guessing and source discipline.

If you let the assistant roam, it will eventually blend approved docs with stale snippets from somewhere else. If you lock it to a known doc set but do not search carefully, it may miss the exact page that contains the answer.

Prismfy helps with the search step. You can query the approved docs directly with POST /v1/search, keep the evidence set narrow, and instruct the assistant to answer only from the returned pages.

Why this matters now

Product teams update documentation continuously. That creates a moving target for Q&A systems.

The common mistakes are familiar:

• the assistant cites an old article when a newer one exists
• a release note changes behavior, but the assistant still uses the older docs
• a pricing or plan question gets answered from memory instead of approved text
• the Q&A tool returns a generic answer because it searched too broadly

The fix is to treat approved docs as an access control boundary, not just a nice-to-have corpus.

Step-by-step solution

1. Build the assistant around an approved docs list.
2. Search the relevant docs domain with Prismfy.
3. Filter the results to the pages that match the product area.
4. Return a short evidence bundle with titles, URLs, and snippets.
5. Require the assistant to cite those sources or say the answer is not confirmed.

This makes the assistant easier to govern. Product and documentation owners can review the same source set the model sees.

Code example

This TypeScript example calls Prismfy for a product-specific query and formats the top results into citation-ready evidence.

type PrismfySearchResponse = {
  cached?: boolean
  results?: Array<{
    title: string
    url: string
    content?: string
    engine?: string
  }>
}

async function searchApprovedDocs(query: string) {
  const response = await fetch("https://api.prismfy.io/v1/search", {
    method: "POST",
    headers: {
      Authorization: `Bearer ${process.env.PRISMFY_API_KEY}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({
      query,
      domain: "docs.example.com",
      timeRange: "month",
      page: 1,
    }),
  })

  if (!response.ok) {
    throw new Error(`Prismfy search failed with ${response.status}`)
  }

  const data = (await response.json()) as PrismfySearchResponse
  return {
    cached: data.cached ?? false,
    evidence: (data.results ?? []).slice(0, 4).map((item, index) => ({
      id: index + 1,
      title: item.title,
      url: item.url,
      snippet: (item.content ?? "").slice(0, 220),
    })),
  }
}

Once the assistant has the evidence, use a rigid instruction set:

Answer only from the approved docs evidence.
Prefer the most specific source page.
If the answer is missing, say which approved source should be checked next.

Practical notes and caveats

Approved docs should not be a vague label. Assign ownership, define review rules, and remove pages that no longer represent the product. A Q&A assistant is only as trustworthy as the source list behind it.

Use domain to keep the search inside the product’s docs site. If the answer could live in release notes, API docs, and a help article, search those categories separately so the assistant can compare them instead of collapsing them into one response.

Keep the snippets short. The model usually needs titles, URLs, and a few decisive lines, not the whole page.

When the search result set is weak, do not force an answer. Returning a careful “not found in approved docs” response is better than a confident guess.

Why Prismfy fits this workflow

Prismfy fits because it gives you a clean, auditable public search request without inventing a parallel knowledge stack. You can verify the approved docs at runtime and keep the assistant’s answer path transparent.

That is especially useful for product Q&A, where source drift is a routine risk and source discipline matters more than clever wording.

FAQ

Can a docs assistant stay docs-first and still use live search?

Yes. Keep approved docs as the primary answer source, then use Prismfy only for public verification when the assistant needs to confirm a current page, release note, or publicly documented change.

Why not let the assistant search the whole public web first?

Because support workflows need tighter control. A docs-first flow reduces noise, preserves product accuracy, and still leaves room for public-web verification when freshness matters.

Related Prismfy guides

• Build a Docs-Only Customer Support Assistant from Approved Docs
• Architect a Docs-First Knowledge Assistant with Public Verification
• Add Real-Time Web Search to an OpenAI Agent Workflow with Prismfy

Try Prismfy

Create a Prismfy key, test POST /v1/search, and wire the search step into the workflow you care about first.