trustgraph-ai/trustgraph
The context interoperability 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. observed · 2026-08-28
Health v2 · maintenance only
68/100
- Activity 99
- Release rhythm 35
- Longevity 56
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 784
- days_rel: n/a
- days_push: 9
- n_releases_24m: 0
Adoption not part of the score
2616 stars · 308 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
TrustGraph is an open-source context interoperability layer that builds unified semantic context layers using hypergraphs, knowledge graphs, and vector embeddings for agentic AI. It provides deterministic, traceable, and cryptographically verifiable agent behavior with GraphRAG, explainability, and multi-tenancy deployed via Docker or Kubernetes.
Use cases
- build graphrag pipelines over enterprise documents
- reduce llm hallucinations with knowledge graph context
- make ai agent decisions explainable and traceable
- run self-hosted sovereign ai without external api keys
- query documents with automatically extracted knowledge graphs
- deploy open weight llms on own infrastructure
- build context-aware agents with ontologies
When to choose
- you need deterministic, auditable agent behavior for mission-critical workloads
- you want graph-enhanced rag instead of plain vector similarity search
- you require self-hosted deployment with open weight models and no external api keys
- you need explainability tracing answers back to sources
- you want multi-tenancy with iam and gateway authentication
When to avoid
- you just need simple vector similarity search without graph structure
- you want a lightweight library to embed in an existing app rather than a platform
- you cannot operate docker or kubernetes deployments
- you need a fully managed saas with zero infrastructure
Facets
framework · maturity active
rag agent-framework llm-inference workflow-automation search-engine vector-database artificial-intelligence large-language-models self-hosted python self-hosted cloud windows hypergraph context-engineering graphrag ontology explainable-ai rdf sparql deterministic-agents sovereign-ai open-weight-models knowledge-graph ai-agents retrieval-augmented-generation knowledge-graphs enterprise-ai docker kubernetes linux macos
6 sources
- readme: https://github.com/trustgraph-ai/trustgraph · fetched 2026-08-28 · 5affec8815e5
- homepage: https://TrustGraph.ai · fetched 2026-08-29 · 3c105d5c84f5
- site_page: https://docs.trustgraph.ai · fetched 2026-08-29 · d7a15c563cfb
- registry_pypi: https://pypi.org/pypi/trustgraph/json · fetched 2026-08-29 · 77fdc6dbff35
- site_page: https://trustgraph.ai/ · fetched 2026-08-29 · 3c105d5c84f5
- site_page: https://trustgraph.ai/integrations · fetched 2026-08-29 · 685908650290
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| trustgraph-ai/trustgraph | main | 68 |
For agents
markdown · JSON · MCP: product_card(name="trustgraph-ai/trustgraph")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem