We build three things: AI that solves a real problem rather than demoing one, data pipelines that make your numbers trustworthy, and dashboards people actually open. Our team scopes the work, builds it to a fixed scope, and hands it over documented, in your own cloud accounts. If a simpler answer would serve you better than the impressive one, we will tell you.
Three offers, one team.
Three distinct pieces of work. Most engagements start with one and grow into another, because a dashboard is only as good as the data behind it and AI is only as good as both.
GenAI and large language models integrated into the products and workflows you already run: retrieval over your own documents so answers cite your content, summarisation and extraction where people currently read and retype, and natural-language querying over existing data. Traditional machine learning where the problem genuinely calls for a model rather than a rule. We are straightforward about when AI is the wrong tool, because a feature that impresses in a demo and frustrates people in production has cost you twice.
Pipelines that move data reliably and on schedule, warehousing and lakehouse design so it lands somewhere queryable, and the unglamorous data-quality work that decides whether anyone believes the output. This is usually where a reporting project actually succeeds or fails: two systems disagreeing about the same customer is a data problem, not a chart problem, and no dashboard will paper over it.
Reporting built in Power BI, Tableau or Amazon QuickSight, depending on where your data lives and what your team already uses. Self-serve analytics so people can answer their own questions instead of queuing for a report, and executive reporting that says what changed and why rather than showing everything at once. A dashboard nobody opens after week two was not a reporting problem, it was a scoping problem.
Three steps, no open-ended retainer required, and no dependency on us at the end unless you want one.
A free call to understand the data you have, the decisions you want to make with it, and what is actually in the way. We come back with a fixed scope and a written quote. If the honest answer is a smaller piece of work, that is what you get quoted for.
Book a scoping callThe work runs to the agreed scope, built inside your own cloud accounts rather than ours. You see progress as it lands instead of waiting for a reveal at the end, and scope changes are a conversation with a number attached, not a surprise on the invoice.
You get the build, the documentation and a handover session with the people who will run it day to day. Everything lives in your environment, so nothing is locked in a black box only we can open. Ongoing support is a separate conversation if you want it.
We are an AWS-focused firm, so AWS is where our defaults live. But a reporting project should follow your data, not our preferences.
Delivery is remote, so the practical questions are data residency and working-hours overlap. Both are answered per market.
Data platforms built in your US accounts and US regions, with a working rhythm suited to a team several hours ahead: live overlap in your morning, and async delivery for the rest.
Delivery on the AWS UAE and Bahrain regions where in-country residency matters, on a working day that runs almost in parallel with yours.
Sydney and Melbourne regions for Australian data residency, with reviews and standups that fit inside the Australian workday rather than at the edges of it.
London and Ireland regions for UK and EU residency, with your morning overlapping our afternoon so reviews happen live rather than overnight.
If your question is not here, ask it on the call. We would rather scope honestly than sell you a platform you do not need.
Bring the data you have and the decision you are trying to make. We will tell you what is realistic, what it would take, and what it would cost, before you commit to anything. If a smaller piece of work would answer your question, we will scope that instead.
