RAG & Knowledge
pipeshub-ai
The open-source, permission-aware context layer that lets agents search all your company knowledge.
★ 3.8k starsApache-2.0
View guide →The semantic intelligence layer for ontologies — governed, traceable knowledge for AI agents
trustgraph is an open-source rag & knowledge project by trustgraph-ai (trustgraph-ai/trustgraph on GitHub). It has 2,787 GitHub stars and 330 forks, is released under the Apache-2.0 license, and was last updated on GitHub on 7 October 2026.
Identify the domain knowledge agents must answer about unambiguously, and bring an OWL ontology, build one, or start from a domain standard.
No clone is needed unless building from source — the config tool generates a deployment bundle for Docker, Podman or Minikube.
Run the config tool, follow the generated INSTALLATION.md, and connect your LLM provider (or a self-hosted open-weight model).
Ingest documents (PDF, DOCX, XLSX, PPTX, HTML, Markdown, CSV, images), then ask a natural-language question in the UI on port 8888.
RDF 1.2 named graphs with OWL ontology enforcement: typed entities, defined relationships and logical inference instead of fuzzy chunk similarity.
W3C PROV-O-based provenance: extraction lineage, query traces and agent behavior are stored as queryable graph data.
Converts PDF, DOCX, XLSX, PPTX, HTML, Markdown, CSV and image files into structured semantic knowledge.
A native agent runtime that traces behavior and links decisions to source knowledge, plus an API gateway for bring-your-own frameworks.
Workspaces, Collections, Flows and reusable Knowledge Cores isolate, govern and version knowledge over time.
Managed Cassandra storage, Qdrant vectors, S3-compatible object storage, Pulsar/RabbitMQ messaging, and vLLM/TGI/Ollama/LM Studio options ship with the platform.
Clone TrustGraph only if building from source; the normal deploy path is step 2.
git clone https://github.com/trustgraph-ai/trustgraph.git
cd trustgraphThe README quickstart generates an app config (deploy.zip with docker-compose.yaml or Kubernetes resources, plus INSTALLATION.md).
npx @trustgraph/configStart the generated deployment with Docker/Podman/Minikube; the TrustGraph UI serves on port 8888 by default.
# follow the generated INSTALLATION.md — see README for the exact commandtrustgraph-ai maintains it (copyright TrustGraph, 2024–2026), with docs at docs.trustgraph.ai and a Discord community.
Yes, it is Apache-2.0 licensed and self-hosted.
Almost nothing does: the README notes the only possible keys are a third-party LLM service (or self-host open-weight models instead), optional third-party OCR, and the API key you set yourself for its gateway.
The README's comparison: Neo4j is a general property-graph database with schema-optional semantics and no native provenance or ingest; TrustGraph is purpose-built as an ontology-enforced semantic layer with ingest, retrieval and agent tracing included.
Run npx @trustgraph/config, deploy the generated bundle, ingest a document, and query it from the UI on port 8888.
The open-source, permission-aware context layer that lets agents search all your company knowledge.
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Ready-to-run templates for RAG, AI pipelines and enterprise search that stay in sync with live data
Free and open — grab the source, star the repo, and start creating.