Incorporation announcement
Foundation structure, nonprofit direction, and what public-benefit infrastructure means for the work.
Notes from the foundation
Notes from the work.
Announcements, product notes, research essays, Neuroverse updates, Yar progress, and the planned Helix Model series.
A running log of announcements, research notes, and product updates, published as they happen.
Neuropsych focus
The public framing for attention, mood, cognition, sensory processing, social communication, and insight.
Yar announcement
Product principles, early access, roadmap feedback, privacy boundaries, and cognitive companionship.
Helix Model
A planned research essay series on trajectories, coordinates, validation, and interpretation.
The gap between where healthcare moonshots start and where they need to end
Ambitious health-AI projects often begin with a model and end with a demo. The harder, more valuable distance is from a promising result to infrastructure a whole ecosystem can trust, reproduce, and build on. A note on why we are starting with the foundation, not the headline.
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What we mean by a health-state coordinate
Position, trajectory, deviation from baseline, uncertainty, and evidence traceability: the five things every coordinate carries, and why each one matters.
Read morePublishing the experiments that didn't work
Why negative results belong in the open record, and how we document them alongside the ones that did work.
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Disease as trajectory: why a map changes everything
When you treat disease as a label to assign, you build different infrastructure than when you treat it as a trajectory to understand. The difference runs all the way down.
Read moreCytognosis Foundation: nonprofit status confirmed
We have received 501(c)(3) recognition. A short note on what that means for the mission and what it doesn't change.
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Integrating wearable signals without overclaiming
How we handle physiological signals from consumer devices, including what we do when the data is noisy, incomplete, or not validated in research settings.
Read moreFAIR-compatible by default: our data architecture
Findable, accessible, interoperable, reusable: we explain how these principles are baked into the way we store and share every dataset and model artifact.
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