Enterprise data platforms that pay back in production.
We deploy Snowflake, Databricks, Microsoft Fabric and Palantir Foundry end to end, and stay until the business runs on them. What you pay for is the result: numbers every team trusts, AI working on your own governed data, and a platform bill you can forecast.
Six things that change once it is live.
The platform is how we get there. This is what people across the business notice.
Pipelines replace the monthly extract and the spreadsheet that quietly became a system of record. The figure is ready while it can still change the decision.
We move what people actually use, run old and new side by side until the numbers match, then switch the old estate off, so you stop paying for both.
Roles, masking, lineage and an audit trail are set up from the first day. Who saw what, and where each number came from, can be shown rather than reconstructed.
Four platforms. We pick the one that fits the job.
We do not resell licences, so our recommendation is only about fit. Often the right answer is one platform at the core and a second where it earns its place.
Best when analytics and data sharing come first.
Best when heavy data engineering and machine learning come first.
Best when the business already runs on Microsoft.
Best when the platform must run operations, not just report on them.
Prove one outcome first. Then scale.
- Step 01
We choose on fit, not on brand
Where the work sits, what your team already knows, what you already pay for and what the board needs to see. The platform choice follows from that, and we write the reasoning down.
- Step 02
We land the foundation properly
Accounts, identity, networking, environments and infrastructure as code, so the platform is secure and repeatable from the first day rather than tidied up later.
- Step 03
We prove one outcome on live data
One real business question answered end to end before we scale. It tells you whether the design holds, while changing course is still cheap.
- Step 04
We run it, or hand it over
Monitoring, cost control, upgrades and support, or a clean handover to your own team. Success is a platform people open every day, not one delivered and left alone.
What is an enterprise data platform?
The system a business keeps its data in so everyone reads the same numbers: it collects data from your tools, cleans and models it once, controls who can see what, and feeds reports, AI and operational applications from that single source. Snowflake, Databricks, Microsoft Fabric and Palantir Foundry are the four we deploy.
It is the foundation under data and analytics, business intelligence and artificial intelligence. Not sure which platform, or whether you need one yet? Start with tech consulting or the What is an AI readiness assessment?.
Which platform should we choose?
It depends on where the work sits. Snowflake suits analytics and data sharing, Databricks suits heavy data engineering and machine learning, Microsoft Fabric suits businesses already running on Microsoft, and Palantir Foundry suits platforms that must run operations rather than only report. We recommend on fit for the job you describe, and sometimes the answer is a mix.
Do you resell Snowflake, Databricks, Microsoft Fabric or Palantir Foundry?
No. You buy the platform licence directly from the vendor, in your own account. We design, deploy and run it. That keeps the recommendation about fit rather than commission, and the platform stays yours if you ever move on from us.
Can you migrate us off our current warehouse or reporting tool?
Yes. We move the data, rebuild the reports people actually use on agreed definitions, run old and new side by side until the numbers match, then switch the old one off. Migration is planned in the same roadmap as the deployment, not left as a second project.
How quickly will we see a result?
We aim to answer one real business question end to end on live data before the wider build starts, so you see value early and can redirect cheaply. How long that takes depends on how many sources are involved and the state of the data, and we scope it on a short call.
Who is this for?
Organisations whose data is spread across systems and spreadsheets, whose reports disagree, or who want AI but do not have data that is ready for it. You do not need a data team in place, and you do not need to have picked a platform before you call.
Tell us what you need your data to do.
Send a few details and we’ll set up a short call to scope it and give you a tailored quote. No obligation, no hard sell.