Robust data privacy and security measures to safeguard sensitive information and comply with regulations

DATA PRIVACY & SECURITY

Seamlessly integrates with Graph Neural Networks (GNNs) to analyze and interpret complex network structures

GNN INTEGRATION

Designed with enterprise in mind ensuring scalability, reliability, and performance for large-scale data processing and analytics

SCALABLE ARCHITECTURE

• Information Search & Retrieval
• Observability & Threat Detection
• Cross-Domain Analysis
• Transfer Learning in ML Models
• Real-time Anomaly Detection
• Explainable AI and Model Interpretability
• Automated Knowledge Graph Construction
• Contextual Recommendation Systems
• Predictive Analytics and Forecasting
• Complex Event Processing
• Data Integration & Interoperability

Potential Applications

Using transformer models, R!AN employs attention mechanisms to identify and extract meaningful relationships between entities or concepts. This process creates a comprehensive and contextually rich search space, making it easier to uncover significant connections within the data.

Attention-Based Graph Embeddings

R!AN constructs a  semantic data fabric by transforming private data into knowledge vectors, which serve as interconnected data points. These vectors act as precise pointers to relevant knowledge, enabling semantic understanding and effective data utilization.

Semantic Data Fabric