A data-science firm, pointed at the hardest medical cases.
Ternary Health is built by researchers. What makes a plan trustworthy isn't a longer questionnaire or a bigger model — it's standardized inputs, a curated pattern library, and two researchers who read every case by hand. This is the data behind the method: what we ask of every client, what we've built across all of them, and how the two of us turn one into the other.
The dataset is where we start, not where we stop.
Standardizing your inputs is the disciplined part — the same Core Panel, the same wearable metrics, the same structured intake for every client, so nothing gets lost and every case is comparable. But a standardized dataset is a starting line.
Once it’s in, the two of us work your case by hand: reading your labs against your genome, your wearable trends against your symptom timeline, your family history against the literature — looking for the patterns specific to you. The data is what makes those patterns visible. Finding them, and deciding what they mean for your plan, is research we do ourselves. No case is a lookup.
Inputs from you. Patterns from us.
One half is the same standardized starting kit for every client. The other half is what we’ve built across all of them — five named assets that get sharper every engagement.
The standardized inputs every engagement begins from — the structured intake, the Core Panel, optional genome and wearable data, vitals.
Five named assets that compound with every case — Case Library, Signal Dictionary, Evidence Matrix, Specialist Graph, Outcomes Ledger.
Inputs, in. A prioritized plan, out.
The Core Dataset is what arrives. The Data Foundation is what we bring — the case library that lets us recognize a pattern in your case from having seen it before, the signal dictionary that tells us which findings matter for your condition, the evidence matrix that says what the current literature actually shows.
The plan that comes out the other end is built option by option, with each one weighed against the same three questions: Evidence × Personalization × Action.