The knowledge base is the single source of truth for your AI assistant. Every response is grounded in content that your team has curated, reviewed, and approved — the assistant never invents answers or pulls from external sources. This design ensures traceability, accuracy, and compliance.

Two Content Types

AskRAI supports two types of knowledge content, each suited to different use cases:

Both types live in the same knowledge base and are searchable together. The difference is in how they enter the system.

Content Ingestion Pipeline

When you upload a document to a knowledge pack, AskRAI processes it through an automated pipeline.

1. Upload — drag and drop files into a document-type knowledge pack. Supported formats include PDF, DOCX, PPTX, XLSX, and image files.
2. Parse — the system extracts text content, preserving page numbers and section headings.
3. Chunk — long documents are split into semantic segments that each capture a coherent unit of information.
4. Index — chunks are added to both the text search index and the vector index for semantic search.

For Q&A pairs, you write the question and answer directly — no pipeline needed. Q&A pairs are indexed immediately after creation.

Knowledge Packs

Knowledge packs are containers that group related content together. Each pack has a content type (Q&A or Document) chosen at creation, and content within a pack shares the same lifecycle and access controls.

Packs serve two purposes:

• Organization — group content by topic, department, or use case (e.g., "HR Policies", "Building Permits", "IT Self-Service")
• Access control — groups reference knowledge packs to control which users can access which content

Content Lifecycle

Every knowledge item follows a status workflow that controls whether it appears in search results:

Only Approved content appears in user-facing AI responses. This ensures that every answer the assistant gives comes from vetted, curator-approved material.

Two Search Modes

AskRAI offers two ways to search the knowledge base:

• Text Search — keyword-based search that matches exact terms in questions, answers, and document content. Fast and predictable.
• AI Search (semantic) — meaning-based search that finds relevant content even when the wording differs from the query. Uses vector embeddings to match by concept rather than keywords.

Both modes are available to curators in the admin console and to the AI assistant at runtime. The assistant uses whichever mode (or combination) is configured for your tenant.

Next Steps

• Knowledge Base — create and manage Q&A pairs and document chunks
• Knowledge Packs — organize content into collections and upload files
• Guardrails — understand how safety rules protect knowledge-based responses
• Access Control — learn how groups control access to knowledge packs