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Knowledge Base

The knowledge base is the foundation of Appilot's intelligence. Unlike generic AI assistants, Appilot's answers come from organization-curated content, not free-form model generation.

Knowledge content​

Each piece of knowledge is:

  • Authored by your organization — not AI-generated
  • Scoped to a domain and URL pattern — so it's relevant to specific pages
  • Versioned and publishable — draft → published workflow

Example​

{
"title": "How to complete the insurance claim form",
"content": "Step 1: Enter the policy number (found on your insurance card)...",
"domain": "claims.insureco.com",
"url_pattern": "/new-claim",
"status": "published"
}

When a user is on claims.insureco.com/new-claim and asks a question, the AI receives this knowledge as grounding context.

Scoping: Domains and URL patterns​

Knowledge is matched to the user's current page:

DomainURL PatternMatches
app.example.com/registerExact page
app.example.com/settings/*Any settings subpage
app.example.com*Any page on the domain

More specific patterns take priority over general ones.

The demand-driven loop​

Appilot creates a feedback loop between users and knowledge teams:

User asks question
│
├─── Knowledge exists → AI answers with grounded content
│
└─── Knowledge missing → User creates a request
│
Knowledge team sees request
│
Team creates/publishes content
│
User is notified ← ─ ─ ─ ┘

This means your knowledge base is driven by actual user demand, not guesswork about what to document.

RAG files​

In addition to authored knowledge content, organizations can upload documentation files (PDFs, SOPs, manuals) that the AI can reference:

  • Files are processed, embedded, and stored
  • When a user asks a question, relevant file chunks are retrieved
  • The AI uses both knowledge content and file context for answers

See RAG Files for management details.