Semantic Data Charter
AI cannot run your business until the meaning of your business is modeled. Someone has to build that model. Today it gets built inside a vendor's platform, and it stays there. You rent it.
Axius SDC does it the other way. We turn the databases you already have into governed data assets, with meaning and provenance bound to the payload, in open standards, in your own store, on your own infrastructure. You own the meaning layer. And you can prove it.
The question that is left
Everyone now agrees the meaning layer is what makes AI work on your data. The only question left is who owns it.
The platform way
Their engineers build the meaning layer for you, per customer, inside their proprietary software. Your raw data is copied out of your source systems, so the data itself is not what holds you. The ontology, the business logic and the workflows are, and there is no export for them.
Deploying it on your premises keeps your data behind your walls. The meaning still lives in their software. That is location sovereignty, not ownership sovereignty.
The Axius SDC way
Your domain experts model the meaning once, as reusable components you keep. SDC_Agents turn your existing datastores into validated, signed SDC data in open formats and deliver it into the store you already run, including your graph database or triplestore.
The meaning and the governance are bound to the payload and expressed in open standards, so they survive the platform. Swap the graph database, the LLM or the hardware underneath without a replatform.
What you get
01 · Model
Define your data models in SDCStudio with constraints bound to the data, so there is no interpretation drift between the people who know the domain and the systems that use it.
02 · Validate
sdcvalidator and
sdcgovernance enforce constraints at runtime.
Every payload is checked against its model, so compliance is structural rather than
aspirational.
03 · Deploy
Run SDCStudio Sovereign on-premises for air-gapped environments, or use the cloud platform. Either way the meaning layer is yours, in open standards, and it stays yours if you ever leave.
Proof
The creed is that we never claim what we cannot prove. So this section is identifiers, not adjectives. Each one resolves without asking us for anything.
Specification
The SDC4 Reference Model, in W3C XSD 1.1. There is no private format.
Validator
Apache-2.0, on PyPI. Install it and check our work without an account.
Paper · substrate economics
Deterministic CPU-bound validation modeled against inference-based governance across scale. A modeling study, not a measurement.
Paper · governed execution
Constraint-state evidence and governed execution at the AI deployment boundary.
Ontology alignment
How SDC maps to Basic Formal Ontology, written down rather than asserted.
Distribution
SDC_Agents ships in Google's official Agent Development Kit community toolset, reachable by any developer on the ADK Python framework.
Who it is for
Regulated, classified or sovereign environments where the workload has to run air-gapped and the vendor cannot be in the loop at runtime.
You are evaluating a semantic layer and you want to know what you keep if you leave. Ask for the export path before you sign, not after.
You are putting LLMs against your own data and you need the same evidence to produce the same verdict every time, not a plausible answer that moves.
Thirty days, your own data, and a written answer on what it would take to make your meaning layer yours.