Intelligence shaped around the person.
MATILDA combines a purpose-built machine-learning model, connected health data and AWS-powered infrastructure to build a changing picture of each person’s habits, routines and health context.
Health signalsDaily contextPersonal baselineChanging patternsUseful next steps
Connected data. Individual intelligence. Clear destinations.
See how authorized health signals move through MATILDA’s cloud foundation into individualized models, auditable recommendations, conversational support and the provider portal.
A model designed for individual lives, not average behavior.
MATILDA’s machine-learning model was developed in-house to form a personalized understanding of each user. It learns from connected metrics and the circumstances surrounding them, then adapts as the person’s life and data change.
Personal from the start
The model organizes information around the individual’s own history, routines and goals.
Context stays attached
Meals, activity, sleep, medication and personal observations remain connected to the readings they may help explain.
Designed to adapt
New information supports rapid model updates, helping MATILDA remain relevant as patterns change. Lightweight user models can be loaded, updated and unloaded efficiently as patient needs evolve.
Learn the person’s baseline, preserve daily context and adapt as routines change.
Understand changes, explore suggestions that fit daily life and share context with authorized care teams.
From scattered signals to useful context.
MATILDA does more than place information on the same screen. Its intelligence layer preserves timing and relationships, compares new events with the user’s evolving baseline and presents patterns in a form people and care teams can review.
Scalable servicesReliable data processingSecure architectureResponsive experiences
A cloud foundation built to support connected intelligence.
MATILDA uses AWS to support data processing, model operations and responsive product experiences. Cloud resources can expand or contract with demand, helping the system scale efficiently while aligning infrastructure cost with actual use.
Data resiliency is supported through multiple operating and storage locations so services and information can recover if a location becomes unavailable. The deployment system is cloud-provider agnostic, preserving the option to change providers or adopt a multi-cloud architecture when the product requires it.
AWS provides the current cloud foundation. MATILDA’s in-house model provides the patient-specific intelligence.
The model changes as the person changes.
Health behavior is not static. Schedules shift, preferences change and new information becomes available. MATILDA was designed to retrain its personalized understanding with each user’s authorized data so its view can evolve with them.
Built for understandable recommendations and flexible delivery.
The technology is designed to connect many data sources, keep recommendations traceable and support the different ways people and trusted professionals interact with MATILDA.
One model for each user
Each person has an individualized machine-learning model that learns their own baseline, routines and changing patterns for truly tailored recommendations.
A visible path to the recommendation
The individualized model can provide structured traces used by the language layer, making it easier to examine why a recommendation was produced.
Fast loading and updating
Lightweight models support rapid loading, unloading and updates without treating every patient as one large shared model.
Many sources, one experience
The platform is designed to ingest and assimilate authorized information from separate sources, including workflows initiated directly in the application.
Voice as well as text
Audio integration with cloud services allows the chatbot experience to become conversational while retaining the context behind the response.
Trusted sharing without reconstruction
With user authorization, the provider portal gives trusted medical professionals a connected view of readings, patterns and relevant context.
Powerful technology needs clear boundaries.
MATILDA organizes information, identifies patterns and supports more informed choices and conversations. It does not replace clinical judgment.
The clinician makes medical decisions.
MATILDA can surface context for review, while licensed professionals remain responsible for diagnosis, recommendations and treatment.
Access depends on authorization.
Care-team visibility is tied to the patient’s permission and the access model surrounding their account.
MATILDA is not emergency monitoring.
The platform does not automatically intervene, dispatch assistance or guarantee immediate clinician review.
The intelligence matters because the person does.
Explore the research principles and evidence framework guiding MATILDA’s continued development.