Platform

Mobile apps

The Android and iOS apps are built for the daily routine. Both are native applications that connect to the phone's health platform, so data from rings, bands, watches and glucose monitors flows into the model without manual entry.

• Today

  Current state, active substances with their timing, the day's forecasts, and quick actions to log a meal, a dose or a workout.

• Nutrition

  Meal logging by photo, text or catalogue, with a glucose forecast for each meal and a daily nutrition summary.

• Stack

  Supplements and medications with schedules, interaction analysis, enzyme load, adherence tracking, dose reminders and a timeline of each substance in the body.

• Simulate

  A continuously running personal model, what-if comparisons, history and lineage of every run, and plain-language explanations of any result.

• Profile

  Personal parameters, connected devices, calibration status, genetic profile, blood panels and subscription.

• Offline and background

  Logging works offline and syncs later. Device data is synchronised in the background so calibration runs without opening the app.

Web application

The web application provides the same account and feature set on a larger screen, with a focus on longer-horizon analysis: multi-day and multi-week trajectories, side-by-side comparison of simulations, trend and insight review, data import from CSV and lab reports, and export of personal data in standard formats. Subscription management and API key administration are also handled on the web.

API

Everything the apps do is available through a documented REST API with tiered access for individuals, developers and research use. Research tiers extend simulation horizon, resolution and retention. A separate partner service provides stateless forecasts and accuracy reporting for organisations that integrate the engine into their own products; see the partners page.

Wearable integrations

Measurements from connected devices anchor the model to reality. The following sources are supported now.

• Phone health platforms

  Apple Health on iOS and Health Connect on Android, covering glucose, heart rate, heart-rate variability, steps and exercise, sleep stages, weight and body composition, oxygen saturation, respiratory rate, skin temperature and fitness estimates. Most rings, bands and watches reach SomaTapestry through this route.

• Continuous glucose monitors

  A direct server-side connection to a leading CGM platform, available from all clients, with additional CGM providers planned.

• Files and manual entry

  CSV import for any time series, and manual or imported blood panels covering glucose, HbA1c, insulin, lipids and more.

• Background sync

  Device data is pulled at regular intervals on mobile so forecasts and calibration stay current.

Direct connectors for additional wearable and CGM vendors are in development, so that users of those devices can connect without going through the phone health platform.

Medical and research equipment

SomaTapestry's positioning as a research tool sets the direction of its integration roadmap. Consumer wearables establish the daily loop; the next stage is to bring in the instruments that research groups and specialist practices already use, so that a mechanistic model can be calibrated and validated against clinical-grade measurements. None of the following is available today. It is planned work, sequenced by research demand.

• Clinical-grade CGMs and laboratory panels

  Professional continuous glucose monitoring systems used in studies, and direct import of laboratory results, including glucose, HbA1c, insulin and C-peptide, lipids and hormone panels, from laboratory information systems.

• Metabolic and body-composition instruments

  Indirect calorimetry for measured energy expenditure and substrate use, DEXA and bioimpedance body composition, and resting metabolic rate measurements, used to calibrate the energy balance and body-composition components of the model.

• Cardiac and sleep instruments

  ECG and Holter monitoring, ambulatory blood pressure, and polysomnography, providing clinical-grade signals for the autonomic, cardiovascular and sleep components of the model.

• Research study platforms

  Connections to electronic data capture and clinical trial systems, standardised exports for study cohorts, and de-identified data pipelines so that research groups can run the engine against their own populations under their own governance.

Each integration will follow the same evidence process as a model change: the instrument's measurement characteristics are documented, the mapping into the model is reviewed, and accuracy is reported against held-out data before the integration is released.