Model how your business works. Govern the changes you make to it.
The Studio builds the model, the Explorer answers from it, the Change Orchestrator runs your initiatives on it, and the Compute Engine does the computing underneath.
Documents in, answers out.
The inputs are documents you already hold: procedures, policies, system inventories, org charts. Connecting the systems underneath is optional. Where you do connect them, the model is tied to the actual schemas, code and interfaces.
- Procedures, policies and regulations
- Systems list and schema exports
- Org chart and approval matrix
- Product and service definitions
- Programme and milestone plans
- Source code
- Database schemas
- API definitions
- Data pipelines and lineage
Documents alone are enough to start. Connect these and the model notices when they change.
Any initiative, run on the model: model the change on the transformation map, then charter it and drive it to work packages through two gates.
Every question answered from the model, with the evidence attached: impact, enforcement, ownership, dependency.
You model the business domain by domain. Each domain can then be linked to the systems that run it, so a change underneath shows up as a flag.
The domains together are the model. Same set of types every time; the domains adapt to what the client is.
- What breaks if we retire this
- Whether a rule is actually enforced
- Who signs, and on what evidence
- What a change breaks, before you commit
- Where work actually gets stuck
The compute under all three: it reads your sources, builds the links, checks the rules and signs the proof.
No other tools provide this.
The platform works out what each element would look like if it were real in your systems, then measures your material against that. Same material, same links, every time.
Nothing changes a live system without two signatures, held by two different people, with no way to route around it. The AI drafts and never signs.
When a work package deploys, the model updates in the same step. There is no separate documentation task. EA tools lag, catalogues age, and no adjacent category closes this loop.
For contrast: EA tools are hand-drawn, and rot. Data catalogues know tables without knowing meaning. RAG retrieves text but cannot prove what it found, and it has no way to compute what is missing. Every claim here traces to the paragraph, the schema line or the function in the code, checked structurally. 1,957 deterministic tests guard the behaviour that must never vary.
Four products, one model.
Each one has its own page. The model is the thing they share: built once, and read by the other three.
You scope the domains. The platform reads your material and proposes what it found, and what your experts confirm is the model.
Explore Coherence ExplorerAsk and seeAsk it, and the answer names its sources. Test a change and see what it touches before you commit.
Explore Coherence Change OrchestratorGovern changeAny initiative modelled on the transformation map, then driven through two gates to the work packages that land it.
Explore Coherence Compute EnginePerform the calculationThe compute under the other three. Nobody opens it directly, and it is what makes the same material give the same answer every time.
ExploreHow it runs once it is yours is on the operating page.
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