Now accepting early access applications

CGM data in.
Chart-ready notes out.

Ekabolic transforms continuous glucose monitoring data into AI-generated clinical documentation with per-sentence provenance, built for endocrinologists, diabetes educators, and PCPs managing diabetes.

HIPAA-compliant by designProvider-in-the-loopProvenance on every sentence

Why now

THE CHALLENGE

CGM adoption is outpacing clinical workflow

More patients on CGM means more data to interpret, but documentation still happens manually. Providers spend valuable encounter time narrating glucose patterns aloud or scrolling through AGP reports to write A&P notes by hand.

THE SOLUTION

AI that reads the glucose, writes the note

Ekabolic ingests Dexcom and Libre data, computes deterministic glycemic metrics, detects 16+ pattern types across 24-hour and 14-day windows, and composes draft A&P documentation before the encounter starts.

THE OUTCOME

Review, edit, paste. Encounter time reclaimed.

Every sentence traces back to specific patient data, not a generic summary. Review the draft, make edits, and paste directly into your EHR. Documentation that used to take 8 to 12 minutes per CGM patient now takes under 2.

Capabilities

From raw glucose to clinical narrative

A deterministic compute pipeline feeds structured data to constrained AI composition, so you get traceable, editable documentation, not a black-box summary.

0

Deterministic Glycemic Metrics

0+

Dual-Window Pattern Detection

03

AI-Composed Clinical Documentation

0

EHR-Paste-Ready Output

The science

Deterministic by design. Composed with intent.

Raw sensor values become published-algorithm metrics, then confidence-scored patterns, then a structured note. The math is reproducible, the prose is constrained, and every claim stays anchored to the signal it came from.

Raw CGM signalDeterministic metricsConfidence-scored patternsStructured note

How it works

Three steps. Under two minutes.

01

Connect CGM

Link your patients' Dexcom or Libre accounts. Data syncs automatically before each encounter.

02

Open encounter

Metrics compute, patterns surface, and a draft clinical note generates, all within seconds.

03

Review & paste

Edit the AI draft as needed, then paste directly into your EHR. Every sentence traces back to the data.

Why Ekabolic

Not another CGM dashboard

Existing platforms show you the data. Ekabolic interprets it, documents it, and gives you a draft you can review and paste, so the encounter is about the patient, not the paperwork.

CGM data analysis
Others: Displays AGP charts and summary stats
Ekabolic: Computes metrics, detects 16+ patterns, fuses acute + chronic signals
Clinical documentation
Others: None. You write the note
Ekabolic: AI-generated draft A&P, patient letters, messages
Provenance
Others: None
Ekabolic: Per-sentence evidence IDs linking every claim to patient data
EHR workflow
Others: Separate portal to log into
Ekabolic: Copy-paste plain/rich text or HL7 CDA export
AI approach
Others: LLM on raw data or no AI at all
Ekabolic: Deterministic compute, structured data, constrained LLM composition
Metabolic wellness
Others: Diabetes-only focus
Ekabolic: Non-DM CGM interpretation, insulin resistance proxies, progression risk

Built for clinical trust

AI you can verify, not just trust

HIPAA-compliant by design

No PHI in logs, no PHI in email. Built for clinical data from day one.

Deterministic, not stochastic

Metrics and patterns are computed with published algorithms. The LLM never touches the math.

Provider-in-the-loop

Every output is a draft. Mandatory review before anything reaches the chart. No autonomous actions.

Provenance, not vibes

Per-sentence evidence IDs link each claim to the specific CGM data that generated it. Audit-ready.