Introduction
What is NeuroVecta?
Getting Started
Logging In
Quick Create UI
Sidebar Menu
Working with Files
Vector Databases
Uploading Files
Indexing Files
Querying Documents
Citation Rationales
FAQs
Contact
Vector Databases
Understanding how NeuroVecta stores and retrieves your documents
A vector database is the foundation of how NeuroVecta understands and retrieves information from your documents. It stores documents in an AI-readable format that enables fast, accurate semantic search and AI processing.
Unlike traditional keyword-based search, vector databases understand the meaning behind your queries and can find relevant information even when the exact words don't match.
Key Concepts
Organised by Project
Documents are grouped into databases by the user, which can be aligned with projects or specific use cases. Only the selected database's documents are available to NeuroVecta at query time.
Vector Embeddings
Documents are converted into vector representations that capture their semantic meaning, enabling deep contextual understanding. Each piece of text becomes a point in a high-dimensional space where similar concepts are located near each other.
Semantic Search
When you query your documents, NeuroVecta converts your question into a vector and finds the most semantically similar content in your database. This means it can find relevant answers even when your question uses different words than the original document.
How Databases Work in NeuroVecta
Database Creation
You can create multiple databases to organise your documents by project, topic, or any other criteria that makes sense for your workflow.
Example: You might have separate databases for "Research Papers 2024", "Product Documentation", and "Legal Contracts".
Query Scope
When you start a chat session, you select which database to query. NeuroVecta will only search within that specific database, ensuring relevant and focused results.
This isolation prevents information from different projects from interfering with each other and improves response accuracy.
Real-Time Updates
When you add or remove files from a database, the changes are automatically reflected in the indexing queue. Once indexing is complete, the new content becomes immediately available for querying.
You can monitor indexing progress via the pulsing icon on the sidebar.
Best Practice
Create separate databases for different projects or document types to keep your content organised and improve query relevance. This approach helps NeuroVecta provide more accurate and focused responses.