1A routine visit
An adult has the routine blood work their care already calls for. No new test is needed to generate the flag.
Health Systems
Surface CKD risk before your patients feel it
Turn routine lab results already on file into a prioritized list for kidney evaluation. NephroSense AI helps clinicians decide who needs confirmatory eGFR and urine albumin testing next.
01
Routine labs
Already on file
02
Clinician review
Priority for kidney evaluation
03
Confirmatory testing
eGFR + urine albumin
Physician oversight at every step
The scale of the gap
87%
of US adults with CKD don't know they have it — the disease advances silently (CDC).
37MUS adults with CKD
SourcesThe Gap in the Record
The record marks an unmeasured patient as unremarkable
One patient, one draw, read two ways. Nothing on either side was ordered specially — the difference is which values get read together.
One patient · routine visitThe same record, read two ways
Today
What the record shows today
Each result read on its own, and the one the record never received.
Routine results — unremarkable, one at a time
Urine albumin (uACR) — not ordered
No flag raised
Nobody decided this patient does not have CKD. Nobody looked.
Read together
The same record, read together
The same values already on file, entered or uploaded into NephroSense AI.
Prioritize — confirmatory kidney evaluation
Suggested next step: eGFR + urine albumin (uACR)
One Patient's Journey
From a routine blood draw to a planned follow-up
What the workflow looks like for one person, with the clinician deciding at every step.
2Flagged for review
NephroSense reads the labs already on file and flags this patient for the clinician, with a confidence signal.
3Confirmatory testing
The clinician reviews the flag and decides whether to order the eGFR and urine albumin tests that confirm or rule out kidney disease.
4Follow-up is planned
The results come back to the clinician, who plans the follow-up. Every diagnosis and treatment decision stays with the care team.
Illustrative journey. The people shown are illustrations, not real patients, and the steps describe the clinical workflow, not a study result.
For Health Systems
What this is measured on
A flag is only worth what happens after it. These are the outcomes a deployment is evaluated against.
Confirmatory-testing completion
Of those flagged, how many received the eGFR and urine albumin testing KDIGO recommends.
Confirmed-risk yield
How many flagged patients were confirmed on follow-up — whether the flag is worth acting on.
Referral completion
Whether patients needing nephrology or care-management follow-up actually reached it.
Workflow burden
Review time per flagged patient, and whether the flag arrives inside an existing workflow.
Solutions
Beside the chart today, inside it next
Risk triage runs today, beside the chart. The EHR integration puts the same output inside it, and is in development. Different buyers, and each carries the stage it has reached.
Risk triage
Available todayCKD risk triage from the panel you already drew
The primary workflow reads a routine adult workup — blood work and vitals already recorded in ordinary care — and returns a CKD risk score with KDIGO-aligned clinical considerations in under ten seconds. No additional screening order, no new hardware. The output is a prioritization: which patients should move to the front of the queue for the confirmatory eGFR and urine albumin testing KDIGO already recommends.
Where this stops: NephroSense AI is Clinical Decision Support, not a diagnostic. It does not replace urine testing, eGFR or any other test, and it does not diagnose CKD. Confirmatory kidney testing is ordered by the clinician after a patient is flagged, and every clinical decision remains the provider's, based on a complete patient evaluation.
Reports and exports
nephrosenseai.com
Generated Report
CKD Risk Assessment Report
Synthetic patient · Generated Mar 15, 2026
Complete
Illustrative — synthetic data. Not a real patient or a performance claim.
- Instant risk assessment
- Enter adult patient biomarkers or upload a lab report; a CKD risk score returns in under ten seconds.
- Clinical considerations
- KDIGO-aligned considerations sorted by urgency — high, moderate, routine — each with a next step.
- Confidence signal
- Every prediction carries an explicit confidence signal, so the basis for the score is visible rather than assumed.
- What-if simulator
- Adjust biomarker values and see how the risk score responds.
- Reports and exports
- A PDF with the risk score and considerations for the patient record, plus FHIR R4-shaped output for exchange with existing systems.
- Follow-up planning
- Prioritize confirmatory testing, referral urgency and longitudinal monitoring under physician oversight once a patient is flagged.
