A system that models your health and adapts in real time.
SETPOINT builds a personalized Twin, interprets your current state, and continuously adjusts what you should do next—based on your response over time.
Health systems don’t understand you over time.
Most tools track metrics, surface snapshots, or recommend static routines. They don’t model how your system changes. Without memory, interpretation, and adaptation, personalization breaks down.
Most systems wait until symptoms become events.
Static recommendations ignore individual trajectory.
Data accumulates, but the system does not learn.
From input to adaptation—continuously.
SETPOINT is a closed-loop system. It builds a model, interprets state, guides action, and updates through feedback.
Signals, symptoms, goals, and context
A personalized model initialized from your profile
Current interpretation of where you are
Adaptive next actions
Structured execution
Response updates the model
Plan recalibrates over time
Your Twin is the model the system updates over time.
SETPOINT initializes a personalized Twin during onboarding, then refines it through feedback, trajectory memory, and cohort calibration.
Goals, symptoms, load, history, and current context create the starting model.
Cohorts and reference humans help establish baseline ranges and expected trajectories.
The Twin feeds state interpretation, plan selection, and protocol decisions.
Sessions and check-ins update the model, confidence, and projected next state.
A structured system, not a single feature.
SETPOINT connects data, models, decisions, protocols, sessions, and feedback into one longitudinal system.
Structured interventions, selected by state.
SETPOINT does not serve generic content. StateK selects protocols from a structured library, then adapts sessions based on response.
Downregulation protocol for elevated load and reduced recovery.
Consistency protocol for maintaining progress and reducing regression.
Variation logic used when feedback shows no meaningful change.
One system, multiple surfaces.
SETPOINT operates through user, clinician, and system intelligence interfaces.
State visibility, sessions, feedback, trajectory.
Patient state, plan oversight, decision traceability.
Cohorts, calibration, protocols, audit, performance.
Cohort-aware by design.
DT4H calibrates the Twin against cohorts, reference humans, baseline patterns, and expected trajectories. Your model is not isolated—it is continuously calibrated.
A signal—not the system.
SPI is a derived longitudinal signal inside SETPOINT. It reflects state and trajectory, but it is not the product.
How the system adapts over time.
A simple example of how SETPOINT interprets, acts, and updates based on feedback.
Designed for rigor.
SETPOINT supports precision health workflows; it does not replace clinical judgment.
State, plan, protocol, and updates are traceable.
Reasoning is visible where decisions affect action.
Start your system.
See how your model evolves from input, state, action, and feedback.