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Reviresco 47

What is proven

no hiding

What is built, and what is not.

Some of this works today. Some is only designed. Some we genuinely do not know yet. Here is which is which - you should not have to work that out for yourself.

Working now

The clinician's app

Taking notes from a conversation, storing them encrypted on the machine, and running the AI and transcription locally all work today. That is our own assessment; nobody outside has checked it.

Designed, not built

The part that makes us different

The ranking maths, the way promises are described, the safety rules and the testing plan are all written down in full and internally checked. Independent review has not happened yet.

Not built

The ranking engine

The maths that decides what is most urgent does not exist in code yet. Neither does the shared safety core, or the store that holds every promise.

Unproven

Whether it helps patients

We do not yet know if it works. Accuracy, whether it holds up in another hospital, whether it improves care, whether it works equally well for everyone, and what regulators will say are all still open.

Safety rules

eight, non-negotiable

Rules the build has to pass.

These are the rules we hold ourselves to, not a claim that we already meet every one. Breaking one should stop the build - not turn up as a reassuring footnote three months later.

  1. 01Patient data is never stored unencrypted
  2. 02Nothing leaves the machine without consent
  3. 03A person signs off on every clinical action
  4. 04Every change is recorded and traceable
  5. 05When unsure, it stops and asks a human
  6. 06Tested for fairness across six groups
  7. 07It fails loudly, never silently
  8. 08Regulatory controls are designed in from the start

Tests it must pass

prove it first

What has to be true before it goes near a patient.

A model can be accurate and still be useless, or harmful, if it buries the people using it in alerts. Both have to pass.

AreaGateDetail
AgreementTwo reviewers agree at least 70% of the timeIf experts cannot agree what counts as a miss, nothing else matters
FitPredictions line up with what happenedNo systematic drift when checked
CalibrationA stated 70% chance means roughly 70%Within a narrow margin, not loosely
InterruptionsNo more than 6 alerts a dayPer coordinator - more than that and people stop reading them
Warning timeAt least 24 hours notice, typicallyLate enough to be wrong, early enough to act on
FairnessWorks equally well across six groupsChecked separately for each, not just on average

How this could fail

how it dies

Suppose this does not work. What went wrong?

Every one of these has a warning sign we can watch for, and something we would do about it. The point is to stop money going into a broken idea, not to look confident.

PM-01

We cannot agree what counts as a miss

Warning sign
Two experts look at the same case and disagree too often.
What we do about it
Have people judge cases by hand before building anything. If they cannot agree, stop.

PM-02

The patent covers the wrong thing

Warning sign
Our lawyer cannot match what we have built to what we filed.
What we do about it
Sort out what the patent actually covers before showing the details more widely.

PM-03

Old problems eat the roadmap

Warning sign
Known safety issues stay flat or grow while new features keep shipping.
What we do about it
Make fixing them a condition of releasing anything, and check it more than one way.

PM-04

It gets regulated as a medical device

Warning sign
Our lawyer cannot argue a clinician could independently review what it suggests.
What we do about it
Keep the useful everyday parts separate from the prediction, and plan the regulated route in advance.

PM-05

It nags people until they ignore it

Warning sign
More than six interruptions a day, or people overriding it more often.
What we do about it
Treat alert volume as a reason not to ship, not something to tune afterwards.

PM-06

We never get enough data to prove it

Warning sign
We need more cases than we can get, and no second site has agreed.
What we do about it
Work out how much data is needed early, and fund a second site as a real milestone.