Your data has a story.
We help you tell it honestly.
We're a small team of statisticians who work in R. We untangle messy datasets, run careful analysis, and hand everything back in plain language — with code you keep and methods you can check.
Watch a dataset become a decision.
This is the shape of almost every project we do. Scroll through it — the panel on the right is the same data at each step.
We start with your data, as it really is.
Spreadsheets with three naming conventions, exports that almost match, columns nobody remembers creating. That's normal — it's where every real project begins, and it doesn't scare us.
Then we tidy, carefully and openly.
Every cleaning decision is written down in code — what we dropped, what we fixed, and why. You can re-run it, audit it, or challenge it. No silent judgement calls buried in a spreadsheet.
We model with statistics that fit the question.
Not the fanciest method — the right one. We show uncertainty honestly, test our assumptions, and tell you when the data can't answer the question. That honesty is the whole point.
You get answers you can act on and defend.
A clear report in plain language, charts your board will actually read, and the full code behind every number. When someone asks "where did this figure come from?" — you'll know.
Practical capabilities, not buzzwords.
Everything below is work we've genuinely done, in R, end to end. If your problem doesn't fit neatly here, ask anyway — the answer is usually a conversation, not a category.
Small team. Strong opinions about honesty.
These aren't values off a poster — they're the standards we hold each other to on every job.
Show the working
Every figure traces back to code you can run. If we can't show how we got a number, we don't publish the number.
Say the uncomfortable thing
If the data doesn't support the conclusion you hoped for, we'll tell you early and plainly. That's what you're paying for.
Leave you stronger
We'd rather teach your team to run the analysis than make you call us every month. Capability transfer is built into how we work.
The kind of problems we solve.
Modernising cancer screening surveillance
The Australian Centre for the Prevention of Cervical Cancer needed their monthly surveillance reporting to be faster, clearer, and easier to maintain. We rebuilt the pipeline in R and Quarto, mentored the team along the way, and helped chart a sensible path to their new cloud platform.
- Monthly reports now generated from a single reproducible pipeline
- Replaced a costly external address-validation service with an in-house solution
- Team mentoring built in — their analysts now extend the pipeline themselves
Actual humans, who answer their own email.
No account managers, no handoffs. The people below are the people who do the work.
Tell us what's going on with your data.
No pitch decks, no discovery-call scripts. Describe the problem in your own words and we'll reply with our honest read — including whether we're the right people for it.