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Knowledges

Knowledge bases in Vectense Platform provide contextual information to AI models, enabling them to make informed decisions based on your organizational data and documents.

Overview​

Knowledge bases store and organize information that AI models can reference during workflow execution. They enable:

  • Context-Aware AI: Provide relevant information to AI models
  • Document Processing: Index and search through document collections
  • Intelligent Retrieval: Find relevant information based on queries
  • Organizational Memory: Preserve and access institutional knowledge
  • Content Understanding: Extract insights from unstructured data

Quick Navigation​

Knowledge Source Types​

File Bucket​

Upload documents directly through the web interface:

  • Supported Formats: PDF, Word, Excel, Text, RTF, Markdown
  • Drag & Drop Interface: Easy file management
  • Automatic Processing: Files are indexed automatically
  • Version Control: Track document updates and changes

Local Filesystem​

Connect to file systems and network drives:

  • Directory Monitoring: Watch for file changes
  • Pattern Matching: Filter files by type and name patterns
  • Recursive Scanning: Process entire directory trees
  • Real-time Updates: Automatically index new and modified files

Web Content​

Crawl and index web pages and documentation:

  • Website Crawling: Extract content from web pages
  • Depth Control: Set crawling depth and limits
  • Content Extraction: Convert HTML to structured text
  • Update Scheduling: Refresh web content periodically

Key Features​

Intelligent Indexing​

  • Vector Embeddings: Convert text to searchable vector representations
  • Semantic Search: Find content based on meaning, not just keywords
  • Multi-language Support: Process content in multiple languages
  • Content Chunking: Break large documents into manageable segments

Retrieval System​

  • Similarity Search: Find most relevant content for queries
  • Context Ranking: Prioritize results based on relevance
  • Result Filtering: Apply filters to narrow search results
  • Performance Optimization: Fast retrieval even for large datasets

Content Processing​

  • Text Extraction: Pull text from various document formats
  • Metadata Preservation: Maintain document properties and structure
  • Content Validation: Verify document quality and completeness
  • Error Handling: Gracefully handle processing failures

Integration​

  • Workflow Integration: Use knowledge in AI workflow steps
  • API Access: Programmatic access to knowledge content
  • Real-time Updates: Keep knowledge current with source changes
  • Monitoring: Track usage and performance metrics

Knowledge Workflow Integration​

Context Injection​

Knowledge bases provide context to AI models:

  1. Query Generation: AI determines what information to retrieve
  2. Knowledge Search: System finds relevant content
  3. Context Assembly: Relevant content is formatted for AI
  4. AI Processing: Model uses context to generate informed responses

Use Cases​

Document Analysis

  • Extract information from contracts and invoices
  • Summarize research papers and reports
  • Compare documents for similarities and differences

Customer Support

  • Answer questions using knowledge base content
  • Provide consistent responses based on documentation
  • Route inquiries based on content classification

Content Generation

  • Create summaries from multiple sources
  • Generate reports using organizational data
  • Produce content that follows company guidelines

Decision Support

  • Provide background information for business decisions
  • Compare options using historical data
  • Generate recommendations based on past experiences

Performance and Scaling​

Indexing Performance​

  • Batch Processing: Efficiently process large document sets
  • Incremental Updates: Only process changed content
  • Parallel Processing: Use multiple workers for large collections
  • Resource Management: Balance performance with system resources

Search Performance​

  • Vector Optimization: Optimized vector similarity calculations
  • Caching: Cache frequent queries for faster response
  • Result Limits: Control result set sizes for performance
  • Index Optimization: Regular optimization of search indexes

Storage Management​

  • Compression: Efficient storage of vector embeddings
  • Cleanup: Remove outdated or unused content
  • Archival: Long-term storage of historical content
  • Backup: Protect knowledge base data

Security and Privacy​

Access Control​

  • Role-Based Access: Control who can view and modify knowledge
  • Workspace Isolation: Knowledge bases are workspace-specific
  • Content Filtering: Filter sensitive content from results
  • Audit Logging: Track access and usage patterns

