The Hypergraph Content Studio for Semantic Data Products.
Build portable model-based semantic hypergraphs for reference data, taxonomies and structured graphs.
TerminusDB data products use a guarded model to ensure accurate and high quality model-based structured data.
- Build and share information and data model
- Cloud hosted for TerminusDB datalog engine
- Version control, portability, and collaboration
We have a growing customer base and maintain TerminusDB since 2025. View our interactive demo, or sign up today to get started!
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Core technology: Hypergraph Content Studio
Tired of your messy data? No problem.
With the Hypergraph Content Studio, we enable technical professionals to transition from tabular data to model-based portable structured data that evolve as needs change.
The Content Studio brings the a git-for-data software collaboration model to data, advanced RDF linked data modelling, and safe to edit parallel workspaces with version history.
- Proper governance needs great tooling
When navigating complexity and governance challenges, you need flexible graph data management capabilities like branching, cloning, and merging of data so you can move fast, experiment and simulate the future without breaking things. We bring true data product collaboration, all the way down to the data layer!
With the Twinfox Platform, we enable you to easily structure and process information as accurate, visual and make use of linked data in no time.
- Built-in Semantic Layer
Our semantic data product hosting capabilties for logical twins is provided securely and professionally on AWS with an enterprise high performance option in the Azure cloud.
We commercially license and extend the TerminusDB open source knowledge graph engine that provides key open source functionalities for collaboration and linked data storage, and enables you to avoid vendor lock-in as you can always clone and pull the data product to run elsewhere.
You can even store your data locally with TerminusDB on your laptop for offline use cases and to transport data products, and model such local logical twins through our data portability layer.
- Facts and 100% correct AI (to a set of rules)
The built in data structure modeller helps you build accurate directed hypergraphs, type taxonomies and ontologies collaboratively and visually including advanced capabilities such as multiple inheritance. The data products adhere to RDF principles including global content-addressable type-checked objects, and even a document-oriented JSON-LD Framing query interface.
Of course it has APIs, with a GraphQL and an AI datalog engine for reasoning and path queries, and logical metadata! What's not to like?
- Be effective, keep it simple, save time
Start simple with built-in templates and our simple and connected getting started logical twin. Use data-driven forms and YAML instead of JSON-LD when you author Markdown as Wiki-styled content to keep things neat.
DFRNT Logical Twins cover use cases up to and including advanced enterprise semantic knowledge graphs. But works for any linked data, like how we use DFRNT as a CMS for our own blog content, categories and links.
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Next Steps
Let's get started!
Getting started is easy. We include what you need to get started with cloud-hosted model-based structured data products.
Specify, build, use and share hierarchical nested records. Export visualisations, connect using GraphQL and REST APIs and navigate complex information easily.
Get started by signing up for onboarding through the link below, and we'll set you up with a demo and free trial.
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