About Analysis Health.
Analysis Health is founded by two entrepreneurs with backgrounds in data engineering and brand strategy, who saw a specific gap in health diagnostics.
The cost of running lab tests for 100+ markers has dropped from thousands to hundreds in a decade. New companies — Function Health, Superpower, Life Force, and many more — who have each made comprehensive panels accessible. People are finally able to run these tests in volume. But what hasn't yet expanded is the work that comes after: turning long lab reports into a plan that names what to do first.
We know this gap personally. For years we'd been ordering our own panels and ending each round with more numbers and not much more clarity. One co-founder became Analysis Health's first client — lingering health struggles that had resisted years and thousands of dollars spent searching for the root cause. While what surfaced wasn't a complete mystery, using AI to read the labs alongside the full history explained them more clearly than anything before.
But Analysis Health wasn't just built because we couldn't find an answer for ourselves. We built it because we could see exactly where the gap in health interpretation is, and what it would take to close it. Decades of data engineering experience anchor the technical architecture behind every analysis.
We built the tool we wanted: an interpretation that takes the data already in hand and produces a plan, in hours. Not another panel. Not another subscription. The missing layer that turns data into action.
Why Analysis Health Exists.
Health data is only as valuable as what gets done with it.
Facts about lab testing.
13.3 billion clinical lab tests are run in the US every year, and roughly 75% of clinical decisions depend on what those tests show.¹ The volume keeps growing — direct-to-consumer genetic testing has more than doubled in the last five years,² and comprehensive panels are now within reach for anyone willing to pay.
The interpretation gap.
Patients can’t read what they get. A study of patients with lower numeracy found only 38% could correctly identify whether a lab result was inside or outside the normal range.³
Doctors don’t have time. Primary care physicians would need 26.7 hours a day to deliver every recommended check on a typical patient panel.⁴
The system doesn’t follow up. Up to 62% of abnormal lab results lack timely follow-up, depending on test type.⁵
The gap isn’t in your data — it’s in the work that turns the data you already have into an educational resource and actionable plan.
Analysis Health exists to close that gap. More data isn’t the answer. More interpretation is.
How We Use Technology.
Artificial intelligence is the backbone of how we interpret data.
Our analysis is the kind of pattern-recognition artificial intelligence is trained to do at scale. It reads patterns across multiple markers, compares how different analytical frames score the same evidence, and ranks what matters most for next steps.
For us, such advanced technology is what makes our work possible. We use it to run analyses at a depth and speed no small team could match. We use it to maintain consistency across every report — the same architecture, every time. And we use it to iterate on our approach as the science changes, without rebuilding the whole system from scratch.
How we shape the AI models we use is what makes our analysis specifically ours: our frameworks define its depth, what gets weighted, what gets flagged with less certainty, and what gets delivered. The interpretation is technology-backed. The structure is all ours.
Our Role Alongside Care.
Analysis Health was built to work alongside medical care.
Our position is intentional — we’ve thought about it carefully and couldn’t build the product any other way.
A doctor’s role is irreplaceable. Clinical examination, diagnosis, prescription of treatment, and the ongoing relationship of a care provider are the work of medicine. None of that is what we do.
What we do sits in a different layer. People are now accumulating lab data faster than a short clinical visit can engage with thoughtfully. The cost of testing has come down; the time available to interpret each test hasn’t expanded with it. A real gap has opened between data and conversations had about it.
Analysis Health works directly in that gap. We turn data into something organized — what’s connected to what, what to address first, what’s worth raising in your next visit. You end up with data you can act on, in your own time, on your own terms.
What We Believe.
Our company beliefs are woven into our work — what gets included, what gets cut, and what we can claim.
Health data should be usable.
A panel that no one can act on is a panel with less value. Numbers exist to help make decisions.
AI is part of our methodology, not our headline.
It’s the craft behind each analysis, not the product itself. Customers come for personalized interpretation; the technology that delivers it stays in the background.
More data doesn’t replace interpretation.
Good interpretation reads markers in relationship rather than in isolation. A single value out of range is a poor witness. The same value sitting inside a pattern across markers, against the customer’s symptoms and history, says something different.
Analysis Health works alongside medical care, never as a substitute.
Our job is to bring organized data to the user’s conversations with their doctor — with named patterns, prioritized concerns, and the right questions to raise.
Health science and technology both evolve.
Our products evolve with them. What’s certain today gets revisited as the field changes; iteration is built into the design, not retrofitted.
Health data should be usable.
A panel that no one can act on is a panel with less value. Numbers exist to help make decisions.
Numbers exist to help make decisions.