Data Services
Data and AI engineering.
Dataicraft designs the data architecture, builds the pipelines and analytical systems that run on it, and hands over a working model your team can operate and extend. The work covers the system beneath the reporting, not only the reporting itself.
What this is
Reporting defects commonly originate in the underlying data model rather than in the reports themselves, and become most expensive to correct once reporting depends on them. Engagements therefore begin at the warehouse: establishing the grain of each table, what a single row represents, which system is the authoritative source for each fact, and how conflicts between systems are resolved.
Pipeline development follows. This covers extraction from operational systems, change data capture where volumes justify it, and transformation logic held in version control and covered by automated tests rather than embedded in scheduled jobs.
Machine learning and AI work follows the same order. A model is only as good as the data underneath it, so the warehouse and the pipelines come first, and the model is built on records that are already correct and already current.
Engagements are structured to conclude. The objective is a documented system your team maintains and extends, not a continuing dependency on us.
Scope
- Data engineering
- Warehouse design, pipelines, data modelling, and integration between operational systems. This is the foundation the rest of the work depends on.
- Analytics
- Operational and analytical reporting, dashboards, and business intelligence built on a model that holds up to questioning.
- Machine learning
- Forecasting, classification, and recommendation systems trained on a business’s own operational history, including deep learning where a problem genuinely calls for it.
- Applied AI
- AI integrated into workflows people already use, rather than presented as a separate product for them to adopt.
- LLM engineering
- Custom language-model systems: assistants, retrieval over internal documents and data, and automation wired into existing applications.
How engagements run
- 01
Assessment
We review the source systems and produce a written record of the data as it currently exists, including its structure, quality, and ownership. The assessment is fixed in scope and duration, and it establishes the basis on which the remaining work is estimated.
- 02
Design and build
Warehouse design precedes pipeline development. Delivery is incremental, so that reporting against the first completed subject areas can begin before the full model is in place.
- 03
Handover
We hand over documentation, automated tests, and the working sessions your team needs to extend the system without us. Ongoing support is available where it is wanted, rather than assumed.
Next
Begin with an assessment.
The assessment is fixed in scope and duration, and produces a written record of your data as it currently stands. That document is yours regardless of whether an engagement follows.