Policies & Playbooks

Roll out policy changes people actually follow

Ship a policy update once; every answer reflects it immediately.

The pain

You updated the travel policy in March, and in September people still book under the old rules — the announcement email is buried, the wiki page is bookmarked at the old URL, and answers from colleagues carry the outdated version forward indefinitely.

How BeforeQuery solves it

With BeforeQuery, the policy document is the single source of truth: update it, sync the source, and every subsequent answer reflects the new rules with a citation to the current version. Gap and question analytics show which policy areas generate the most confusion after a change, so comms can target the follow-up where it's needed.

How it works

1Keep the policy document as the single source of truth in its existing home — wiki, Drive, or an uploaded PDF.
2Update the policy and sync the source; BeforeQuery re-indexes the new version.
3Every subsequent answer reflects the new rules, with a citation to the current document.
4Watch question analytics after the change to see which areas generate confusion.
5Target follow-up comms at the topics people are actually asking about.

What you get

One policy update propagates to every future answer immediately after sync.

No more stale answers circulating through bookmarks and hearsay.

Post-change confusion is measurable, not anecdotal.

Comms effort goes where question data says it is needed.

Features that make it work

Scheduled source syncs

Always-current answers

Citations to the live policy

Question & gap analytics

Frequently asked questions

How fast does an updated policy show up in answers?

As soon as the source re-syncs. Wiki and drive sources sync on a fixed schedule (typically every 5–10 minutes for Notion, Confluence, Drive, and SharePoint), and website sources can be synced manually — after which answers retrieve only the new version.

Can we see whether people understood the change?

Question analytics and knowledge gaps show what employees ask after a rollout and where the assistant lacked confident answers — a direct readout of which parts of the change landed and which need follow-up.

How long does setup take?

Most teams are live the same day. You connect a source — a docs URL, GitHub repo, Notion workspace, or a file upload — and BeforeQuery crawls, normalizes, chunks, and embeds the content automatically. The website widget is a single script tag, and the Slack/Discord bots install in a few clicks. There is no model to fine-tune and no infrastructure to run.

Are answers backed by citations?

Yes. Every answer includes a structured citations list with the URL, title, and excerpt of each source used, and the answer text cites sources inline. Users can click through to verify any claim against the original document — which is what makes the answers trustworthy enough for support, sales, and internal use.

Is my content used to train AI models?

No. Your indexed content, embeddings, and conversations are isolated to your workspace and are only used to answer your own questions. Content is never shared across customers, and data is encrypted at rest and in transit. Enterprise plans add OIDC/SAML SSO, audit logs, and data-residency options.

Which knowledge sources can I connect?

18+ source types: websites, GitHub, GitLab, Notion, Confluence, Google Drive, SharePoint, Shopify, Zendesk, Jira, Linear, Salesforce, Slack, Discourse, Stack Overflow, YouTube, OpenAPI specs, and direct file uploads (PDF, Markdown, TXT, HTML). Sources sync on a schedule, and GitHub/GitLab can re-index automatically via webhooks on every push.

What happens when the AI is not confident in an answer?

Answers are confidence-scored. When retrieval confidence falls below your threshold, BeforeQuery returns a transparent, configurable fallback — typically pointing users to your support channel — instead of guessing. Those unanswered questions are logged in knowledge gap analytics so you can close the gap in your docs.

Does BeforeQuery work in languages other than English?

Yes. BeforeQuery answers in the language of the question while retrieving from your knowledge base, even if your docs are English-only, with citations back to the original pages. Workspace analytics break questions down by language so you can see which markets are asking what.