built by an engineer · validated in the open
A clinician gets fifteen minutes, and the evidence that should inform the visit is scattered across more research than anyone can read. Zenlo reads the whole profile against the whole literature — and hands the synthesis back to the doctor.
Why Zenlo exists
The study that would change a decision usually already exists — it's just buried in a literature no clinician can keep up with, waiting to be applied in a visit too short to apply it. Meanwhile a patient's own data — labs, history, medications, trends across years — rarely gets read as one connected picture.
Chronic disease is now 86% of U.S. healthcare spending, and the gap between catching something early and catching it late can run 26× in cost. A large part of that gap is simply reading that no one has the hours for. Zenlo is the reading layer — built to do, every time, what a doctor would do if they had read everything and forgotten nothing.
Zenlo proposes. The clinician decides. Every synthesis is a draft until a doctor reviews it, edits it, and signs it. We surface the patterns and the things worth a second look — then we stop, exactly where clinical judgment begins. We never deliver a conclusion around the physician. That isn't caution bolted on afterward; it's the shape of the product.
How the engine reads a patient
One shared clinical core does the work — the same engine behind every Zenlo product. Here is what happens in between.
A PDF, a photo, or raw text becomes structured biomarker data — normalized across units and reference ranges by age and sex.
Claude Haiku 4.5 · ~$0.001 / patient15 validated clinical patterns, plus interaction analysis across eight types of relationship between them — because risk rarely lives in one number.
F1 0.963 best-in-benchmarkInsulin resistance (HOMA-IR), biological age, and longitudinal trends — computed and explained, not left as raw figures.
HOMA-IR · BioAge · Trend EngineEvery read is grounded in a knowledge store of 2,534 documents spanning population data and published research, 2000–2025.
pgvector · NHANES + PubMedZenlo holds the patient's standing history, evolving results, the relevant literature, and the tools that connect them — as one context.
static + dynamic + retrieval + toolsSee the engine, block by block. The full architecture — every block and how the products reuse them — lives on the engine map. Open the engine map →
What we hold to
The synthesis is a draft until a clinician signs it. Zenlo informs the decision; it never replaces the person making it. This is also why we stay on the right side of the line that separates clinical software from a medical device.
We label what's live and what we're still building, on every product. No demo-ware dressed up as shipped product. We would rather show you a smaller true thing than a bigger false one.
Zero-data-retention AI under signed business-associate agreements, HIPAA-aligned design, row-level isolation per user, and k-anonymity (k ≥ 10) on anything aggregated. A file is the patient's; the doctor decides what is ever shared.
Validated in the open
Zenlo's pattern engine was benchmarked across five frontier models and tested against 4,018 NHANES patients. The methods — and our audits — are published.
Who's behind it
Engineer and founder, building Zenlo end to end from Los Angeles — from the clinical engine to the product you use.
Practising clinicians guide the medicine, the patterns, and the boundaries — so the engineering stays accountable to clinical reality.
No outside capital, no pressure to overstate. One solid product at a time, validated before it goes out.