Services 01
Data foundation for AI
AI is only as good as the data under it. We connect scattered sources, align definitions and build platforms that process data fast and cost less, so analytics and models can run on top.
When this fits
- Data exists but lives in thousands of spreadsheets, separate systems or unlinked files.
- Two reports show different numbers for the same metric and nobody knows which one is right.
- Your data platform costs keep growing, licences are expensive or the platform is too slow for models.
- Data must stay in your data centre, sometimes with no internet access at all.
What you have at the end
- One platform with documented sources, definitions and lineage.
- Measured processing time and running cost, before and after.
- A foundation ready for the first AI use case, with the data it needs already in place.
What we do
- 01
Connect and contextualise sources
Images, lab results, machine and system data linked to the station, product or customer they belong to. One shared source instead of many copies.
- 02
Definitions, quality and lineage
We align metric definitions, set quality checks and show where each number comes from, so analysts and AI assistants can point to the source.
- 03
Platform modernisation
Spark on Kubernetes, Trino, object storage. We migrate in stages and compare results before switching over, with a rollback plan.
- 04
Performance and cost
We tune data reads, partitioning, shuffles and queries. In a telecom project that alone made processing twice as fast.
- 05
ML-ready pipelines
Feature pipelines, model tracking in MLflow and the same foundation for analytics and machine learning.
Start with
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Questions buyers ask
Do we have to move to the cloud?
No. We build in your data centre, in the cloud or hybrid. In our telecom project everything ran on-premise with no internet access.
Can you migrate us off Cloudera or Hadoop?
Yes. We modernised a telecom platform running 900,000 jobs a week on Cloudera, rebuilding it on Spark and Trino: twice as fast, 60% lower operating costs and no Cloudera licence fees.
How do you avoid breaking reports during a migration?
We migrate in stages and run old and new side by side, comparing results job by job before each switchover. Every stage has a rollback.
What does it cost?
Start with the data platform cost review or the AI readiness assessment; both have a fixed scope and a "from" price on their pages. The full project is quoted after that, with every item justified.
Let's talk about your project
Tell us about your case
Pick one problem.
Show us the data you have.
Let's agree a measurable goal.
Name the process and the data you have. An engineer, not a call centre, gets back to you.
We reply within one business day.