Getting clean, AI-ready data and modern applications aren't two separate projects, they're the same foundation. We build both together so your AI investments actually have something solid to stand on.
It is the work of updating where your data lives, how it moves, who can see it, and the applications that depend on it. Most of it falls into five workstreams.
Find out what data and applications you actually have, what they cost to run, and what is quietly at risk.
Move data off aging on-premises storage and into a cloud platform sized for your workload, then build the pipelines that keep it current.
Catalog what you hold, classify the sensitive parts, and control who can reach it.
Turn the result into dashboards and forecasts your business leaders can use without calling IT first.
Rebuild, extend, or replace the applications sitting on top, so they scale and stay supportable.
You rarely need all five at once. You almost never need only one.
They started as fifteen years of reasonable decisions. The moment someone picks up the phone is usually one of these.
If one of those sounds like your Tuesday, the rest of this page is about what we would do next.
Nine things, run by the same engineers, so the seam between your data and your software stops being your problem to manage.
We assess your data and reporting environment first. You get a clear picture before anyone proposes an architecture, which is the opposite of how these projects usually go.
We migrate on-premises storage to a right-sized platform on Microsoft Azure or AWS, so capacity follows demand instead of a purchase order.
We catalog your data, classify the sensitive parts, and apply access rules. This is also the work that has to happen before any AI tool is pointed at your files.
Business intelligence is the part your colleagues actually see. We build reporting in Microsoft Power BI so people can answer their own question at 7 a.m.
Our data scientists build models that use your history to forecast what is coming. Useful only when the four steps above are done properly, which is why we do not sell it first.
Legacy applications fail in predictable ways. We work with your product owners and your security team to decide which ones are worth rebuilding and which are worth retiring.
When the software you need is not on the market, we design and build it. Usually the thing standing between a manual process and the hours it eats.
Most of the productivity sitting on the table in a mid-market company is in the gaps between systems. We build the integrations that close them.
If you have an idea but no scope, a Springboard engagement answers the practical questions and hands you a plan. You can take that document and build with someone else.
For most companies, that is not much. If permissions are loose, a Copilot rollout does not create a new problem. It shows everyone the one you had.
So we treat AI readiness as an outcome of the data work rather than a separate purchase. For agent and AI application work once the foundation is in place, see our artificial intelligence services.
OnShore wanted to modernize ValidationMaster, their flagship platform for FDA-regulated manufacturers. We rebuilt the reporting and document generation, improved the interface, and delivered against compliance requirements that had sunk two earlier attempts with other vendors.
Read the OnShore Technology Group case studyHorton was pulling client and premium data out of a CRM, insurance platforms, and XML forms by hand. We built the pipelines and a single source of truth, then stood up Power BI so their business teams could answer their own questions.
Read The Horton Group case studyWe do our best work with companies between roughly 200 and 5,000 people who run on Microsoft and have an IT leader in the building. Manufacturing, financial services, professional services, retail, education, and legal, mostly.
Your current environment, your applications, your data sources, and the constraints you are working inside.
Not just IT. The controller, the plant manager, the person maintaining the spreadsheet that holds everything together.
Scope, sequence, budget, timeline, dependencies, and what we would do first. In writing.
Then you decide. If you want us to run it afterward instead of handing it back, that is what our managed services are for.
Thirty minutes with an engineer who has untangled this before. Bring your worst reporting problem and the application nobody wants to touch.
Talk to an engineer about your data and appsNo pitch deck. We look at your sources, your apps, and what they are costing you, and you get an honest read either way.