Company
We built the layer between visits.
That is where high-risk patients actually decline, and it is the part of care nobody has the hours to staff properly.
Why this exists
- 01
Healthcare already has the data.
Every patient's story exists — in encounters, claims, notes, results and documents, across systems that were never designed to be read together. The problem was never that the information is missing. It is that nobody can act on it between visits.
- 02
Healthcare already has the teams.
Care managers, transitions nurses, quality teams, pharmacists: the people responsible for patients between visits exist and know exactly what should happen. They cannot reach everyone, every week, by hand, so contact happens at the frequency staffing allows.
- 03
The layer between them does not exist.
Continuous intelligence and follow-up between encounters — knowing each patient, reaching them, finishing what is routine, and bringing the team what needs judgment. That is the layer LifeWatch is. It extends the care team. It never replaces clinicians.
Follow-up fails in the handoffs.
Knowing who needs contact is a data problem. Knowing the patient is a memory problem. Making the contact is a reach problem. Proving what happened is a documentation problem. In most organizations those are four systems and three teams — and the handoffs between them are where patients get lost.
- 01
The list never quite reaches the caller
The report that names who needs contact is built in one system and worked in another. By the time outreach opens the file, someone on it has already been readmitted.
- 02
The finding waits in a queue
A patient says something on a call that deserves clinical attention today. Passed between teams it becomes a message, then a task, then tomorrow — and tomorrow is already full.
- 03
The proof never gets written
The contact happened, but the note is retyped later or not at all. At month end nobody can say who was actually reached, so the work cannot be defended — or billed.
So here the record, the intelligence, the patient’s memory, and the conversation are one motion. The record decides who needs contact and gives the conversation that patient’s own history. The conversation writes its own note, its own escalation, and its own billing evidence as it ends — back into the same record. Nothing waits in an export queue for someone to re-enter it.
That is the thesis, and it is why this is a company rather than a feature of something else. Each layer is useful alone. The reason they live together is the seams.
What the same weeks look like with the seams closed.
Close the handoffs and the weeks between visits stop being unstaffed. Three things become true that no amount of extra effort inside the old model could make true.
Routine work finishes on the contact
Booking, refill routing, education, care-gap outreach, and the honest reason a patient declines — completed during the conversation, not queued as tasks for nurses already at capacity.
The care team sees only what needs them
An escalation arrives with the transcript, the sentence that triggered it, and the change against that patient's own baseline — while the conversation is still today's, not tomorrow's.
The next contact starts smarter
What happened writes back into the patient's story and into the next question asked of the population. Nothing is re-asked because two systems were not talking.
And what a patient hears is authored and certified by our clinicians, with your team reviewing every program in full before go-live — the whole model is on Clinical design.
What we hold ourselves to.
Health systems have been sold AI before. These are the commitments that make this worth a second meeting, and every one of them is checkable — on this site, in the contract, or in the software itself.
You can see what ran
Every contact keeps a transcript of what the patient actually heard, and every escalation carries the sentence that caused it. Nothing decides anything you cannot inspect afterwards.
We do not claim what we have not done
There are no customer logos, outcome percentages, or ROI figures on this site, because we do not yet have results we could defend. When we do, they will come with a denominator and a method.
Patient data is not a business model
We do not sell it, and we do not use it to train general-purpose models. It exists in our systems to serve the patient it describes, under your agreement — and it leaves when you do.
When in doubt, hand over
The system's failure mode is chosen, not accidental: a conversation it cannot finish within its program becomes a clinician's conversation, with the transcript attached. It escalates; it does not guess.
Boring where it matters
Patient contact, escalation, and anything touching a record should be predictable and reviewable. The interesting engineering belongs underneath, not in what a patient experiences.
The mechanisms behind all of this are set out in detail on Trust, Security and How we test.
We would rather be told this does not fit.
If continuous follow-up is not your constraint, a short conversation will establish that faster than a demo will.
Talk to our team