Hypothesis engine for medical AI
Research ideas that hold up in the clinic.
Pinah helps engineers without a clinical background build medical AI that makes sense to clinicians. It proposes research directions, screens them against clinical reality, and tests the ones that remain.
- Your starting idea
- Promising direction
- Removed by clinical check
- Confirmed by experiment
Diverge
Explore widely
From your starting idea, Pinah grows a tree of candidate directions, including ones you would not have tried.
Filter
Check against the clinic
Built-in clinical rules remove ideas with hidden flaws before anyone spends time training them.
Verify
Run the real test
Surviving branches are run as experiments, and the results decide where the tree grows next.
You stay in charge. Pinah pauses at key points for your decision, so the direction of the research is always yours.
The name
The stone everything else is set against.
Pinah · cornerstone
Pinah is Hebrew for corner. In even pinah, the cornerstone, it names the first stone laid in a building. Every other stone is aligned to it.
Good research needs the same thing: a steady base under the desk and the chair, so the work on top stays square. That is the job Pinah takes on.
What changes
Less guessing, more signal.
- Fewer dead endsWeak ideas are caught early, before days of work go into a model that could never be trusted.
- Stronger starting pointsEach session sharpens how you frame the next question, so your hypotheses improve with use.
- Your time backThe search runs without you. You return to a short list of candidates worth reading.
Pinah supports researchers and engineers. It does not provide diagnoses or treatment advice, and it is designed to run on your own hardware so patient data stays with you.
Contact
Talk to us.
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