RAG Engine
Advanced AI

Knowledge Graph: Connect the Dots

Understand relationships between concepts for more intelligent responses.

The Isolated Knowledge Problem

Traditional RAG treats documents as isolated islands. Connections between concepts are lost, leading to fragmented and incomplete answers.

How Knowledge Graph Works

1

Entity Extraction

Our system automatically identifies key entities and concepts from your documents.

2

Relationship Mapping

Connections between entities are detected and stored in a graph structure.

3

Contextual Retrieval

Queries leverage both vector and graph search for more comprehensive results.

Why Knowledge Graph Matters

Deep Understanding

Your AI understands how concepts are connected in your knowledge domain.

Complex Queries

Answer multi-hop questions that need to connect multiple pieces of information.

Knowledge Discovery

Discover hidden connections and insights in your data.

Improved Accuracy

Context-aware retrieval reduces hallucinations and errors.

Knowledge Graph Capabilities

FeatureRAG EngineChatbaseCustomGPTDify
Entity Extraction
Partial
Relationship Mapping
Multi-hop Reasoning
Graph Visualization
Partial

Based on publicly available feature lists as of 2024

Perfect For

R&D

Connect research findings, patents, and technical documentation.

Compliance

Track connections between regulations, policies, and procedures.

Enterprise Organization

Understand relationships between people, teams, and projects.

Product Catalogs

Connect products, features, categories, and customer needs.

Ready to Experience This Feature?

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