TrustGraph

Knowledge Graphs are the backbone of trustworthy AI. Here is how to navigate this landscape, cutting through overlapping definitions and hype. The State of the Graph project recently released its most ambitious map yet: a deep dive into the Knowledge Graph Continent. It moves beyond the buzzwords to categorize the actual tools driving the industry. Here is the signal through the noise: ✓ Beyond the Graph Database: A true Knowledge Graph isn’t just about storage. It is about the management of schema, identity, and semantics. The map spans graph infrastructure providers, dedicated Knowledge Graph platforms, and Knowledge Management / Search solutions. ✓ The Semantic Bridge: We are seeing a convergence. The historical divide between the rigor of RDF and the agility of Property Graphs is narrowing as vendors adopt multi-model approaches. ✓ The RAG Revolution: GraphRAG has turned Knowledge Graphs into the "ground truth" layer for LLMs. This is no longer a niche academic pursuit; it is the infrastructure for reliable AI. ✓ Industrial Specialization: The continent is fracturing into specialized domains. From financial services to life sciences, the market is shifting from general-purpose tools to domain-specific powerhouses. The goal isn't just to list vendors. It is to provide a taxonomy for a field that has lacked one for too long. Explore the map now 🗺️ https://lnkd.in/dAuUT9z3 🔗 Follow State of the Graph for the next continents: Graph AI, Graph Engines, and Graph Application Development Stay in the loop → stateofthegraph.com What's your knowledge graph use case? #KnowledgeGraph #AI #DataArchitecture #GraphRAG #DataModeling

What are ontologies and how are they relevant to context graphs?

TrustGraph v2.2 is here — and it's our lightest weight and speediest release yet. 🚀🐇 This release is centered on a theme we've been working toward for a long time: agent flexibility without sacrificing explainability in a scalable but lightweight footprint. 🤖 Multi-Pattern Agent Orchestrator The new orchestrator uses LLM-based meta-routing to select the right execution strategy per request — Plan-then-Execute, Supervisor (parallel sub-agents), or ReAct. Every pattern is fully instrumented with RDF provenance, so you always know why your agent did what it did. Full DAG traceability, new RDF types, 96+ tests. 🐇 RabbitMQ Pub/Sub Backend TrustGraph is now decoupled from any single messaging fabric. RabbitMQ is available as an #ApachePulsar alternative with dramatically lower resource requirements (a **20%** reduction in total footprint!) — a big deal for teams that want TrustGraph's power without the infrastructure overhead. 🔍 SPARQL 1.1 Query Service Query your knowledge graph directly with SPARQL — backend-agnostic, supporting the full query feature set including GROUP BY, UNION, OPTIONAL, aggregates, and streaming for large result sets. Available via SDK, gateway, and CLI. 📄 Universal Document Decoder One service, every document format. DOCX, XLSX, PPTX, HTML, Markdown, CSV, EPUB, and more — all feeding the same pipeline with configurable chunking strategies. Plus: inline explainability triples, persistent WebSocket connections, auto-pull Ollama models, MCP gateway auth, and a new tg-monitor-prompts CLI tool. 👉 If you're building AI agents and care about determinism, explainability, and open infrastructure — TrustGraph is built for you. 🔗 https://lnkd.in/gz-GtFMP #TrustGraph #AIAgents #ContextGraph #KnowledgeGraph #OpenSource #AIInfrastructure #SPARQL #RabbitMQ

Another milestone! 🎉 🌟 Not long ago, we celebrated 1,000 🌟 — and the momentum since then has been incredible. After spening nearly an entire week trending on GitHub, we celebrate 2,000 🌟! This isn't just a vanity metric. Every star represents a developer, researcher, or builder who saw TrustGraph and thought, "yes, this is the context layer AI agents have been missing." That means everything to us. We're building the infrastructure that makes AI agents actually trustworthy — grounded in structured context, not hallucinated guesses. The fact that the community is rallying around that vision is fuel for everything we're doing next. Thank you to every contributor, early adopter, and supporter who helped get us here. The best is still ahead. 🚀 ⭐ https://lnkd.in/gz-GtFMP #OpenSource #AI #ContextGraph #KnowledgeGraph #AIAgents #TrustGraph #GitHub #Milestone

Most AI stacks hide a dirty secret: swap your LLM provider, and everything breaks. TrustGraph was built differently. TrustGraph ships with a full, modular LLM inferencing stack — so you're never locked into a single model or provider. Whether you're running fully air-gapped on-prem or mixing cloud APIs, TrustGraph has you covered out of the box. The inferencing stack supports: 🖥️ Local / Self-Hosted — vLLM, TGI, Ollama, LM Studio, and llama.cpp for full on-premises deployments ☁️ Cloud Providers — OpenAI, Anthropic, Google Gemini, AWS Bedrock, Azure OpenAI, Cohere, and more 🔧 Fully Configurable — swap providers without rewiring your entire pipeline This isn't just about flexibility. It's about control — over cost, latency, data privacy, and compliance. In regulated industries especially, the ability to keep data on your own infrastructure while still leveraging the best available models is a game-changer. TrustGraph's context graph operating system handles the heavy lifting — knowledge extraction, entity resolution, semantic retrieval — and hands off to whatever LLM you trust most. Your stack. Your rules. 👉 Check out the leading context graph operating system: https://lnkd.in/gz-GtFMP #AIInfrastructure #ContextGraphs #ContextEngineering #ContextOS #KnowledgeGraphs #LLM #TrustGraph #AIAgents #EnterpriseAI #OpenSource

TrustGraph 2 is here. 🚀 We've been building toward this: a context graph platform where every answer is traceable, every inference is auditable, and every document is connected to the knowledge it produced. TrustGraph 2 ships with: ✅ End-to-end explainability — PROV-O provenance from document to graph edge, full reasoning traces on every query ✅ RDF-star and named graph support — richer, standards-aligned knowledge representation ✅ Pluggable Tool Services — modular, dynamically registered tools for agent frameworks ✅ Batch embeddings and streaming triple queries — built for scale ✅ Workbench Explainability Panel — inspect reasoning traces right in the UI If you're building AI applications that need to know things — and prove it — TrustGraph is the context development platform for you. ⭐ GitHub: https://lnkd.in/gz-GtFMP

TrustGraph 2 is here. 🚀 We've been building toward this: a context graph platform where every answer is traceable, every inference is auditable, and every document is connected to the knowledge it produced. TrustGraph 2 ships with: ✅ End-to-end explainability — PROV-O provenance from document to graph edge, full reasoning traces on every query ✅ RDF-star and named graph support — richer, standards-aligned knowledge representation ✅ Pluggable Tool Services — modular, dynamically registered tools for agent frameworks ✅ Batch embeddings and streaming triple queries — built for scale ✅ Workbench Explainability Panel — inspect reasoning traces right in the UI If you're building AI applications that need to know things — and prove it — TrustGraph is the context development platform for you. ⭐ GitHub: https://lnkd.in/gz-GtFMP