Dr. Michael Snyder
Co-Founder, January AI

Why glucose is key to good health

At January, our mission is to increase the world’s “healthspan”—the number of years we remain in good health, free of chronic disease. Research continues to show that managing blood sugar is core to the cause, driven by its ability to regulate weight, cholesterol, inflammation, and so much more.

Now, for the first time, the January app harnesses powerful AI technology to help you better manage your glucose and build the habits that lead to a longer, healthier life.

January’s impact

Our cutting-edge research combines metabolic science, behavioral psychology, and world-class AI. After clinically proving that CGMs lead to weight loss, we successfully proved that AI can enable sustained behavioral change. Our peer-reviewed research validates what we’ve seen firsthand - that our users experience higher glucose control, weight loss, and more.

The Results

16.2
%

Reduction in caloric intake

-4.1 lbs

Mean weight reduction (12-wks)

58
%

Improved Time in Range (70-140 mg/dL)

11.6
%

Increased relative protein intake

22.8
%

Increased relative fiber intake

4.2
%

Reduced carbohydrate intake

7.3
%

Reduction in caloric intake

-10.4 lbs

Mean weight reduction (12-wks)

63
%

Improved Time in Range (70-140 mg/dL)

*Improvement in estimated A1c=0.28%
10.6
%

Increased protein intake relative to total calorie

23.9
%

Increased fiber intake relative to total calorie

4.4
%

Reduced carbohydrate intake

Our Research

We’ve authored multiple whitepapers with rigorously designed clinical studies in metabolic health. This research has enabled our proprietary AI system to accurately predict glucose responses and has validated the impact of the January product.

0

Digital health application integrating wearable data and behavioral patterns improves metabolic health

1

Virtual Blood Glucose Monitoring and Prediction Using Machine Learning

1

Machine-Learned Prediction of Glucose Response

2

Heart Rate and CGM Feature Representation Diabetes Detection From Heart Rate: Learning Joint Features of Heart Rate and Continuous Glucose Monitors Yields Better Representations

3

Machine-Learned Prediction of Glucose Response for 1000 Subjects

4

Improvement in Glucose Regulation Using a Digital Tracker and Continuous Glucose Monitoring in Healthy Adults and Those with Type 2 Diabetes

5

Digital Health: Tracking Physiomes and Activity Using Wearable Biosensors Reveals Useful Health-Related Information

6

Glucotypes reveal new patterns of glucose dysregulation

7

A longitudinal big data approach for precision health

8

Personal aging markers and ageotypes revealed by deep longitudinal profiling

9

Deep longitudinal multiomics profiling reveals two biological seasonal patterns in California

10

Pre-symptomatic detection of COVID-19 from smartwatch data

Our Advisors

Meet the experts behind our groundbreaking research.

Scientific Advisory Board

Dean at the Tufts Friedman School of Nutrition Science and Policy, and Professor of Medicine at Tufts Medical School
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Dariush Mozaffarian, MD, PhD
Scientific Advisor
Professor of Medicine, Stanford School of Medicine, Endocrinology, Gerontology, & Metabolism
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Tracey McLaughlin, MD, MS
Scientific Advisor
Assistant Professor, Stanford School of Medicine. Artificial Intelligence, Machine Learning, and Multiomics Integration for Clinical Immunology
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Nima Aghaeepour, PhD
Scientific Advisor
Associate Professor of Microbiology & Immunology, Stanford, NIH Director’s Pioneer Award Winner
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Justin Sonnenburg, PhD
Scientific Advisor
Research Dietitian, Stanford University
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Dalia Perelman
Scientific Advisor
Associate Professor University of Michigan Medical School Department of Microbiology & Immunology
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Eric Martens, PhD
Scientific Advisor
Founder at Nautilus Biotechnology and Associate Professor at Stanford University
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Parag Mallick, PhD
Scientific Advisor
Professor Emeritus, Friedman School of Nutrition Science and Policy at Tufts University and Chair, American Nutrition Association Board of Directors
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Jeffrey Blumberg, PhD
Scientific Advisor

AI Advisory Board

Professor UC Berkeley, Founder/President/Chief Scientist covariant.ai (formerly Embodied Intelligence), Founder Gradescope
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Pieter Abeel, PhD
AI Advisor
Associate Professor of Computer Science, Stanford University, Chief Scientist at Pinterest, and investigator at Chan Zuckerberg Biohub
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Jure Leskovec, PhD
AI Advisor
Assistant Professor, Department of Electrical Engineering and Computer Sciences, UC Berkeley.
Read more
Sergey Levine, PhD
AI Advisor
Assistant Professor at Carnegie Mellon University
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Zico Kolter, PhD
AI Advisor

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