company · mission
we didn't make the models.
we made them reachable.
the science is other people's, and every result we return names its source. what we built is the layer that plans a run, records it, and hands back something you keep.
our mission is to cultivate the next generation of medicines — starting with neurological, metabolic, and reproductive health — so breakthrough therapeutics can come from any researcher, anywhere in the world, regardless of their resources or institutional backing.
what we stand for
open science, named sources, patients first.
- open science
great science shouldn't hide behind paywalls. we believe every researcher deserves access to modern tools, whether they're at a major university or a small lab halfway around the world.
- give back
we're building toward becoming a public benefit corporation — committed to supporting the open-source ecosystem we depend on through revenue to maintainers, equity grants for contributors, and fellowships for developers.
- attribution
we don't pretend to invent the models we run. esmfold, diffdock, admet-ai, aizynthfinder — that is other people's science, and every result we return names its source. what we built is the layer around them: the runtime that plans and executes a run, the tamper-evident ledger that records it, and the passports that turn raw model output into something a chemist can read. we acknowledge our debt to rdkit, mol*, biopython, alphafold, and hundreds of maintainers.
- patients first
behind every molecule we model, there's someone waiting for a better treatment. that's who we're really building for.
how we work
show the uncertainty. name the source.
- rigour
we don't hide the uncertainty. confidence scores ship with every structure, and low-confidence regions are flagged rather than smoothed over.
- ethical ai
AI should be transparent, fair, and safe. we don't ship an answer without its source — every number on a canvas card names the tool, the parameters and the run that produced it.
- collaboration
the best ideas come from unexpected places. we actively seek diverse perspectives to challenge our thinking.
- sustainability
good science should be sustainable. we're mindful of our computational footprint and build for the long term.
the next breakthrough could come from anywhere.
let's make sure it can.
join the movement