Vector Knowledge Base FAQs

Question 1

What types of documents can I upload?

Accepted Answer

It supports a wide array of formats including PDF, DOCX, PPTX, XLSX, CSV, images (with OCR), TXT, Markdown, and various code files (Python, JavaScript, C#), ensuring comprehensive document ingestion.

Question 2

What is Vector Knowledge Base?

Accepted Answer

Vector Knowledge Base is a personal semantic search engine that converts your documents into an intelligent, searchable knowledge base using vector embeddings and advanced AI algorithms for conceptual understanding.

Question 3

Can Vector Knowledge Base help organize my documents automatically?

Accepted Answer

Yes, it features 'Auto-Clustering' using HDBSCAN and TF-IDF to automatically group similar documents into semantically meaningful clusters and even generate descriptive names for them.

Question 4

How does semantic search differ from keyword search?

Accepted Answer

Semantic search finds documents by understanding the meaning and context of your natural language queries, going beyond exact keyword matches. It uses vector embeddings to grasp conceptual relevance, not just literal terms.

Question 5

How does AI Agent Integration work?

Accepted Answer

Via the Model Context Protocol (MCP), Vector Knowledge Base allows AI agents (like Claude Desktop) to programmatically interact with your knowledge base, enabling them to search, create, and manage documents efficiently.

Vector Knowledge Base

Vector Knowledge Base

Key Features

Use Cases

Key Features

Use Cases