Data platforms your whole organisation can build on.

We design and deliver lakehouse platforms that are fast to change, cheap to run and trusted by the analysts, applications and AI models that depend on them.

Good platforms are boring in the best way.

Pipelines run on time. New sources take days, not months. Analysts find what they need without raising a ticket. Costs are predictable. That's the platform we aim to leave you with.

We favour simple, proven patterns: medallion layers, version-controlled transformations, automated testing and infrastructure as code. Clever is fine when it's needed, but never by default.

What we deliver

  • Target architecture and platform selection
  • Lakehouse build on Fabric, Databricks or Snowflake
  • Batch and streaming ingestion pipelines
  • Data models, semantic layers and metrics
  • Performance tuning and cost optimisation

Platform choices, explained plainly.

Unified

Microsoft Fabric

A strong fit for Microsoft-centric organisations with heavy Power BI use and lean platform teams.

Lakehouse

Databricks

Excellent for engineering-led teams, large-scale processing and machine learning on open formats.

Warehouse

Snowflake

Simple to operate and strong for SQL-first analytics and sharing data across organisations.

How a platform build runs.

  1. Assess

    Profile your sources, review existing pipelines and agree the first high-value data products.

  2. Design

    Choose the platform and patterns, and document the target architecture and standards.

  3. Build the first slice

    Deliver one end-to-end data product into production, with testing and monitoring in place.

  4. Scale

    Onboard further sources and teams on the same foundations, with your engineers increasingly in the lead.

Common questions.

Which platform should we choose?

It depends on your existing estate, skills, licensing and workloads. We'll give you an independent recommendation, and we've written a guide on one popular option: Is your organisation ready for Microsoft Fabric?

How long until we see results?

A first production-ready data product is usually possible within eight to twelve weeks. A full enterprise platform is delivered in stages over several months.

Can you work alongside our existing team?

Yes, and we prefer to. Pairing with your engineers is the fastest way to share knowledge and keep the platform maintainable after we step back.

Planning a new data platform?

We'll review your current setup and give you a clear, independent recommendation.