This page describes the shape of the evaluation. The step-by-step procedure is published in full on semanticdatacharter.com, across six pages: prerequisites, picking components, the on-ramps, the evaluation period, and reading the results. No account is needed to read any of it, and nothing there is behind a form.
Why evaluate now
Agents are going to read your data. Today they guess what it means.
An agent reading your data infers what each field means from whatever format it arrives in. Every agent does it, every time, and each format is one more guess. A Governed Data Record gives your agents one deterministic thing to execute against: each value is bound to a published definition that is never edited, validation is a yes or a no, and the same record checked against the same model gives the same verdict every time. Your agents should execute against what your data means, not what they guess it means.
The way most organizations hold their data makes that hard. The data sits in a shape one vendor's application defines. The vendor sets the maintenance deadlines. Moving off costs a migration priced in years, and the meaning of the data is rebuilt each time, because where the data is stored, the format it is exchanged in and the application that defines it are three different things, and someone else owns the definitions. Your next migration should be the last time you migrate meaning.
The path, end to end
Every step uses tools that are published and open. The evaluation runs each one on your data.
- Define it once. Your domain experts model what your records mean, in
SDCStudio or with
sdcmodeler, composing from 9,822 free public components (measured on production, 19 October 2026), most built from open standards: NIEM, FHIR, NIH CDE, UBL and GS1, Peppol, UN/EDIFACT, ISO 20022, FOCUS and more. If we can't model a standard, it isn't an open standard, and we are modeling every one that is, in public. - Bring your data in. SDC_Agents read one data source you already run (SQL, CSV, JSON or MongoDB) and write validated Governed Data Records. A value that is missing or unusable is recorded as such, with the reason, never guessed.
- Keep it anywhere. The records are open formats, and they live in your storage: any cloud, any document store, a bucket. The validator runs offline and depends on nothing of ours.
- Send it to the formats you exchange today.
sdc-mapperwrites the same records as OASIS UBL, UN/EDIFACT and the OMOP Common Data Model, and reports every value: placed by a lookup the model already binds, placed by a declared mapping rule, or not representable in that format. Your partners keep receiving the formats they use now. - Settle and verify. A decision made over a record produces a Receipt that
anyone can check, offline, without asking us. An optional governance track runs
sdcgovernancealongside one of your decision flows for the thirty days, with a Receipt for every decision. - Decide at day thirty, with evidence. You keep everything either way.
What you see at day thirty
The cost of your present way, priced on your own data.
Your declared count. Every value a mapping rule had to place by hand is work your organization does today, and redoes whenever a partner's rule, a profile or the standard itself changes. The report counts it, value by value, for each format.
What each format could not hold. Where a value was refused, masked or never asked, the record says so. The report shows which formats can say that too, and which turn it into an empty field.
Your validation outcomes. How many records validated as they came in, how many carried values that failed their constraints, and which constraints those were.
Where this goes
Mapping is the cost of the present. When the Governed Data Record itself is what partners exchange, the application's data model and the exchange format are the same thing: no loss of fidelity between them, no mapping to maintain, and every record verifiable by whoever receives it.
The procurement frame
The usual objection to starting is not technical and not price. It is the fear of a long commitment that ends in a disrupted production system with nothing to show for it. The evaluation is built so that fear has nothing to attach to.
- Alongside production, not in it. The agents read one source, read-only and enforced: SQL is limited to SELECT, files are never modified, and each agent is isolated to its own purpose. Nothing your existing systems do changes.
- No migration of your live systems. The records are new and additive; your systems of record stay where they are.
- No contract with Axius SDC to run it. The validator, the agents, the mapper, the governance engine and the Receipt verifier are Apache 2.0.
- Two costs. The components are free. The rest is a minimal SDCStudio account (typically under 20,000 credits, $20 worth) and your own team's time.
When an evaluation becomes a purchase, an organization account buys credits on an invoice under an order form, with a spending limit for each member and a contract term. Organization accounts are live from 25 October 2026.
What you keep
Everything the evaluation produced is yours, whatever you decide.
Your models and your records. The composed data model, its schema, and every Governed Data Record made from your source, in open formats, on your own storage.
The reports. The mapping reports for each format, the validation outcomes and, if you ran the governance track, the Receipts for every decision.
The generated app stack. You can also download an Apache 2.0 app stack scaffolded for the profile you pick: a fully open-source profile (Apache Jena/Fuseki with PostgreSQL), an enterprise profile (Graphwise GraphDB with SirixDB and Keycloak), or both. Every later app you generate imports into it, so infrastructure is procured once across the portfolio rather than once per project.