Curiosity

Curiosity Documentation

Learn, deploy, and build enterprise AI apps on Curiosity Workspace.

Pick your path

Curiosity Workspace is our graph + search + AI platform for building AI applications on top of your own data. These docs are organized around what you are trying to do with it.

Learn Curiosity Workspace

For developers. Core concepts, schema, ingestion, search, embeddings, and the permission-aware UI. The end-to-end developer journey, APIs, and tutorials.

Deploy and manage

For administrators and SREs. Install on Docker, Kubernetes, AWS, Azure, GCP, OpenShift, or Windows. SSO, ReBAC, monitoring, backups, upgrades, and the production checklist.

Build enterprise AI apps

For platform builders. Ship domain-specific AI apps on Curiosity Workspace: custom front-ends in Tesserae, custom endpoints, AI tools, scheduled tasks, NLP pipelines, and data connectors.


Curiosity Workspace at a glance

Three layers that are usually stitched together from separate systems, delivered as a single deployable:

Graph

Typed nodes and edges with stable keys, schemas, and traversals. Used for navigation, faceting, and grounded AI.

Search

Text, vector, and hybrid retrieval with property and graph-relationship facets. Permission-aware at query time.

AI

Embeddings, NLP, LLM orchestration, AI tools, and agents — grounded in the graph and constrained by ReBAC.

Read the architecture overview See the API overview


Developer resources

Tesserae UI

Our design system. C# component library used by the Workspace front-end and by your custom interfaces.

H5 Compiler

C# → JavaScript transpiler that powers Tesserae and the Curiosity front-end.

Catalyst

Natural language processing pipeline used inside the Workspace and available as an open-source library.

Curiosity CLI

The curiosity-cli dotnet tool. Test, upload front-ends, ingest folders, sync git, and promote workspace definitions — from any shell or CI pipeline.

Open Source Projects

All open-source projects developed and maintained by Curiosity.


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