Features
Explore TrustGraph’s comprehensive feature set designed for building intelligent, context-aware AI agents.
Automated Context Graph Construction Transform raw data into interconnected context structures with ontology-driven context engineering
Context Cores Reusable, modular context bases that can be dynamically loaded and removed at runtime
3D GraphViz Visualization Interactive three-dimensional exploration and analysis of graph relationships
Relationship Analysis Deep inspection of connections and dependencies within your context bases
Single & Multi-Agent Systems Support for various agent configurations from simple single agents to complex multi-agent orchestration
MCP Interoperability Native integration with Model Context Protocol for seamless external tool connections
Custom Workflows Runtime-adjustable flow creation with dynamic parameter modification
Intelligent Context Retrieval Precision-grounded information extraction for highly accurate AI responses
Vector Search Semantic similarity searching across your entire context base for contextually relevant results
GraphRAG Interface Graph-enhanced retrieval-augmented generation combining context graphs with vector search
Direct LLM Chat Unmediated language model interactions for flexible conversational experiences
Multi-Modal Queries Support for text, structured data, and semantic queries across different data types
Natural Language to GraphQL Converts natural language questions into structured GraphQL queries automatically
OCR Pipeline Support Built-in optical character recognition for processing documents, images, and scanned materials
High-Throughput Streaming Efficient large-scale data ingestion with Apache Pulsar for real-time processing
Customizable Chunking Adjustable document segmentation algorithms optimized for your data and use case
Multi-Format Support Process PDFs, documents, structured databases, APIs, and unstructured data sources
Multi-Cloud Support Deploy on AWS, Azure, Google Cloud, OVHcloud, Scaleway, or any Kubernetes environment
Fully Containerized Complete Docker-based deployment model for consistency across all environments
Run Anywhere Flexibility From local development to on-premise data centers to enterprise cloud deployments
Single Command Deploy Launch your entire agent infrastructure with docker compose in seconds
Multiple Graph Stores Choose from Neo4j, Apache Cassandra, Memgraph, or FalkorDB for your graph database
Vector Database Options Built-in support for Qdrant (default), Pinecone, Milvus, and other vector stores
Multi-LLM Support Integration with Anthropic, OpenAI, Google VertexAI, AWS Bedrock, and 40+ other providers
Enterprise Connectors Pre-built connectors for databases, APIs, cloud storage, and enterprise systems
Prometheus & Grafana Integration Comprehensive monitoring dashboards with pre-configured metrics and alerts
Telemetry Tracking Track latency, error rates, throughput, and cost metrics across your entire system
Audit Logging Complete audit trails for compliance, debugging, and performance analysis
Cost Monitoring Real-time tracking of LLM API costs, compute usage, and infrastructure expenses
Data Sovereignty Keep your data in your chosen region or on-premise for regulatory compliance
Native Multi-Tenancy Isolated namespaces, separate resource allocation, individual quota management, and security boundary enforcement per tenant
Access Control Fine-grained RBAC, SSO integration, and multi-factor authentication support
Open Source Transparency Full source code access for security audits and compliance verification
Configuration Builder Assembles all selected components and builds them into a deployable package
UI Integration Libraries Three libraries for quick UI integration of TrustGraph services into your applications
Deterministic Queries Template-driven SPARQL and vector similarity search eliminate fragile query synthesis
Built-in Resilience Pulsar pipelines replay and recover automatically, keeping systems responsive during failures or rolling updates