Organizations often struggle with fragmented data across disparate systems, hindering comprehensive analysis and the discovery of critical relationships. This data siloing impedes timely decision-making and the ability to gain a unified understanding of complex information landscapes.

GraphAware provides GraphAware Hume, a connected data analytics platform designed to break down data silos and create a unified view of intelligence. The platform ingests and structures data into a knowledge graph, enabling intuitive navigation and exploration of complex datasets. This approach accelerates the identification of hidden relationships and patterns, ultimately empowering organizations to enhance safety, security, and trust by delivering on their missions more effectively.

GraphAware Hume Platform: A connected data analytics platform built on graph technology for comprehensive intelligence analysis.

Data Ingestion and Workflow Engine (Hume Orchestra): Supports streaming and batch data processing with a drag-and-drop interface for designing custom data workflows.

Entity Resolution: Automates the identification and linkage of disparate data points representing the same real-world entity using configurable rules or third-party services.

Unstructured Data Processing: Leverages Large Language Models (LLMs) within the platform to extract entities and relationships from text-based intelligence reports and enrich the knowledge graph.

Advanced Visualization Engine: A WebGL-based library for rendering complex graph visualizations, optimized for performance and user interaction.

Graph Data Science Integration: Incorporates graph algorithms for advanced analytics, including influencer analysis, node classification, link prediction, and graph clustering.

Collaborative Features: Enables sharing of insights through snapshots, contextual notes, comments, and Action Boards for report generation in various formats.

Role-Based Access Control (RBAC): Provides granular control over data access at entity, relationship, and attribute levels to ensure data security and compliance.

Python 3 Support: Allows execution of native Python code in message transformers and filters, with management of third-party libraries via a UI.

Geospatial and Temporal Analysis: Features a new map engine with split-view capabilities, proximity clustering, and synchronized map and graph views for enhanced spatial and temporal investigations.

The primary target audience includes law enforcement agencies, financial authorities, national security organizations, and cyber defense companies that require advanced analytics to process and understand complex, interconnected data.