MNEOS · Humans and AI, building the future together
MNEOS unites human scientists and engineers with artificial intelligence, and soon with embodied AI and humanoid robotics, to take on the hardest problems in health, engineering and knowledge. Every experiment we run teaches the next one, because we built the memory to make sure it does.
Founded and led by David Sherrer. The first Neuroclearance bench prototype is being built right now, its public site and open brain-health library are live at neuroclearance.com, and we are looking for the people who want to shape the experiments that follow.
The record feeds the next question, so each experiment starts with more understanding than the last.
Featured work
What if we could understand how the brain clears, repairs and sustains itself, and use that understanding to help people stay sharp, recover faster and age well? Neuroclearance is our answer to that question: a research program that starts with the instruments, because the right measurements are how a bold idea becomes real science. The first bench system is being built now.
Where we stand. Research stage: Neuroclearance is not a treatment, and clinical benefit is still to be established. We publish every milestone as it is reached.
Three fronts
Brain health and healthy aging
Can a better understanding of brain physiology lead to useful approaches to brain health, recovery and healthy aging?
We are building the instruments to understand how the brain clears, repairs and sustains itself, so that understanding can become better lives. The first bench prototype is being built now, and the program's public site teaches the science behind it.
Scientific AI and memory
Can a research system answer what changed, show where that answer came from and preserve what a human decided to do about it?
AI that remembers why. We are building DOS, a memory that keeps every source, decision and lesson, so human and machine intelligence can compound across every project instead of starting over.
Materials, manufacturing and testing
How should measured results change a model, a material choice and the next experiment?
Ideas have to survive the physical world. Through related programs in materials, manufacturing and testing, we put models and AI to work on real hardware, then build the embodied systems that will do it alongside us.
The vision
We believe the next great leaps in science and engineering will come from teams of human and artificial minds working as one: people bringing judgment, creativity and purpose; AI bringing tireless search, synthesis and computation; and embodied AI and humanoid robots bringing hands to the laboratory and the factory floor.
MNEOS is where that team is being assembled. The memory is DOS, so nothing learned is ever lost. The proving ground is real hardware, from a brain-health bench instrument to advanced manufacturing lines. The measure of success is simple: does the next experiment start smarter than the last?
The road ahead
Now. A human founder and AI collaborators working daily on Neuroclearance, DOS and physical engineering. Most of the day-to-day research, drafting, design iteration and software is done by AI under human direction and review.
Next. Instruments and manufacturing cells that AI can operate under human direction, with every run recorded and learned from.
Then. Embodied AI and humanoid robotics working alongside people in the lab and on the line, as full members of the team.
Proof in practice
Neuroclearance is the clearest example so far of the MNEOS method at work. The founder sets the questions, the standards and the decisions. AI collaborators do most of the rest, and DOS keeps the record of what was decided and why. In the founder's words, these days many of his most productive colleagues are not human.
What that has produced so far, with every item reviewed by a person before release:
Division of labor today
People decide. Questions, standards, safety, what gets published, and what the measurements mean.
AI does. Literature synthesis, drafting, design exploration, analysis, software and site construction, at a pace a small human team could not match.
DOS remembers. Sources, decisions and lessons, so nothing has to be rediscovered.
How the work advances
Our method is simple to say and demanding to do: start from a question worth answering, bring every piece of evidence to bear, let people and AI explore the possibilities together, test the idea against the physical world, and keep the whole story so the next experiment starts smarter.
People lead. AI amplifies. Measurements decide.
Founder
David Sherrer has spent his career turning hard technology into things people can build and use: founding Haleos and Nuvotronics, taking new microfabrication from concept to production and acquisition, and leading defense and manufacturing programs since. MNEOS is his answer to a question he could not stop asking: how much more could a small team accomplish if human insight, AI and a memory that never forgets worked together from day one?
Where we are. MNEOS is founder-led today. Its day-to-day work is carried out with AI collaborators, and it is growing into a community of people. The people who join now will shape what it becomes.
One ecosystem
NuvoNexus, LLC is the operating home of MNEOS and DOS.
NeuroClearance is the brain-health research program, with its own public site and open library at neuroclearance.com.
MacroVation builds and manufactures: foam systems, sleep-surface materials and naval components for U.S. defense customers.
Helicon Defense brings allied battlefield innovation into trusted U.S. production.
Field notes
neuroclearance.com is live: what the program is building, how it works, and an open, source-cited library on how the brain maintains itself. Built in a human–AI collaboration, and why we say so.
Four properties every serious instrument earns before it earns a claim: repeatability, timing, calibration and honest fault handling. This is the standard we are building to.
Join us
If you can improve a model, challenge an assumption, build an instrument, write software that remembers, or design a better experiment, there is a place for you here. Start with a problem that excites you and tell us what you would bring.
