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To meet the demands of enterprises, a platform needs to enable multi-tenancy, user and agentic access controls, data management, and total data privacy. TrustGraph enables these capabilities with:
- **Flows and Flow Classes -> Multi-tenancy**. Flow classes are sets of processing components that can be combined into logically separate flows for both users and agents.
- **Collections -> User/agent access controls and data management**. Collections enable grouping data with custom labels that can be used for limiting data access to both users and agents. Collections can be added, deleted, and listed.
- **Tool Groups -> Multi-agent**. Create groups for agent tools for multi-agent flows within a single deployment.
- **Knowledge Cores -> Data management and data privacy**. Knowledge cores are modular and reusable components of knowledge graphs and vector embeddings that can serve as "long-term memory".
- **Fully Containered Platform with Private Model Serving -> Total data privacy**. The entire TrustGraph platform can be deployed in any environment while managing the deployment of private LLMs for total data sovereignty.
- **No-LLM Knowledge Graph Retrieval -> Deterministic Natural Language Graph Retrieval**. TrustGraph does *not* use LLMs for knowledge graph retrieval. Natural language queries use semantic similarity search as the basis for building graph queries without LLMs enabling true graph enhanced agentic flows.
- **Flows and Flow Classes -> Multi-tenancy**. *Flow classes are sets of processing components that can be combined into logically separate flows for both users and agents.*
- **Collections -> User/agent access controls and data management**. *Collections enable grouping data with custom labels that can be used for limiting data access to both users and agents. Collections can be added, deleted, and listed.*
- **Tool Groups -> Multi-agent**. *Create groups for agent tools for multi-agent flows within a single deployment.*
- **Knowledge Cores -> Data management and data privacy**. *Knowledge cores are modular and reusable components of knowledge graphs and vector embeddings that can serve as "long-term memory".*
- **Fully Containered Platform with Private Model Serving -> Total data privacy**. *The entire TrustGraph platform can be deployed in any environment while managing the deployment of private LLMs for total data sovereignty.*
- **No-LLM Knowledge Graph Retrieval -> Deterministic Natural Language Graph Retrieval**. *TrustGraph does *not* use LLMs for knowledge graph retrieval. Natural language queries use semantic similarity search as the basis for building graph queries without LLMs enabling true graph enhanced agentic flows.*
## Why TrustGraph?