trustgraph

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The open-source ontology runtime for AI agents

Your ontology. Your agents. Your rules.

Every platform now sells you an ontology. TrustGraph is the one you own.

For enterprises deploying AI agents where decisions carry real risk, TrustGraph is the open-source ontology runtime that turns your documents and data into ontology-grounded knowledge, and governs what every agent and user can see from it.

Unlike other platform ontologies, TrustGraph is built on W3C standards (RDF, OWL, SHACL, PROV-O) for total ownership and portability of your knowledge and business logic. Your ontology, your knowledge, and your audit trail stay yours, portable across any cloud, model or deployment.

How it works

            Your ontology                       Your documents & data
                 │                                       │
                 └──────────────────┬────────────────────┘
                                    ▼
                         ┌──────────────────────┐
              1. EXTRACT │     OntologyRAG      │  Triples match classes and properties,
                         │                      │  checked against constraints
                         └──────────┬───────────┘
                                    ▼
                         ┌──────────────────────┐
              2. GROUND  │    Context Graph     │  RDF knowledge in named graphs,
                         │                      │  with PROV-O lineage to every source
                         └──────────┬───────────┘
                                    ▼
                         ┌──────────────────────┐
              3. GOVERN  │  SHACL-AF Policies   │  Every query evaluated per node:
                         │                      │  Allowed · Filtered · Violation
                         └──────────┬───────────┘
                                    ▼
                     GraphRAG · SPARQL · Agents · MCP
           + a queryable trace of how each answer was produced

Additional Technical Diagrams

What makes it different

Core capabilities

1. Own it: open standards, portable knowledge

• Knowledge is stored as RDF, including language tags, XSD datatypes and RDF-star quoted triples.
• Load knowledge as Turtle or TriG (named graphs preserved); export the graph as Turtle.
• Package knowledge into Context Cores that carry triples, embeddings, provenance and source documents between deployments.
• Move whole workspaces between deployments with portable .tgx bundles (tg-export-workspace / tg-import-workspace).

2. Use it: ontology to knowledge

• OntologyRAG uses your ontology to guide extraction. A similarity-based selector picks the relevant part of the ontology for each chunk, with a bypass mode for small ontologies.
• Extracted triples are validated against ontology domain and range constraints, including the subclass hierarchy. Triples that break the rules are rejected.
• rdf:type attributes are stored with graph embeddings, so you can filter vector searches by entity type.
• Schema-free GraphRAG and hybrid (BM25 + vector) DocumentRAG are also available, both with cross-encoder reranking.

3. Govern it: policy-based query filtering (new in 2.10)

• Write access policies as SHACL-AF shapes, stored in the urn:graph:policy named graph.
• Every graph query is evaluated node by node with a tri-state result: Allowed, Filtered or Violation.
• Policies apply across the REST API, SPARQL and GraphRAG, using a per-request user context.
• Each evaluation publishes a structured policy.evaluation audit event.
• With no policies loaded, the system runs in open mode.

4. Steer it: guided graph traversal (new in 2.10)

• Supply grounding seeds or graph seeds to skip LLM concept extraction.
• Restrict each hop by type, relationship or named graph, and filter edges by language tag.

5. Prove it: explainability

• Extraction emits PROV-O lineage from document to page, chunk and edge (urn:graph:source).
• GraphRAG, DocumentRAG and agent queries record full reasoning traces (urn:graph:retrieval).
• Inspect them with tg-show-explain-trace and tg-show-extraction-provenance, or query them with SPARQL.

6. Decide fast (new in 2.10)

• Decision Scoring (Laya, ONNX Runtime, ~35 ms per call): pick an option, score on an ordered scale, or get a yes/no confidence.
• Cloze Classification: auto-train a DistilBERT classifier from labeled examples and serve it with confidence scores.

Agents and APIs

• Agent orchestrator with ReAct, Plan-then-Execute and Supervisor patterns.
• MCP server with tools for graph queries, SPARQL, GraphQL over structured data and embeddings, with bearer-token authentication.
• SPARQL 1.1 query service with 30+ built-in functions and streaming results.
• REST, WebSocket, Python SDK, TypeScript libraries and a full tg-* CLI.

Quickstart

No need to clone the repo unless you are building from source. TrustGraph deploys as a set of Docker containers. Configure it on the command line in one step:

npx @trustgraph/config

The config process will generate an app config that can be run locally with Docker, Podman, or Minikube. The process will output:

• deploy.zip with either a docker-compose.yaml file for a Docker/Podman or resources.yaml for Kubernetes
• Deployment instructions as INSTALLATION.md

For a browser based configuration, try the Configuration Terminal.

Standards support

Note on scope: TrustGraph uses OWL ontologies to guide extraction and to check domain, range and subclass constraints. It is not a full OWL reasoner. See the Ontologies docs for details.

Integrations

• LLMs: All major LLM APIs, including OpenAI and compatible providers, Claude, Gemini (GCP and AI Studio), Near AI, AWS Bedrock, Azure, Mistral, Cohere, Ollama, vLLM, LM Studio, TGI and llama.cpp
• Messaging: Apache Pulsar or RabbitMQ (Kafka experimental)
• Storage: Cassandra (graph), Qdrant (vectors), S3-compatible object storage
• Documents: Docling decoder for PDF, DOCX, XLSX, PPTX, HTML, Markdown and CSV
• Deployment: Docker / Podman Compose, Minikube, Azure AKS, GCP, AWS, Scaleway, OVHcloud; amd64 and arm64 images; Nvidia, AMD, and Intel GPU support
• Security: IAM with JWT and API keys, workspace multi-tenancy, fine-grained capabilities

Getting Started with TrustGraph

• Getting Started Guides
• Build an App
• Developer APIs and CLI
• Deployment Guides

TypeScript Library for UIs

There are TS libraries for quick UI integration of TrustGraph services.

Contributing

Developer's Guide

License

TrustGraph is licensed under Apache 2.0.

Copyright 2024-2026 TrustGraph

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

   http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

Support & Community

• Bug Reports & Feature Requests: Discord
• Discussions & Questions: Discord
• Documentation: Docs