AI & Automation Build
The agents and workflows that take repetitive work off your team.
AI & Automation BuildData, Systems & Reporting
Most growing businesses don't have a data problem, they have a data-in-six-places problem. We design and build the database, the pipelines that keep it current, and the reporting on top, so the answer to "how are we doing?" takes a second rather than a morning.
Businesses that have outgrown spreadsheets. The signs are consistent: numbers assembled by hand each month, two systems that disagree and nobody sure which is right, reporting that arrives too late to change anything, and a growing amount of someone's week spent moving data between tools.
We map what data exists, where it lives, who touches it, and which decisions are currently being made without it.
We agree the data model, the definitions, and what the reporting has to answer, before a line of it gets built.
We build the database, the pipelines and the reporting, then run it alongside your existing process until the numbers are trusted.
New systems arrive and new questions get asked. We stay close to what we've built so it keeps up.
Builds run as fixed-price sprints, with a retainer where ongoing analysis and development is part of it. Everything starts with a short call and an AI & Automation Health Check.
Getting your data out of the tools it's trapped in and into one place it can be used from. That usually means a properly designed database, automated pipelines that keep it current, and reporting built on top. The end state is a single set of numbers everyone works from instead of four exports that disagree.
Yes. Database design and build is a core part of what we do, usually PostgreSQL, sized to the business rather than over-engineered. We design the model around the questions you need answered, not around what happens to be easy to store.
Almost never. Most of the value comes from connecting what you already have. We pull from your accounting system, CRM, payment processor and operational tools and leave those in place.
A dashboard is the last five percent. The reason most dashboards go stale is the layer underneath: nobody owns the data model, the definitions drift, and the numbers stop being trusted. We build that layer first, then the reporting on top of it.
Because the reconciliation is designed in rather than bolted on. Every figure traces back to its source, and where two systems disagree the build surfaces it instead of quietly picking one. That instinct comes from an accounting background rather than a purely technical one.
It depends on how many sources are involved and how clean they are. We scope it properly at the start and run it as fixed-price sprints, so you know what you're getting before anything is built.
The agents and workflows that take repetitive work off your team.
AI & Automation BuildMonth-end, reconciliation and reporting, running on fewer hours.
AI & Automation for Finance TeamsSee it in practice in our international events company case study, where multi-currency data from several systems was pulled into one reporting view.
Tell us what systems you run today and what you wish you could see. We'll come back on whether it's a fit and what a sensible first step looks like.
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