Matr, as in matter.
Because data is only worth what you do with it.
Small data teams are buried under the same demand as big ones, with a fraction of the people. The market's answer is always the same: hire more, or wait. We didn't accept that trade-off.
Matr exists so a small team can ship like a large one, without growing to do it.
Scale your output, not your headcount.
Every company sits on more data than it can use. The warehouse is full, the models are possible, the questions are obvious. What's missing is the team to turn all of it into decisions fast enough to matter.
So data teams spend their days answering the same requests, rebuilding the same dashboards, and pushing predictive projects to "next quarter" because there's never room. The business decides on instinct while the data sits one step away.
Matr was built to close that step. Not by replacing the data team, but by giving them the leverage to deliver at a scale their headcount shouldn't allow.
applied everywhere.
Data should serve the decision, not the dashboard.
A number nobody acts on is a cost, not an asset.
The expertise stays with you.
Matr does the heavy lifting; your team keeps ownership of the models, the data, and the judgment.
No black boxes.
Every prediction comes with its reasoning. If you can't explain it, you can't trust it, and you won't act on it.
Ship real things.
No speculative roadmaps, no futuristic promises. Concrete capabilities, in production, this quarter.
for teams that move fast.
Matr lets a data team deploy predictive models and self-service analytics in days, and lets business teams use the output where they already work.
Predictive analytics, dashboarding, API and MCP access, embedding, all on the same platform, on your data, with one semantic layer and one set of permissions.
The founding team
Station F, Paris.
Matr is built by a small team where everyone owns a real part of the product and the trajectory. Short team, fast decisions, high bar on quality.
Victor
Pervès
Thomas
Fontaine
Camille
Pradel
More than ten companies run Matr in production, from subscription brands and healthtech scaleups to software publishers embedding analytics in their own products. Different industries, the same pattern: small data teams delivering far beyond their size.
