WHOLECONTEXT AI™

Healthcare’s missing
intelligence layer.

A research platform designed to connect the evolving story of a person’s health—across observations, records, public data, and care coordination.

THE QUESTION

What gets lost
between the records?

Complex chronic illness unfolds over time. Symptoms change. Records sit in different places. Environmental context and daily observations may never reach a clinical conversation.

WholeContext AI explores how these fragments can become a coherent, traceable view that helps people prepare, communicate, and coordinate. The initial focus is Lyme and related complex chronic conditions.

01 / CONNECT THE STORY

Longitudinal evidence

Bring observations and records into a timeline, retain source links, and distinguish patient-reported information from clinical evidence and AI-generated interpretation.

02 / EXPLORE CONTEXT

OpenDataDelta &
Discovery Lab

Explore public health, environmental, and community information in local context. Population-level signals support investigation; they do not establish an individual diagnosis.

03 / SUPPORT THE NEXT STEP

Care coordination

Organize visit preparation, clinician briefs, care-circle perspectives, and next steps so important questions and responsibilities are easier to follow.

Research-stage, with human review. Public demonstrations use synthetic patient stories. WholeContext AI is not a diagnostic service, a substitute for clinical judgment, or a validated predictor of individual health outcomes.

RECOGNITION & DIRECTION

Built for Lyme.
Exploring broader relevance.

WholeContext AI, developed from the earlier LymeSignal work, was a Phase 1 winner in the 2026 HHS TOPx Tech Sprint. The project examines how connected context could support people navigating complex illness.

The wider research question is how the same principles—longitudinal evidence, provenance, human review, and care coordination—can apply across healthcare. Broader applicability remains a research ambition.

Visit WholeContext AI ↗

Competition recognition does not imply government endorsement or clinical validation.

Where does the demonstration data come from?

Public demonstrations use synthetic patient stories alongside public and open datasets. Synthetic records illustrate workflows; they are not evidence of clinical effectiveness. Any future use of real patient information would require appropriate permissions and safeguards.

Does WholeContext diagnose illness?

No. The research platform organizes information and supports exploration, preparation, and human review. Medical decisions require qualified clinical judgment.

What makes context different from another summary?

Context includes how observations relate over time, who supplied them, the source behind a statement, and what is uncertain or missing. Preserving those distinctions helps a reviewer understand the evidence rather than only read a condensed narrative.

LET’S BUILD SOMETHING THAT MATTERS

What problem
is worth solving next?

Bring a business challenge, a product idea, or a research question. Let’s explore what better intelligence could make possible.

Start a conversation ↗

Healthcare’s missingintelligence layer.

What gets lostbetween the records?