Our Technology

Explore the advanced technology stack that powers our knowledge graph and RAG solutions, delivering unparalleled data intelligence.

Knowledge Graphs

Advanced graph database technology for complex relationship modeling

Vector Databases

High-performance vector search for semantic similarity matching

AI Integration

Seamless integration with leading LLMs and AI frameworks

Architecture Overview

Explore the technical architecture behind our solutions and understand how each component works together to deliver powerful data intelligence.

Knowledge Graph Architecture

Our knowledge graph architecture creates a comprehensive representation of entities and relationships within your data ecosystem, enabling complex queries and insights discovery.

Graph Database

Core storage layer optimized for relationship data using Neo4j, TigerGraph, or Amazon Neptune.

Ontology Layer

Defines the structure, relationships, and rules that govern your knowledge domain.

Data Integration

ETL pipelines that transform and load data from various sources into the graph structure.

Query Engine

Specialized query processing for traversing relationships and extracting insights.

Visualization Layer

Interactive interfaces for exploring and analyzing the knowledge graph.

Knowledge Graph Architecture

Technology Stack Explorer

Dive into the technologies that power our solutions and understand their capabilities and use cases.

Graph Databases

Our graph database technologies provide the foundation for storing and querying complex relationship data.

N

Neo4j

Industry-leading graph database with powerful query capabilities using the Cypher query language.

Key Features:
  • ACID transactions
  • Horizontal scaling
  • Native graph storage
  • Rich query language (Cypher)
T

TigerGraph

Scalable graph database optimized for deep link analytics and machine learning applications.

Key Features:
  • Parallel graph processing
  • GSQL query language
  • Distributed architecture
  • Real-time deep link analytics
A

Amazon Neptune

Fully managed graph database service by AWS supporting both property graph and RDF models.

Key Features:
  • Fully managed service
  • High availability
  • Multiple graph models
  • Integration with AWS ecosystem
J

JanusGraph

Distributed graph database with multi-datacenter high availability and flexible storage backend.

Key Features:
  • Elastic and linear scalability
  • Multiple storage backends
  • Gremlin query language
  • Transaction support

Feature Comparison

See how NexusGraph's technology stack compares to traditional database solutions and basic RAG implementations.

Feature
N
NexusGraph
T
Traditional DB
B
Basic RAG
Data Capabilities
Structured Data Support
Unstructured Data Support
Relationship Modeling
Semantic Understanding
Multi-modal Data
Query & Retrieval
Keyword Search
Semantic Search
Graph Traversal
Hybrid Retrieval
Context-aware Queries
AI Integration
LLM Integration
Contextual Grounding
Reasoning Capabilities
Automated Knowledge Extraction
Continuous Learning

Interactive Technology Demo

Explore how our technology works through these interactive visualizations.

This visualization demonstrates how knowledge graphs connect entities through relationships, enabling complex queries and insights discovery. You can see how different entities like Person, Company, Project, Skill, and Location are interconnected, allowing for powerful path-based queries and relationship analysis.

Ready to Harness the Power of Our Technology?

Discover how our advanced knowledge graph and RAG solutions can transform your organization's data ecosystem and unlock new possibilities.