The Brain Behind
Clinical Context.
CGM data without context is just noise. Aegle's Context Engine automatically maps glucose fluctuations to real-world behavioral data—meals, meds, and activity—giving you the full clinical story in seconds.
Interaction Timeline
Sarah Jenkins
14:24Anomaly Detected: Glucose spiked to 210 mg/dL. AI captured context: "Whole grain bagel".
Aegle Assistant
Protocol Active
EHR Sync
LIVESyncing with Dr. Simmons
The Problem: Continuous Data, Discontinuous Insight.
Telehealth and Remote Patient Monitoring (RPM) have solved the problem of data collection. However, for a clinician, thousands of data points are often practically useless without the "Why" behind the readings.
Current workflows rely on patient recall or manual logging—both of which suffer from high friction and low compliance. Aegle replaces this manual interaction with an Autonomous Contextualizer.
Temporal Correlation
Our system monitors the delta in glucose levels in real-time. When a significant deviation is detected, our AI triggers a lightweight, natural language conversation with the patient to capture immediate behavioral context—meals, medications, exercise, or stress—while the memory is fresh.
Zero-Retention Triage
The engine processes this raw conversation, isolates the clinical variables, and presents them as a "Contextual Log" to the provider. The AI never replaces clinical judgment; it simply provides the metadata the provider needs to make an informed decision in seconds.
By closing the loop between telemetry and behavior, Aegle transforms a chaotic chart of spikes and dips into a clear, actionable clinical narrative. We call this Clinical Contextualization—and it is the prerequisite for scaling chronic disease management.
Closing the "Context Gap" for clinicians.
Passive Data Streaming
Thousands of data points flow from the patient's CGM through our Junction API bridge directly into our engine.
Automated Context Ingestion
Our AI assistant identifies glucose anomalies and textually interviews the patient via SMS or the Aegle App.
Clinical Decision Support
Providers receive a prioritized feed of "Context-Rich" events, reducing review time from minutes to seconds.
Logic Visualization
Algorithm View: Context Logic
Input: Glucose Delta
+42 mg/dL in 15 mins
Step: Automated Inquiry
"Reviewing spike. Sarah, did you have a meal recently?"
Output: Clinical Metadata
Variable: [High-Carb Meal]
Confidence: [98%]
Ready to see the "Why"?
Scale your metabolic practice with the engine that delivers context, not just data.