Cadelic Orbit is an enterprise wiki that maintains itself.
Orbit reads your invoices, contracts, email and chat into one structured knowledge graph, then works from it. It runs on your own hardware, so nothing goes to a model provider you did not choose.
In private development. Cloud invites open in batches.
Every action Orbit takes is an entry in an append only ledger. The graph is what those entries build.
Context is scattered by default.
The decision is in an email, the number is in a spreadsheet, the reason is in a chat thread nobody will search. No single person, and no single model, has ever seen all three at once.
Retrieval is not understanding.
Pointing a model at your documents returns passages. It does not return a company. Orbit resolves the entities first, so the model reads a structure rather than a search result.
Most AI tools require you to send everything away.
The standard architecture for enterprise AI is to upload your commercial history to somebody else's infrastructure. Orbit is built to run where your data already is.
Arbitrary formats in
/capture pipelines accept PDFs, mail, exports and chat logs
One name per thing
Canonical entity resolution collapses variants to a single node
Graph, not documents
A local, file based knowledge graph the model can traverse
Agents work from state
Agents run under explicit system prompts in AGENTS.md, and every run is logged
Sites is a satellite, not a second product. It is a web compiler you can use on its own, and every site you build with it writes structured context back into Orbit: the copy, the components, the commit history, the decisions. Satellites exist to feed the core.
Local
Runs entirely on your machine. Inference runs on Apple Silicon or local GPUs.
- ↳Nothing leaves your network boundary
Private cloud
Deployed to your AWS or GCP environment. You hold the keys.
- ↳Outbound connections only to specified model providers
Managed
Hosted by us in UK or EU data centres.
- ↳Zero-retention inference APIs
What is true today
Working now
In build
Planned
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