One number per metric
Revenue means the same thing in every report, because it resolves to one definition.
Services / 03
Data modernization
Pipelines, warehouse and governance so your reporting and your AI finally stand on the same numbers, and you can say where any figure came from.
Where it pays off
Four places this earns back fastest.
Reporting that closes faster
Month-end stops being a week of reconciliation between teams who each built their own extract.
AI that has something to stand on
Most failed AI projects are data projects in disguise. This is the part that has to work first.
An audit you can pass
Lineage and access control in place before someone asks where a figure came from.
What ships
Everything you need to run it without us.
The working build
Deployed in your environment, monitored, with a way back if it misbehaves.
A way to check it
The tests and measures that prove the work is right before anyone relies on it, and keep proving it after.
Runbook and training
Two sessions with the team who owns it after we leave.
Source code
In your repository, under your licence. No lock-in, no black box.
FAQs
Straight answers.
What does it cost?
Most first engagements land between a four-figure fixed fee and a small phased build. You get the number after the assessment, before any commitment.
Do you need our data first?
No. The assessment works from interviews and sample records. Nothing leaves your environment until there's a signed scope and a DPA.
What if it does not work?
We agree what good looks like before we build, and measure against it as we go. If the work cannot clear that bar, we stop and say so.
Who owns what you build?
You own it all: code, prompts, models and documentation, in your repository. We keep nothing you cannot run without us.