What is a Knowledge Base?
Knowledge Bases in Noxus are intelligent data repositories that enhance AI capabilities with domain-specific information. They process and store information in a way that makes it readily accessible for AI operations, maintaining context and relationships between different pieces of information.Content Types
| Type | Supported Formats | Description | Use Cases |
|---|---|---|---|
| Documents | PDF, DOCX, PPTX, TXT, RTF, HTML, Markdown | Text-based content that can be processed and indexed | Documentation, guides, policies, presentations |
| Data | CSV, JSON, XML | Tabular and structured data formats | Data analysis, configuration files, structured content |
| Images | JPEG, PNG | Visual content that can be analyzed and indexed | Diagrams, charts, visual documentation, screenshots |
| Archives | ZIP | Compressed files containing multiple documents | Bulk document uploads, archived content |
| EML (RFC822) | Email messages with metadata and attachments | Email archives, communication records |
Metadata Support: All file types support custom metadata fields that can
store additional information such as author, department, creation date, tags,
or any custom attributes relevant to your organization. This metadata enhances
search capabilities and provides richer context for AI operations.
Core Capabilities
Knowledge Bases offer extensive configuration options and capabilities to optimize performance for your specific use case:| Configurationdd | Options | Description |
|---|---|---|
| Search Methods | Semantic, Keyword, Hybrid, Hybrid with Reranking, RRF Hybrid | Configure how content is searched and retrieved |
| Embedding Models | Text Embeddings, Multimodal Embeddings | Choose AI models for content understanding |
| Data Sources | Documents, Google Drive, OneDrive, Website | Control allowed content sources |
| Ingestion Settings | Processing methods, chunking strategies | Customize how content is processed and stored |
Search Methods
Semantic Search - Uses vector embeddings to understand the semantic meaning of content, enabling natural language understanding beyond keywords, context-aware search results, and conceptual relationship matching. Best for complex queries and concept discovery. Keyword Search - Uses BM25 ranking for fast, precise text matching with exact term matching and relevance scoring. Provides fast performance for large datasets and precise results for specific terminology. Hybrid Search - Combines semantic understanding with keyword precision using score fusion techniques. Offers balanced results for diverse query types with configurable fusion methods (RRF, relative scoring) and optional AI-powered reranking.Accessing Knowledge Bases
Knowledge Bases offer multiple interfaces for access and management, each suited to different use cases:- 🖥️ Platform Interface
- 🔌 API Integration
- ⚡ SDK Implementation
- 🤖 Co-workers
- Flows
Our web-based platform provides an intuitive interface for comprehensive knowledge management:
- Upload and organize documents with drag-and-drop simplicity
- Monitor system usage and track performance metrics
- Configure different search methodologies
- Real-time search and content preview capabilities
Perfect for content managers and teams who need comprehensive knowledge management with full visibility into system performance.
Next Steps
- Learn about Co-workers
- Explore Flows
- Review best practices