Q&A over your OpenAPI reference
Ask 'which endpoint updates a subscription?' and get the answer.
Your OpenAPI reference has hundreds of endpoints, and developers scroll and Ctrl-F to figure out which one they need, what auth it requires, and what a valid payload looks like. Reference docs describe endpoints, but nobody wrote the connective 'how do I…' tissue.
BeforeQuery ingests your OpenAPI spec as a first-class source type, indexing endpoints, parameters, and schemas. Developers ask questions in natural language — "which endpoint cancels a subscription and what scopes does it need?" — and get precise, cited answers combining the spec with your guides.
How it works
- 1Connect your OpenAPI spec as a source — endpoints, parameters, and schemas are indexed.
- 2Add your guides and tutorials so retrieval combines reference with how-to content.
- 3Developers ask in natural language: 'which endpoint cancels a subscription and what scopes does it need?'
- 4Answers cite the relevant spec entries and guide sections together.
What you get
Features that make it work
Frequently asked questions
How is the OpenAPI spec indexed?
OpenAPI is a dedicated source type: the spec is parsed and indexed at the level of endpoints, parameters, and schemas, so retrieval can pinpoint the specific operation a question is about rather than a whole reference page.
Does it handle spec updates?
Yes — trigger a re-sync (or schedule one) whenever the spec changes, and the index re-embeds the affected content. Answers reflect the current spec after the sync completes.
Can answers combine the spec with prose docs?
Yes. Retrieval is unified across all sources in the project, so an answer can cite both the endpoint definition from the spec and the relevant walkthrough from your guides.
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.
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