Knowledge Base

The knowledge base is where your content lives — the documentation, policies, product guides, FAQs, and internal runbooks that your AI bots search when answering customer questions and that your agents browse when they need a quick reference. This guide covers creating and organizing collections, uploading content, scoping collections to specific bots, maintaining content quality over time, and using knowledge base feedback signals to improve bot performance.

Overview

The RapiDesq knowledge base serves three audiences:

Content is organized into collections — named groupings of articles that you can scope bots to. A billing bot attached only to the billing collection searches only billing content; a general support bot might be attached to multiple collections for broader coverage. This scoping is what lets you run focused, high-quality bots rather than one mega-bot with a giant undifferentiated content blob.

Collections

A collection is a named group of related articles. To create one, navigate to Admin > AI > Knowledge Base > Collections and click Create Collection.

Field Description
Name An internal name for the collection (e.g., "Billing & Payments", "Product Tutorials", "Security & Compliance"). Shown in admin views and in bot configuration.
Description A short description of what's in the collection. Useful for admins choosing which collections to scope a bot to.
Visibility Whether the collection is private (used only by AI bots and agents) or published as part of a customer-facing help center. You can change this later without losing content.
Locale The primary language of the content. Used for search tuning and for matching bots serving specific languages. A collection can have content in multiple languages, but a primary locale helps the system route queries appropriately.

Common collection patterns

Collections should be coarse, not fine

Too many tiny collections become a management burden and make it hard to scope bots cleanly. A good rule: if a bot would need access to more than 3–4 collections, you probably have too many. Aim for 5–15 collections total across the whole tenant, each covering a meaningful topic area.

Adding Content

Content enters the knowledge base in several ways, each suited to different sources.

Direct authoring

The built-in editor lets you write articles directly in RapiDesq. Each article has a title, body (rich text with headings, lists, tables, images, and links), metadata (tags, category, last-updated date), and an optional "verified by" field showing who last reviewed the content for accuracy.

Use direct authoring when content lives natively in RapiDesq and doesn't exist elsewhere — typical for customer-facing help articles you create specifically for support.

File upload

Upload existing documentation in common formats. Supported at launch:

Uploaded files are automatically parsed into articles. Headings become article boundaries when the document contains multiple topics; a single-topic document becomes one article. You can review and split or merge the resulting articles before they go live.

Bulk import

For large-scale migrations from existing help centers or documentation platforms, bulk import accepts a structured archive (typically a zip of Markdown files with front-matter for metadata, or an export from a supported platform). Bulk import preserves structure, metadata, and internal cross-links; broken external links are flagged for review.

API ingestion

For content that's authored and maintained outside RapiDesq (for example, in a Git-backed documentation system, a Notion workspace, or a CMS), the knowledge base API lets you keep RapiDesq's copy in sync. A scheduled job or a webhook from the source system pushes updates; RapiDesq replaces the corresponding article content while preserving its identity, ratings, and attached bot associations.

This is the right pattern when:

Article Structure

Every article has a small set of fields that affect how bots and agents find and use it.

Field Purpose
Title Short, specific description of what the article covers. Good titles are searchable and unambiguous: "How to update your billing email" beats "Billing" every time.
Summary One or two sentences summarizing the article. Surfaces in bot citations and in search results. Worth writing intentionally rather than auto-generating.
Body The full article content. Supports rich text, lists, tables, images, code blocks, and internal links to other articles.
Tags Free-form labels used for filtering and organization. Examples: "billing", "enterprise", "common-issue", "troubleshooting".
Last verified A date and optionally a user, indicating when the content was last reviewed for accuracy. Articles that haven't been verified recently are flagged in quality reviews.
Status Draft, Published, or Archived. Only Published articles are searchable by bots and agents. Archived articles are kept for history but excluded from search.

Scoping Content to Bots

Every AI bot is attached to one or more collections. The bot can only answer from content in those collections. Scoping is configured in the bot's Knowledge Base section.

Scoping patterns

Scope tradeoffs

Narrower scope produces higher quality answers on the topics covered but refuses more out-of-topic questions. Broader scope answers more questions but with less precision. The sweet spot is usually a small number of specialized bots (narrow scope) combined with one general-purpose bot (broad scope) as a fallback.

Scope is a quality lever

When customers report that a bot is giving bad answers, don't just blame the bot or the content — look at the scope. A bot scoped too broadly gets confused by irrelevant content. A bot scoped too narrowly refuses legitimate questions. Adjusting scope is often the fastest quality fix.

Maintaining the Knowledge Base

A knowledge base without maintenance decays. Products change, policies evolve, new issues emerge, and stale content actively hurts bot quality. Plan for ongoing maintenance from the start.

Regular reviews

Set a cadence for reviewing the knowledge base — typically monthly for high-traffic content, quarterly for everything else. The admin dashboard surfaces:

Feedback signals

Every bot response includes thumbs-up and thumbs-down feedback from customers, plus a mechanism for customers to say what was wrong. These signals aggregate per article:

Identifying content gaps

The knowledge base dashboard tracks questions the bot escalated because it couldn't find relevant content. These are your content gaps. Patterns of questions without matching articles tell you exactly what to write next. "We keep getting questions about import failures but have no article about them" is a concrete content project with known demand.

Updating articles

When you update an article, RapiDesq preserves its identity (the URL, the bot citations, the history) while updating the content. Pending conversations don't change — if a bot cited the old content five minutes ago, that citation still points to what the bot actually used. New conversations after the update use the new content.

Optional: Public Help Center

Collections with their visibility set to public can be published as a customer-facing help center at a configurable URL (typically help.yourcompany.com or a subdirectory of your main site). The help center shows articles organized by collection, with search, and styled to match your brand. Customers can browse or search without authenticating.

A public help center complements the AI bot — it gives customers a self-service option before they start a conversation, and it gives the bot content a public URL that can be shared in replies and cited in conversations. Exposure is optional; many RapiDesq customers keep their knowledge base private and use it only for the AI bots and agents.

Best Practices

Write for answering questions, not for presenting

A knowledge base article that the AI bot uses well looks different from a marketing landing page. Short, direct, one topic per article. Use concrete headings that match the questions customers actually ask ("How do I reset my password?" beats "Password Management"). Put the answer in the first paragraph and add detail below for readers who want more.

One topic per article

An article that covers three loosely-related topics will be cited for all three but answer none of them cleanly. Split multi-topic articles into focused single-topic articles. Link between them when they're related.

Keep articles current or archive them

An outdated article with the wrong information is worse than no article at all — it gives the bot misleading content to ground answers on. If you can't keep an article current, archive it. The bot won't cite archived content.

Match collection structure to how you want to scope bots

Collections are the unit of bot scoping. Organize content into collections that reflect how you want bots to access it. If you want a billing-only bot, make sure billing content is a single well-defined collection, not scattered across a dozen.

Review content gaps weekly

The list of questions the bot couldn't find answers for is the most valuable input you'll have on what to write next. Review it weekly, even for 15 minutes, and file a ticket or task for the top 1–3 gaps. Over a few months this compounds into dramatically better bot coverage.

Lean on citations, don't hide them

The bot cites its sources by default. Don't configure it to hide that. Customers trust answers more when they can click through to the source, and your team can audit every answer against its source. Hiding citations would be a short-term perception gain and a long-term trust cost.