GH Repository · trustgraph-ai
trustgraph
The context orchestration layer powered by hypergraphs. Build a unified semantic context layer where agentic outcomes are deterministic and agent behavior is not just traceable, but cryptographically verifiable.
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pythonmakehelp-wantedhypergraphworkflow-automationgraph-engineeringdeterminismcontextPythonontologyopen-sourcegraphagent-appagent-harnessknowledge-graphcontext-orchestrationowlexplainable-aiagentcontext-harnessrdfcontext-graphcontext-engineering
TrustGraph is an open-source Python toolchain that provides a context orchestration layer built on hypergraphs. It aims to create a unified semantic context layer in which agentic outcomes are deterministic and agent behavior is traceable and cryptographically verifiable.
You reach for it when you want agent context grounded in an ontology-backed knowledge graph with deterministic, verifiable behavior rather than opaque LLM flows.
Use it to
- Build a unified semantic context layer for agents
- Model context with hypergraphs, RDF, and OWL ontologies
- Trace and verify agent behavior deterministically
- Automate agent workflows with a context harness
For Developers building verifiable, ontology-driven agentic systems
- Role
- agent-app
- Language
- Python
- Licence
- Apache-2.0
- Forks
- 320
- Open issues
- 17
- Last push
- 2026-09-16
topicsknowledge-graphcontext-orchestrationhypergraphagentsontologydeterminism