The domain data model
The model describes the customers, orders, projects, employees, assets, and other objects your company works with. Each term has one definition and a clear governance rule that your operators recognize.
Service: AI-Ready Data Foundation
FOUR TO EIGHT WEEKS / FIXED SCOPE
Domain data modeling, ETL pipelines, and AI data readiness.
Build the data foundation your AI work needs.
We define a domain data model, reconcile the source systems behind it, and build pipelines to keep the records current. Shugyo and other AI tools can then work with data your team trusts.
Book a fit call
Download the data readiness checklist
Starts from EUR 15k for four to eight weeks. We finish when the agreed dashboards use the same definitions and figures.
01
WHO THIS IS FOR
This engagement is for teams whose AI work has stalled on unreliable data.
- 01 Two dashboards report different figures for the same measure, with no agreed source of truth.
- 02 Your CRM and ERP use different definitions of a customer.
- 03 A Claude, ChatGPT, or internal copilot pilot stalled because the team could not trust its data.
- 04 After a reorganization, acquisition, or new business line, nobody can explain how the data fits together.
These problems usually point to the data layer, even when responsibility for it is spread across several teams.
02
WHAT YOU GET
What your team receives.
Cleaned canonical sources
The source of truth for each domain object is documented. We reconcile conflicting records and record which system wins when values differ.
The pipelines
We build the ETL, ingestion, and reconciliation pipelines that keep the canonical sources current. They use standard tools and come with enough documentation for your team to change them.
The runbook
The runbook explains what to do when data drifts, a new source appears, or the model needs to grow. Your team can maintain the data layer after the engagement ends.
03
HOW THE ENGAGEMENT RUNS
A typical six-week engagement.
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Weeks 1-2With your team
Define the model.
We work with the people responsible for operations, finance, and engineering to define the domain data model. Together, we resolve conflicting definitions with the relevant owner.
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Weeks 3-5Our synthesis
Build the pipelines.
We reconcile the records and build the pipelines that update the canonical sources. We use your existing tools where they fit and write maintainable code for the remaining work.
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Week 6With your team
Hand over operations.
We deliver the runbook and transfer operational ownership to your team. If useful, we can stay on a small retainer for the next thirty days.
04
THE GRADUATION PATH
How the work supports Shugyo.
At handoff, your team owns all four deliverables and can operate the data layer without us.
Shugyo can use the domain model and canonical data as its semantic layer. Once that foundation is in place, a Shugyo implementation typically takes weeks.
05
THE MAP
AI pilots often expose problems in the data: conflicting definitions, stale records, or unclear ownership. The problem becomes visible when the model returns an answer nobody can verify.
EmpoweredHouse / AI-Ready Data Foundation
06
PRICING
Starts from EUR 15k.
The final price depends on the number of source systems, requirements for data residency or PII handling, and the delivery pace.
Source systems
More sources, more reconciliation.
Regulatory weight
Data residency and PII handling.
Delivery pace
Parallel delivery costs more than sequential work.
We set the price during the fit call. If the data layer is already healthy, we will recommend that you leave it alone.
07
THE FIT CALL / 30 MIN
Use the fit call to check whether data is the place to start.
The call takes thirty minutes. Bring examples of the sources and reports that disagree, along with the name of the person responsible for them. We will tell you whether this engagement fits the problem.