Clinicians, primary care groups, FQHCs
EHR integration
Designed, in buildThe same output, inside the chart instead of beside it
Risk triage runs alongside the chart; the EHR integration would run inside it. It is the embedded layer, returning structured risk into the record and following what happens after a patient is flagged. That integration work is underway now.
What it is designed to do
- Automatic lab ingestion
- Reading results from the EHR as they post, so a patient is scored on the panel already in the record rather than on values re-entered by hand.
- Embedded order sets
- Drafting the confirmatory tests and, where indicated, the referral the moment a patient is flagged, configurable to a group's standard of care, for the clinician to review and sign.
- Referral routing and closure
- Following a flagged patient through to whether the referral and confirmatory test completed — the outcomes a deployment is evaluated on.
What has to be true first: A first site. The engineering is in progress; what it needs alongside that is an institution willing to co-design the workflow placement and do the interface and governance work any EHR integration requires there.
Scope: The integration changes where the output lands, not what the model does or what it is permitted to claim. Until it ships, risk triage reaches clinicians through the standalone workflow and the FHIR R4-shaped output it already emits.
Embedded order setsConcept — in development
nephrosenseai.com
Order Set
DraftPatient flagged for kidney evaluation
Confirmatory Tests
eGFRUrine Albumin (uACR)
Referral, if indicated
Nephrology
Clinician reviews and signs
Configurable to your standard of care
Illustrative — synthetic data. Not a real patient or a performance claim.
CMIO, clinical informatics, IT
Evidence
Where the evidence stands
Stated plainly, because you should not have to ask for it.
Retrospective feasibility demonstrated on a US adult clinical cohort. Retrospective external testing on an independent US cohort is complete; the result is company-reported, unpublished and not yet peer reviewed.
What this is, regulatorily
NephroSense AI is a Clinical Decision Support tool for use by licensed healthcare professionals with physician oversight. It does not provide medical diagnoses and does not replace any laboratory or diagnostic tests. By integrating a patient's existing clinical data faster, it helps clinicians prioritize who needs confirmatory testing and follow-up sooner. All clinical decisions must be made by qualified healthcare providers based on a complete patient evaluation.
One Platform
One platform, whichever question you arrived with
Health systems and trial sponsors ask different questions. Each application requires its own model and its own validation, but all of them are built on one platform: the same routine-panel inputs, the same deployment architecture, the same IP.
Routine inputs, already on file
The model reads values already present in a routine adult workup — drawn and paid for as part of ordinary care. No new assay, no new visit, no new hardware.
Model-to-data by design
Institutional deployments are designed so that inference runs inside your environment as a query-only container — patient-level data does not leave it, and the model is not transferred to you as weights.
Your environment
Your records
Values already on file
Query-only container
Inference runs here
Your team
Receives the output
- Patient-level data does not leave
- The model is not transferred as weights
Patent-pending technology. Provisional patent filed March 2026.
Getting Started
Three steps, and you can stop after any of them
Nothing here requires a commitment to the next thing. The first one does not require talking to us at all.
Run it yourself
Open the demo application and put your own values through it. Nothing to install, no conversation required.
What it settlesWhether the output is something your clinicians would act on.
Retrospective look-back
We run the model against a de-identified extract of your own patients and report what it would have surfaced, against what actually happened.
What it settlesWhether the signal is there in your population, before any deployment.
Scoped pilot
A defined cohort, a defined workflow placement, and the outcome measures above agreed in advance.
What it settlesWhether it changes confirmatory-testing and referral completion in practice.
Before procurement asks
- Deployment
- Output is built on HL7 FHIR R4 for clinical data exchange. Embedded EHR deployment is in development.
- Agreements
- BAA and data-use agreements executed per engagement, with the scope of data covered agreed in writing before any extract moves.
FAQ
Frequently asked questions
Do I need new equipment?
How long does it take?
Is NephroSense AI a diagnostic tool?
Can it integrate with my EHR?
What if I only have routine labs?
Is this aligned with screening guidelines?
See what it surfaces in your own population
A retrospective look-back reports what the model would have surfaced, against what actually happened.
Running a kidney or cardio-renal trial? The same platform surfaces a candidate population for confirmatory screening. For biopharma →