Heart disease doesn't travel alone.

Every risk model on the market treats it like it does — cardiac in one silo, renal in another, metabolic in a third. Cardiograph is the first predictive intelligence layer built for the whole syndrome.

Book a 30-minute demo Live in production. Not a concept.

One member. Six conditions. Every one of them talking to the others.

The problem

The risk lives in the connections. The tooling doesn't see them.

The American Heart Association named cardio-kidney-metabolic syndrome because these conditions accelerate one another. Most population health stacks still score them separately, then hand a care manager six unranked lists and no explanation of why anyone is on them.

Cardiac risk scores
Built from cardiac data. Blind to a falling eGFR.
Renal registries
Flag stage progression after it has already happened.
Diabetes programs
Optimize A1c without seeing ejection fraction.
Social risk data
Captured, stored, and rarely joined to anything clinical.
The result
The member whose conditions are compounding fastest looks average in every individual model.

The platform

An intelligence layer, not another system of record.

Cardiograph sits between the data you already capture and the interventions you already run. It doesn't replace your EHR, your care management platform, or your outreach engine — it tells them who to act on and why.

Signal in

Whatever you already have

Claims, labs, EHR extracts, remote monitoring, in-home assessments, retail screening, social determinants. Cardiograph ingests through an API-first interface and builds each member into a connected clinical graph.

Reasoning

Graph and vector fusion

Conditions, medications, labs, encounters, and social factors become traversable relationships. Retrieval blends structural proximity, semantic similarity, and trajectory over time — so the model reads a patient the way a clinician does.

Action out

A ranked list with its reasoning attached

Every score arrives with the path that produced it: the conditions, the trend, the gaps. Care teams get a defensible reason to pick up the phone, and agents can trigger outreach, monitoring, and scheduling from the same signal.

Architecture

Built for teams that will ask how it works.

A composite score, weighted across three independent retrieval signals — tunable per population, per program, per contract.

composite = α · graph  +  β · vector  +  γ · temporal

Graph

A property graph of conditions, comorbidity paths, medications, and care events. Relationship depth and density carry real clinical weight.

Vector

Semantic retrieval across narrative and unstructured context, so a member resembles the cohort they actually resemble — not just the one their codes suggest.

Temporal

Direction and velocity of change. A stable stage-3 patient and a rapidly declining one are not the same risk, and the score reflects it.

Who it's for

Organizations that carry the risk and own the intervention.

Health plans

Stratify CKM risk across the book, sharpen risk adjustment and Stars-linked outreach, and give care management a prioritized list it can defend.

Health systems

Surface the multi-organ patients moving between cardiology, nephrology, and endocrinology without anyone owning the whole picture.

Value-based care organizations

Point finite care management capacity at the members whose trajectories are compounding, before the admission.

Cardiovascular physician networks

Bring a defensible risk layer to value-based contracts across a distributed network, without asking practices to change how they document.

Who built it

Twenty-seven years of shipping health technology that had to work in production.

Cardiograph was built by an operator, not assembled for a raise. It runs today, against a full synthetic cohort that is statistically calibrated to real CKM population distributions — which means you can see the whole thing work in thirty minutes rather than reading about it.

Brian LichtlinFounder and Architect, Cardiograph.ai
Chief Technology Officer, MDLIVEVirtual care platform serving 60M+ covered lives, now part of Evernorth / Cigna.
Founder, MedAppzEarly electronic health record platform, built and taken to market.

See it running on a live cohort.

Thirty minutes, no deck. We'll pull up a patient, walk the graph, and show you exactly how the score was produced.