What is OneNode?

AI-Native

Built for LLM applications with semantic understanding at its core

Multimodal

Search across text, images, and structured data with natural language

Unified

One platform for documents, vectors, and objects—no complex integrations

How It Works

OneNode uses a two-step process to enable semantic search across all data types

STEP 1

Content Analysis

Images are analyzed by vision models to generate descriptive text. All content is normalized into a text representation.

🖼️
Images
📝
Text
STEP 2

Semantic Embedding

All text content is converted into semantic vectors that capture meaning, enabling intelligent cross-modal search capabilities.

📝
Text
🧠
Vectors

Architecture

Three storage layers unified under a single API

Document Store

MongoDB-compatible JSON document storage with flexible schemas

Vector Search

High-performance semantic search with embedding models

Object Storage

Scalable file storage with automatic content analysis

Why OneNode

Developer Experience

Single API for all data operations
MongoDB-compatible query syntax
Built-in AI processing pipelines

Application Capabilities

Semantic search across all content types
Natural language query interface
Automatic content understanding