The problem that wouldn't go away.
Before Nanometrix, our founders spent years running single-molecule localisation microscopy (SMLM) and extracellular vesicle (EV) experiments — and burning through evenings on Python scripts that only one person on the team could read. Every cohort meant another bespoke pipeline; every collaborator meant another round of re-formatting and re-explaining.
The same frustration kept surfacing across conferences and community channels: nobody had a credible analysis layer for extracellular vesicle data. Tools existed — but they were either built for a single instrument, or so generic they told you nothing.
Their first answer was a tool of their own: vLUME, built to make single-molecule localisation data explorable in 3D, published in Nature Methods in 2020 (Spark, Kitching et al.). It worked — and it made the real gap obvious. Seeing the data was never the bottleneck; turning thousands of datasets into quantitative, comparable results was.
A platform, not a plugin.
In 2022 we prototyped the first Nanometrix software: CSV upload, unlimited projects, grouped populations, and batch analysis that didn't require an in-house Python expert. The first labs who tried it never went back.
We deliberately didn't build another plotting tool. We built the surrounding infrastructure — storage, reproducibility, collaboration, compliance — that EV scientists needed to move from one-off figures to shippable science.
From analysis to prediction.
As customer cohorts grew, a new pattern emerged: labs weren't just analyzing their EV data — they were asking whether that data could predict. Could an EV signature separate disease from control? Could it distinguish responders from non-responders?
We launched the Diagnostics AI Pipeline in beta to answer that — tailored predictive models trained jointly by our science team and the lab that owns the data. Generic benchmarks don't translate; close collaboration does.
Where we go next.
Nanometrix now supports research labs, diagnostics companies, and core facilities across Europe, North America, and Asia. Nanometrix Terra unlocked clinical-adjacent deployments. Parallel batches hit the 10,000-sample ceiling.
But we're at the start. Nanoparticle and extracellular vesicle science is moving from descriptive to predictive, from single-lab to multi-site consortia, from exploratory to regulated. We're building the platform that makes that transition survivable.
