TIME TO TRUST
Can you trust the number your decision rests on?
DSharp is data accelerator software — it turns the data you have into data your business can trust.
A 45-minute walkthrough · Your data stays in your environment
The problem today
Getting to a trusted number takes too long
In most data stacks, the hard part isn't running the query — it's being sure of the answer.
Leadership waits
Weeks or months pass before anyone can stand behind the number in the room.
Teams rebuild
The same logic gets re-derived by hand, in every tool, for every question.
AI amplifies the mess
Point AI at unverified data and it just produces wrong answers faster.
What DSharp does
Be sure of the answer — once, from one verified model
DSharp turns changing source data into a single model your whole organization can trust. Leadership and systems read the same definitions, generated as standard, tested code you own. It's one shared model that sits between your sources and your tools — not another platform to migrate to.
“How much did each product line sell last quarter?”
Changing sources, in the systems you already run.
Structures are generated from the model — nothing in your stack gets replaced.
Same trusted definitions — leadership and data teams read the same answer.
The everyday payoff
When the number is finally right, the day gets easier.
Here's what DSharp changes on an ordinary workday, once everyone can trust the same number. Pick the world that looks like yours.
Every technician's day, planned around real billable work.
The service manager sees each morning how much of the day is billable work versus driving, waiting and fetching the wrong part, assembled from time, location, work orders and van stock. Routes get planned so no one drives half a day empty, and technicians get home on time.
The business decides in weeks, not quarters.
For an industrial house we built the reliable foundation the numbers rest on in about ten days, where a previous vendor had spent over a hundred. It's your own code, so no one rebuilds it by hand and you're never locked in.
The warning comes before the machine stops.
Sensor logs, the maintenance system and production control finally read as one signal, so a fault surfaces early. Maintenance runs on a planned quiet shift instead of a 2 a.m. emergency in the middle of production.
You call the customer before they call you.
Orders from ERP, production status from MES and logistics come together, so sales and operations see which orders are slipping while there's still time to act. The promise holds.
The shelf holds what customers actually want.
No more guessing demand in a spreadsheet while stockouts and overstock happen at once. One reconciled number means capital isn't sitting on the wrong pallets, and sales rarely has to say "out of stock."
The right part is already on the van.
Each van is loaded for the day's likely jobs from service history, equipment life cycle and stock per vehicle, so the fix happens on the first visit and the customer isn't left waiting for a second.
A region built from many organizations, reading one set of definitions.
Varha, one of Finland's wellbeing regions, was formed by merging many organizations, each with its own systems and definitions. DSharp helps assemble the concepts its reporting rests on, so leadership and teams stand behind the same numbers.
1,400+ concepts, one shared meaning across the whole organization.
Metsähallitus, the state enterprise managing Finland's public land and water, modeled its shared concepts once so every team draws on the same definitions instead of re-deriving them per report.
A city where departments finally read the same numbers.
The City of Turku uses DSharp to align definitions across departments and systems, so city-wide reporting rests on one trusted model rather than reconciled spreadsheets.
Prove it
See it on one of your own numbers, in days.
No platform project, no big commitment. We take one real source, or just a model of it, and assemble the number live, in your own environment.
Why DSharp
Less effort. Faster trust.
From months to days
Discovery and documentation that used to take a team a quarter happens in days — structures ready for use, not a report.
Up to 90% less manual effort
The repetitive work — mapping sources, defining fields, writing transformations — is done by software, not by hours you pay for.
Nothing to migrate, nothing to unwind
Runs where your data lives, uses your own AI, outputs standard code you keep. If you stop, you lose nothing.
Trusted by data teams across the Nordics and Europe — Metsähallitus, Varha, City of Turku, Pirte, Retta, City of Järvenpää, and more.
Start small
Prove it on one source — in days.
No platform project. No big commitment. We take one real source — or just a model of it — and show you the speed and the trust live, in your own environment.