Answers, not another dashboard
Most businesses do not have a reporting problem. They have twelve reports and no answer. The useful work is deciding which question is worth asking, then making the answer arrive without somebody building it by hand each month.
We start from the decision, not the data. If nobody would act differently depending on the answer, the report is decoration however good it looks. Once there is a real question, AI is genuinely useful for the parts people find slow: pulling from awkward sources, spotting what changed, and writing the summary in language a board will read.
Also sold as AI analytics, business intelligence, data insights and automated reporting.
The work it takes
off your desk
Say what changed and why
Not another chart of the same number, but a written note explaining the movement, with the figures behind it.
Pull from the awkward sources
The system with no export, the spreadsheet somebody maintains, the supplier portal. Usually the reason a report takes two days.
Flag it when it happens
Margin slipping on a customer, jobs running over, a supplier drifting on lead times. Worth knowing in the week, not the quarter.
Write the summary
The commentary that normally takes a manager an afternoon, drafted from the actual numbers for them to correct and sign off.
No surprises,
in writing.
Scope and price agreed before anything is built. If we think you do not need this, we will tell you that instead.
Get a quote ↗- The question written down, and what you would do differently depending on the answer
- A repeatable pipeline from your real sources, not a one-off extract
- Reporting that arrives where you already work, including by email if that is what gets read
- Figures traceable back to source, so a number can always be challenged
- The queries and logic documented and owned by you
Where this
goes wrong
Every supplier will tell you what their service does. These are the ways it fails, and what we do about each one. If a supplier cannot tell you this, they have not built enough of them.
Building a dashboard nobody opens
The most common outcome of analytics projects. If nobody can name the decision it supports, it will be admired once and then ignored.
Answering the wrong question precisely
A great deal of analysis is rigorous work on a question nobody asked. Half of this job is agreeing the question before touching the data.
Confusing correlation with cause
AI is very good at finding patterns, including patterns that mean nothing. Anything that looks like a finding gets tested before it goes in front of anyone.
Numbers that cannot be traced
If a figure is challenged in a meeting and nobody can show where it came from, the whole report loses its authority. Everything stays traceable to source.
What everyone
asks us
Usually not. Plenty of valuable reporting runs directly against the systems you already have. A warehouse is worth building when the number of sources or the volume makes that impractical, not by default.
Yes, and often that is where the real business logic lives. We will also point out where a spreadsheet has become a risk rather than a tool.
Built-in reports answer the questions the vendor anticipated. This work answers the ones specific to how you run, usually by combining sources no single product sees.
You do. The queries, the definitions and the documentation are yours, which matters because the definitions are the part that takes the longest to agree.
Other AI services
Start with
one job.
Tell us the task that eats the most time. We will tell you honestly whether AI is the right answer for it, and what it would cost to find out.
Get a quotation