AI Clinical Decision Support · Diabetes

See every dimension
of your patients' risk

Diamensions uses AI to help care teams identify deteriorating diabetic patients before a crisis — not after.

38M+ diabetic patients in the US
$327B annual cost of diagnosed diabetes
30% miss HbA1c targets every year

The cost of reactive diabetes care

Most health systems only act when patients are already in crisis. By then, the damage — and the bill — is done.

$16,000

Average cost per diabetes-related hospitalization — preventable with earlier intervention.

30%

Of diabetic patients miss their HbA1c targets annually, often without anyone noticing.

1 in 3

High-risk patients never receive proactive outreach from their care team.

From raw data to clinical action

Three steps that turn fragmented health records into a clear, prioritized view of patient risk.

Step 01

Ingest

Pulls in EHR data, labs, pharmacy refills, and clinical notes — all the signals that typically live in silos.

Step 02

Stratify

AI identifies patients silently drifting toward complications — weeks before a lab value turns critical.

Step 03

Act

Clinicians get a prioritized daily worklist — not another dashboard to wade through before morning rounds.

Built for the realities of clinical care

We didn't build another analytics platform. We built a clinical ally.

Proactive, not reactive

Catch silent deterioration weeks before a hospitalization. Give care teams the time to intervene when it actually makes a difference.

Research-backed

Built at the intersection of AI research and clinical care — grounded in peer-reviewed evidence, validated on real patient populations.

Designed for clinicians

Every design decision reduces cognitive load, not adds to it. Diamensions fits into existing clinical workflows instead of disrupting them.

Launching April 2026

We're running our first pilot in April 2026

Limited spots available for forward-thinking health systems ready to move from reactive to proactive diabetes care.

No spam. We'll reach out within 2 business days.