Data Protection​

  • Encryption: Encrypt knowledge content at rest and in transit
  • Privacy Controls: Respect document privacy settings
  • Data Retention: Configurable retention policies
  • Compliance: Support for regulatory compliance requirements

Source Security​

  • Credential Management: Secure storage of access credentials
  • Network Security: Secure connections to external sources
  • Input Validation: Validate all content before processing
  • Malware Protection: Scan content for security threats

Monitoring and Analytics​

Usage Metrics​

  • Query Volume: Track knowledge base usage
  • Response Times: Monitor search performance
  • Content Popularity: Identify most-accessed content
  • User Patterns: Understand how knowledge is used

Quality Metrics​

  • Retrieval Accuracy: Measure search result relevance
  • Content Freshness: Track how current knowledge content is
  • Processing Success: Monitor document processing success rates
  • Error Rates: Track and analyze processing failures

Cost Tracking​

  • Processing Costs: Monitor indexing and embedding costs
  • Storage Costs: Track storage usage and growth
  • API Usage: Monitor external API calls for web content
  • Resource Utilization: Track compute resource usage

Best Practices​

Content Organization​

  • Consistent Structure: Organize content logically
  • Clear Naming: Use descriptive names for documents and sources
  • Regular Cleanup: Remove outdated or irrelevant content
  • Version Control: Track document versions and changes

Performance Optimization​

  • Content Quality: Ensure high-quality source content
  • Regular Updates: Keep content current and relevant
  • Index Maintenance: Regularly optimize search indexes
  • Monitoring: Continuously monitor performance metrics

Security Management​

  • Access Reviews: Regularly review access permissions
  • Content Audits: Audit content for sensitive information
  • Security Updates: Keep systems updated with security patches
  • Incident Response: Have plans for security incidents

Getting Started​

Prerequisites​

Before creating knowledge bases:

  • Active Workspace: Access to workspace with knowledge creation permissions
  • AI Models: Configured models for embedding generation
  • Content Sources: Documents or data sources to index
  • Understanding: Basic familiarity with your content and use cases

Quick Start Guide​

  1. Learn the Basics: Understand knowledge base concepts
  2. Add Your First Knowledge: Create and configure a knowledge source
  3. Test Retrieval: Validate that knowledge works correctly
  4. Integrate with Workflows: Use knowledge in your automations
  5. Monitor and Maintain: Keep knowledge current and optimized

Common Patterns​

Document Repository

  • Upload company documents and policies
  • Create searchable knowledge base
  • Use in customer service and training workflows

Website Documentation

  • Crawl product documentation websites
  • Keep knowledge synchronized with updates
  • Provide context for technical support

File System Integration

  • Monitor shared network drives
  • Automatically index new documents
  • Provide context for document processing workflows

Troubleshooting​

Common Issues​

  • Slow Indexing: Large documents or network issues
  • Poor Search Results: Content quality or query formulation
  • Processing Failures: Unsupported formats or corrupted files
  • Access Problems: Permission or authentication issues

Performance Issues​

  • Index Optimization: Regular maintenance of search indexes
  • Content Pruning: Remove irrelevant or outdated content
  • Resource Scaling: Adjust resources for processing demands
  • Query Optimization: Improve search query effectiveness

Content Quality​

  • Format Validation: Ensure supported document formats
  • Content Review: Verify content quality and relevance
  • Duplicate Detection: Identify and handle duplicate content
  • Error Analysis: Review processing errors and failures

Support Resources​

  • Documentation: Comprehensive guides for all knowledge features
  • Community Forum: User discussions and shared solutions
  • Video Tutorials: Step-by-step video guides
  • Expert Support: Technical support for enterprise users

Ready to create your first knowledge base? Start with Introduction to understand the concepts, then proceed to Add Knowledge for hands-on creation.