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January has been building glucose prediction models since 2020 and publishing the results. Explore our benchmarks, methodology, peer-reviewed research, and scientific advisors.

88%Endocrinology board exam accuracy
0.8%Hallucination rate on clinical cases
Patented techPatent portfolio

Measured against a real endocrinology board exam

88%

Highest endocrinology benchmark score

Our Health Context Engine outperforms GPT, Gemini, and human clinicians on the endocrine medical board exam. Retrieval runs against a curated internal corpus of clinical guidelines and peer-reviewed literature rather than the open web.

0.8%

Hallucination rate

The engine produced hallucinations in 0.8% of cases and contradictions in 1.8%, significantly lower than general-purpose frontier models tested on the same clinical cases.

2h

Forward glucose prediction

CGM-based glucose predictions 2 hours into the future, and virtual continuous glucose curves for people who don't wear a CGM.

Measured behavior change in the January app

Protein intake

+6.9%

Carb intake

-3.5%

Fiber intake

+13.8%

Sugar intake

-16.7%

Participants who lost weight

74.4%

Time in Healthy Glucose Range for people with T2D *

49.7% => 57.4%

* Every 5% increase in Time in Range is clinically meaningful for people with type 2 diabetes.

Six years of models, in order

2020

CGM-based glucose predictions 2 hours into the future

2021

Accurate post-CGM predictions

2022

Virtual continuous glucose curves

2023

Millions of data points from thousands of patients inform a probabilistic model without sensors

2025

Health Context Engine built on a medical-grade personal health knowledge graph

2026+

Integrated patient application and clinical decision support tools

Peer-reviewed papers

2025 npj Digital Medicine

Health Context Engine on a medical-grade personal health knowledge graph

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2023 npj Digital Medicine

Glucose prediction and behavior change without continuous sensors

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2021 Diabetes Therapy

Digital program outcomes for people living with type 2 diabetes

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2025 ADA Scientific Sessions

Evaluating a flexible, AI-supported digital diabetes program

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2021 IEEE

Machine-learning blood glucose prediction from CGM data

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Methodology reviewed by our AI and Scientific Advisory Boards. Meet them

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