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OUR WORK
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National Cancer Institute
3+ year partnership delivering AI research platform
"I have worked with Barnacle Labs for more than 3 years on a project at the National Cancer Institute (NCI)... they treated the work like a collaboration... if you are looking for a partner in AI, I couldn't recommend them more."
Dr Oliver Bogler
Director, NCI's Center for Cancer Training
WHO WE ARE
We build production AI systems for serious organisations — the US federal government, enterprise, biotech.
Our founders led AI at IBM Watson and gained early GPT-3 access in 2020. We've spent a decade learning what actually works — and what quietly fails. We stay ahead through ongoing research, so our advice comes from experience and exploration — not guesswork.
WHAT WE DO
We help enterprises pick the right AI bets and build the next breakthroughs.
Figure It Out
You know AI matters. But you're stuck. What's real? What's hype? Where do you even start?
Build It
You know what you need. But you need someone who knows their stuff to build it.
Train Your Team
Your team needs AI skills. But most training doesn't embed the practical capabilities your team needs.
Guide You Through It
Your team can build it. But you're worried about the dead ends and solutions that won't scale.
Not sure what AI means for you?
We can create an for you in two weeks.
READ OUR THOUGHTS
White Paper
Coming SoonAI Agents: Your next digital co-worker?
by Duncan Anderson
Exploring the frontier of autonomous AI systems and their impact on problem-solving
Blog Post
Building a Reproducible Multimodal Pipeline
by Kevish Napal
Part-1 in a series of posts about proteomics, cancer biology, and AI-driven solutions for oncology.
Blog Post
Understanding Cancer and Telomerase: From Biology to New Treatments
by Kevish Napal
Part-2 in a series of posts about proteomics, cancer biology, and AI-driven solutions for oncology.
Blog Post
Understanding and Processing CT Imaging for Stroke Detection
by William Auroux
A practical guide to turning raw brain CT into training-ready data.
Blog Post
The Dimension Dilemma: Why 2.5D Models Outperform 3D CNNs for Stroke Classification
by William Auroux
Lessons & Experiments on training deep learning models on 3D medical data.
Weekly AI news from builders who ship production systems. No hype, just what matters.