Unified longitudinal health data
Combine clinical records, labs, medications, wearables, nutrition, and lifestyle logs into one longitudinal health view that can be used by both care teams and patients.
January AI unifies clinical, lifestyle and biomarker data to deliver personalized health insights, food logging and glucose predictions for apps, clinicians and care teams.
January AI is a precision health platform that unifies fragmented health data and applies its Health Context Engine to generate clinically grounded insights for care teams, consumer apps, and individual users. The site positions the product as a layer that connects clinical records, labs, medications, wearables, nutrition, and other health signals into one longitudinal view.
The platform is presented in two main forms: an app for consumers and APIs and workflow components for product teams and clinical organizations. Across those formats, January focuses on food logging, glucose prediction, personalized nutrition guidance, and health recommendations based on connected data rather than isolated data points.
Combine clinical records, labs, medications, wearables, nutrition, and lifestyle logs into one longitudinal health view that can be used by both care teams and patients.
Use January’s Health Context Engine to turn fragmented inputs into clinically grounded risks, trends, correlations, and next-best actions.
Embed food logging, glucose predictions, nutritional intelligence, and personalized recommendations into an existing consumer product through APIs.
Support photo-based meal logging, voice or text search, barcode search, and editing of meal results inside the experience.
Surface patient insights inside dashboards, reports, EHR-connected workflows, or white-label apps for care teams and clinical programs.
Provide personalized health coaching and recommendations in the January app, which connects habits, biomarkers, and clinical data.
Clinical teams can bring in labs, medications, wearables, and other patient data, then use January’s Health Context Engine to identify risks, trends, and next-best actions inside care workflows.
Consumer health apps can add food scanning, food search, glucose predictions, and personalized recommendations through January’s APIs without building those capabilities from scratch.
Patients can use the January app to connect their habits, biomarkers, and clinical data, then review personalized coaching and recommendations tied to their own health picture.
Product teams can launch a branded patient experience using white-label app workflows powered by January’s context engine.
Nutrition and metabolic health products can let users log meals by photo, voice, text, or barcode while showing predicted glucose impact and food alternatives.
January connects clinical records, labs, medications, wearables, nutrition, and lifestyle data into a longitudinal view, then applies its Health Context Engine to surface risks, trends, and next-best actions.
The source shows both a consumer iOS app and API-based offerings for product teams. The app is for people who want personalized health insights, while the APIs and workflows are aimed at consumer health platforms, clinicians, and care teams.
January’s app and APIs support food logging, glucose predictions, personalized nutrition guidance, and clinically grounded insights built from connected health data.
The source describes integrations through APIs, EHR-connected workflows, dashboards, reports, white-label apps, and mobile apps, but it does not list named third-party integrations on the pages provided.
The site does not publish a pricing page at the provided URL. The nutritional intelligence page states that plans start at $1,499 per month, but the exact plan details and limits are not fully described there.