Data platforms
Pipelines, semantic layers and governed data products that analytics and AI can trust.
We build the data foundations that reporting and AI depend on: batch and streaming pipelines, a governed semantic layer and data products with clear owners. The platform is designed to run in your environment, and your team can operate it after we leave.
Five steps from first call to handover.
- 01
Find the problem worth solving
We start with the decisions your business needs to make and work back to the data behind them, so each technical choice has a reason.
- 02
Build the foundation
We set up pipelines, storage and the logical layer on a cloud or hybrid architecture that fits your estate, with access rules from day one.
- 03
Model the data
We turn raw tables into documented, tested data products that analysts and AI applications can use without guessing what a column means.
- 04
Deploy and monitor
We move the platform into production with automated tests, alerting and runbooks, so problems are caught before your users see them.
- 05
Tune and hand over
We measure cost and performance, fix what is slow and train your team to run and extend the platform themselves.
Outcomes you can check.
- One governed view of data that was scattered across systems
- Data products your analysts and AI tools can trust
- A platform your own team can run, with runbooks
- A base that new use cases can build on without a rebuild
Related work.
Talk to an engineer about your data platform.
Thirty minutes, no slides. Tell us what you have and where it hurts.
Book a 30-min discovery call