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Knowledge Base / FAQ — Multi-locale Articles, Attachments & AI Search | Velaxe

Knowledge Base / FAQ

Knowledge Base / FAQ vs Atlassian Confluence

Confluence is a great wiki & doc hub. Velaxe KB/FAQ is a purpose-built knowledge system for instant answers, hybrid retrieval, localization, and deflection analytics—with import from Confluence to keep content in sync.

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Who this comparison is for

Teams whose wiki became the KB by accident Support orgs seeking deflection metrics and search quality Ops needing embeddable, locale-routed answers

Knowledge Base / FAQ highlights

  • KB-specific authoring, taxonomy, and locale routing
  • Search tuned for Q→A with vectors + re-ranking

Atlassian Confluence highlights

  • Strong internal documentation spaces & hierarchies

Capability matrix

5 rows
Capability Knowledge Base / FAQ Atlassian Confluence Notes
Q→A schema & FAQ editor Full Partial Confluence is page-centric
Hybrid search tuned for queries Full Partial Velaxe kNN + FTS
Embeddable help widget Full Add-on 3rd-party apps in Confluence
Import from Confluence Native n/a Connections → Confluence
Deflection & search analytics Full Partial Purpose-built KPIs
  • Keep Confluence for specs/runbooks; use Velaxe for external/internal FAQs and help centers.

Total cost of ownership

Reduce agent time and repeated answers by moving FAQs to Velaxe while retaining Confluence for long-form docs.

Assumptions

  • Mix of internal wiki + external KB needs

Migration plan

From Confluence · Connector import → Tag/locale map → Publish

  1. 1

    Connect Confluence space(s)

  2. 2

    Map labels→tags; convert macros to HTML/Markdown

  3. 3

    Publish drafts; enable widget/help center

Security

  • Granular RBAC; content export/deletion flows

Evidence & sources

Claim Value Source
Confluence import Spaces/pages to drafts with attachments product_docs

About Knowledge Base / FAQ

Knowledge Base / FAQ is an enterprise-grade knowledge system for teams to author rich articles, attach images/videos/files, tag them for easy discovery, and localize content by locale. Users get instant answers via hybrid search: classic full-text (FTS) plus semantic vector retrieval with embeddings.

Editors benefit from autosave, clean Markdown/HTML authoring, tag chips, and attachment management. Ops can choose the embedding model and enable a nightly drift job that re-embeds older content as models improve—keeping search results fresh and accurate.

The app is workspace-native, so your data lives with your workspace, behind Velaxe RBAC and audit logs.

Import a Confluence space demo