Wearables digitized the body's physics. Lactate is the chemistry health AI is missing.

The first generation of wearables measured the body’s physics (heart rate, movement, pulse oximetry, sleep etc.). They made the body's rhythms part of everyday life, and they've generated billions of readings that train today's AI health models.

But physics is a proxy. When a doctor makes a critical decision, they rarely rely on heart rate alone. They order a blood test, because the answer is in the body's chemistry.

Continuous glucose monitoring proved that chemistry can be measured on the body, every minute of the day, and built a multi-billion-dollar category doing it. Lactate is the next molecule. It rises when the body's cells and organs aren't getting enough oxygen, which makes it a direct signal for some of the highest-stakes moments in medicine: a baby in distress during labor, a patient sliding into sepsis, internal bleeding after surgery. Today it's measured only by blood draw, a few times at most.

That gap matters for AI. A model can only learn what its data contains. Wearables know what healthy looks like, because that's who wears them. Almost no continuous data exists for the moments when someone becomes seriously unwell, and none of it is chemical.

VitalTrace is building that dataset, starting in the hospital. Every DelivAssure sensor records lactate alongside heart rate and what happened next, including the moment a baby deteriorated. As we move into sepsis, critical care and consumer health, the dataset grows across the episodes that matter most.

We make the sensor. We'll own the signal. And we'll build the chemical dataset the next generation of health AI learns from.