TrustGraph AI ingests data from multiple sources such as web crawlers, social media platforms, CRM systems, and spreadsheets. Its AI-driven engine processes content sentiment and connection metadata to build interactive trust graphs. Users can explore network structures, identify weak links or suspicious clusters, and assign configurable risk thresholds. Customizable dashboards display live metrics and alerts, enabling proactive brand safety management, fraud detection, and reputation monitoring across digital ecosystems.
TrustGraph AI Core Features
Automated trust graph generation
Entity relationship mapping
Configurable risk scoring
Anomaly detection engine
Real-time monitoring and alerts
Customizable dashboards
Data import & API integration
Collaboration and sharing tools
TrustGraph AI Pro & Cons
The Cons
The Pros
Open-source platform providing transparency and trust.
Supports deployment on cloud, on-premises, or local hardware enhancing sovereignty.
Integrates with all major LLM providers for maximum flexibility.
Utilizes graph-driven intelligence for improved accuracy and reduced hallucinations.
Supports containerized deployment for scalable and customizable configurations.
Enables full control and real-time reconfiguration of AI agent parameters.
Helps enterprises avoid vendor lock-in and provides full AI stack sovereignty.