Data Foundations & Analytics

Data foundations your reports and AI can rely on

We bring your company data into one place, model it so each number means the same everywhere, and build the dashboards on top. One source of truth for your reports today, and the foundation for analytics and AI tomorrow.

Start a project

See our work

Organisations we've built for

Best for

When a data foundation is the right move

If your reporting looks like one of these, the problem is usually underneath the dashboards.

Numbers that don't match

Every report shows a different number, and meetings start with an argument about which one is right.

One agreed definition for each metric, in one data model that every report uses.

Data in silos

Sales, finance and operations data sit in separate tools and spreadsheets.

Pipelines that bring them into one place on a schedule, with checks on every run.

Manual reporting

Someone spends days every month copying exports into a spreadsheet.

Reports that refresh on their own, with the logic written down instead of kept in one person's head.

Getting ready for AI

You want AI on your company data, but the data is scattered and nobody trusts it.

Clean, documented data with clear access rules first, so an AI project starts on solid ground.

What you get

What your data foundation includes

Built so the numbers are right, stay right and can be traced back to where they came from.

Data pipelines

Data from your systems loaded on a schedule, with checks that flag missing or broken data.

Data model

Your key metrics defined once, agreed with the business and used by every report.

Dashboards

Reports for the questions your teams actually ask, in the reporting tool you choose.

Data quality

Tests on the data itself, so a wrong number is caught before it reaches a report.

Every project includes

Your data in your own cloud or warehouse

Every metric defined and documented

Pipelines with tests and alerts

A handover your team can run

How we deliver

From scattered data to one source of truth

The same three steps as every project we run, starting with the questions your reports must answer.

Plan

We list the decisions and reports that matter, find where the data lives and agree the definitions. You get the data plan, the risks and a list of what we won't build.

Thin slice

One report built end to end first, from the source to the dashboard, so you can check the numbers early. Then the next source, slice by slice, with a demo every week.

Launch and handover

Pipelines monitored, definitions documented and your team trained, so the numbers stay right after we hand over.

How we work

Security and data

Your data, under your control

A data foundation holds the data your company runs on. It's built so every access is clear and traceable.

Access by role.

People see the data their role needs, personal data only where it's required, and every access is logged.

Personal data minimised.

Personal data left out or pseudonymised wherever a report doesn't need it.

It stays in your environment.

Your data stays in your own cloud or warehouse, and we work in it under a data processing agreement, and every engineer can sign an NDA if you want one.

How we protect your data

Sectors and technologies

Where we've built, and what we build with

Sectors

Our engineering team has built the reporting for hospital, savings and credit, and shareholder management systems, where managers decide on the numbers every day.

Healthcare

Financial services

Logistics & mobility

Public sector & geospatial

Technologies

Widely used tools your team can hire for. We agree them with you, and work in yours if you already have them.

SQL

Python

PostgreSQL

Power BI

AWS

Azure

FAQ

Questions about data foundations and analytics

The groundwork that makes reports and AI trustworthy: your data brought together from its sources, cleaned, modelled and documented, with clear access rules. Dashboards and AI sit on top of that, so they show the same numbers everywhere.

Usually, once your data comes from more than a few systems. For smaller setups, a well-modelled database and a reporting tool can be enough. After looking at your sources and your reports, we tell you which fits.

The one your teams will actually open. If you already have one, we build in it. If not, we compare two or three options against your users, your data and your budget, and you choose.

Each metric gets one written definition the business agrees, tests run on the data with every load, and a sample is checked against the source system before a report goes live.

We bring in only the personal data a report really needs, pseudonymise it where we can and limit who sees it. The data stays in your environment, and we work under a data processing agreement.

Usually, through their APIs, database access or exports, including your ERP, CRM, finance and operational tools. We list your sources in the first weeks and check what each one offers before we promise a date.

Yes. AI on company data needs what good reporting needs: clean, documented data with clear access rules. Our AI app development work builds on that foundation.

The first report is built end to end early in the project, so you can check its numbers in staging, with a demo every week. The written proposal after our first call sets out the timeline for your sources and reports.