Know what your patients do between sessions.

A session lasts an hour. The behavior that decides the outcome happens in the weeks between. We turn what your clients actually log into a read on those weeks, and show the source of every number.

+See the weeks between+Cut the admin+Prove outcomes

Care happens in the session. Outcomes happen in the weeks between. We make those weeks visible, sourced, and yours to act on.

Book a demo

A 20-minute walkthrough on a real, de-identified case. No slides.

~How it works

Three steps. One source of truth.

01

Patients log in Redu

Meals, glucose, steps, and sleep, logged in seconds on their phone. It lands on your dashboard automatically.

02

GlucoSolutions interprets the behavior

Every insight traces to the exact readings behind it, with the computation in plain sight. No black box.

03

You act with confidence

Walk into each session prepped, message patients between visits, and export outcomes your referrers trust.

ER
Prediabetes reversal
Elena Rodriguez
GS-4821· Active
Logged in Redu

Elena · glucose + meals · today

12a4a8a12p4p8pnow
Sourced insight
Interpretation · this week

Elena's afternoons run higher on the days she skips her morning walk.

Source14 days CGM + step logsComputation138 vs 116 mg/dL Traceable
Pre-session outcomes
94
Metabolic score
Fibre intake
27g/day
Sleep
7.2h/night
Daily steps
8,924/day

Your clinician dashboard, built from what your patients log.

~Capabilities

Every signal they log, in one personalized view.

Meals
Glucose
Movement
Sleep
Fibre
Mood
ER
Elena Rodriguez
This week
Live

Glucose · this week

12a4a8a12p4p8pnow
Steps
8,924
Sleep
7.2h
Fibre
27g
Walk before lunch keeps her afternoons steady.

Meals, glucose, movement, sleep, and more, organized into one read on the weeks between sessions.

Available

Workflow automation

Pre-session summaries, auto-organized logs, and less time charting. Walk in already knowing what changed.

+Pre-session summaries
+Auto-organized logs
+Less charting
Pre-session summary
  • Glucose steadier on weekdays than weekends
  • Logging consistency up to 6 of 7 days
  • Two post-dinner spikes flagged for review
Session prep ready
Available

Between-session continuity

A live view of patient behavior, day to day. Message in-app, catch drift in week two instead of week four.

+Live behavior view
+In-app messaging
+Drift alerts

This week · day to day

12a4a8a12p4p8pnow

“Nice work pairing carbs with protein at lunch. That flattened your afternoon. Let's keep it going this week.”

In development

Outcomes reporting

One-click reports for referring physicians, covering glucose trends, habits, and behavior change, formatted to win the next referral.

+Glucose trends
+Habits
+Physician-ready
Outcomes report · preview
Fibre intake
27g
Active days
5/7
Avg sleep
7.2h

Physician-ready summary · building this now with our launch RD.

~Provenance

AI insight that shows its work.

Most AI tools hand you a conclusion and hide the math. GlucoSolutions does the opposite. Every interpretation traces to the exact data it came from, shows the reasoning steps, and shows how each data point was used, so you can trust it, correct it, and defend it to a physician.

You stay the clinician. The software just stops hiding its evidence.

Sourced insight Traceable

Maya's afternoons run higher on days she skips her morning walk.

Source

14 days of glucose readings + step logs from Redu.

Computation

Afternoon average 138 mg/dL on no-walk days vs 116 on walk days.

How it's used

Flagged 3 of 4 no-walk days exceeded the 140 target. You can open every reading behind it.

Every claim is a sourced fact, not a guess.

~Redu

Redu is the patient's half of the system.

Redu is the app your patients actually use. Low-friction logging, a second-chance framing that keeps people coming back, and the engagement that makes everything above possible. Included with your subscription at no cost to your patients.

More about Redu
The Redu patient app home screen: metabolic score, personalized tips, and daily logging.

~Security

Built for PHI from day one.

How we handle data
  • Encrypted storage and row-level access controls.

  • Data minimization for AI features before production patient use.

  • Written data protection agreements before real patient data is used.

Encrypted storage
Row-level access
AI data minimization
Written agreements