Built for the bench
and the terminal
NuHelix AI was founded by researchers who spent too many hours rewriting the same analysis scripts — and too many nights debugging pipelines that should have been reproducible. We built the platform we always wished existed.
Make reproducible science the default, not the exception
Modern biomedical research sits at the intersection of wet lab experiments and computational analysis — yet the tooling gap between the two has never been wider. Bioinformatics pipelines require engineering skill that most research teams lack time to develop, while off-the-shelf tools sacrifice scientific rigor for convenience.
We believe that every researcher — from a PhD student in a university lab to a computational biologist at a pharmaceutical company — deserves access to analysis infrastructure that is rigorous, reproducible, and auditable without requiring a software engineering degree to operate.
NuHelix AI sits between natural language and validated scientific computation. The AI interprets your intent. The platform runs the science. Every parameter, input checksum, and software version is recorded so your results can always be traced back to their source.
Scientists and engineers who have lived the problem
We built NuHelix AI because we spent years fighting the same reproducibility and tooling problems you are fighting. Every product decision comes from that experience.
Dr. Sarah Kim
Co-founder & CEO
Sarah completed her PhD in computational genomics at MIT and spent five years leading RNA-seq analysis pipelines at the Broad Institute. Frustrated by the reproducibility crisis in published bioinformatics, she co-founded NuHelix AI to make verified, auditable workflows the default for every research team.
Raj Patel
Co-founder & CTO
Raj previously led distributed systems teams at two genomics companies where he built large-scale variant calling infrastructure and cloud data pipelines. He brings deep expertise in job orchestration, object storage architectures, and the operational realities of running analysis at scale.
Dr. Marcus Chen
Chief Science Officer
Marcus started as a wet lab immunologist before transitioning to bioinformatics during his postdoc at Stanford. He understands both sides of the bench-to-analysis handoff and oversees the scientific accuracy of every workflow on the platform — ensuring that computational shortcuts never compromise biological validity.
Priya Singh
Head of Product
Priya has spent her career designing interfaces for scientists — first at a lab informatics startup, then as a lead UX researcher at a clinical diagnostics company. She believes that the best scientific tools are the ones researchers actually want to use, and she obsesses over every interaction on the NuHelix platform.
Our values
These are not aspirational posters on a wall. They are the constraints we apply to every product decision.
Scientific rigor
We will never ship a workflow that produces statistically questionable results for the sake of speed or simplicity. Every computation is implemented against peer-reviewed methods and validated against known outputs.
Reproducibility first
An analysis that cannot be reproduced is not an analysis — it is a guess. Every job on the platform records exact inputs, parameters, software versions, and checksums. We treat provenance as a first-class output.
Researcher-centric
We design for the researcher who knows their biology but should not need to know their cloud infrastructure. Complexity is our problem to solve, not theirs.
Open by default
We build on open-source scientific tools and publish our methods documentation openly. When we make decisions about statistical approaches, we explain why. Science should be transparent at every layer.
Join the team
We are a small, focused team working on a hard problem that matters. We move quickly, write things down, and believe that the best products come from people who understand the domain deeply.
Get in touch
We read every email. Response time is typically 1–2 business days.