Getting a diagnosis is too hard
Making the process faster and more reliable changes everything
Getting medical care is hard. No one wants this: every party in the system, from patients to doctors to hospitals to insurers would be better off with faster paths to diagnosis and treatment.
But existing systems were built for a simpler age. They strain under the complexity of new conditions and emerging treatments. So the time is now to reimagine how patients access this care.
What if every patient arrived at a doctor's visit fully prepared to discuss their conditions?
What if every patient could leave those visits fully-resourced to understand and prepare for their next steps?
Technology now exists to bridge the gap between patients and medical systems. We have a working method already producing results for real patients. We need investors and industry partners to help us take it to the next level.
Having a productive doctor's visit is hard
How a patient experiences their symptoms can vary dramatically from how those symptoms are described in the literature. More than that, patients who are new to a condition may struggle to map their experiences into a narrative that doctors can interpret.
Doctor's visits are fast. Preparation can make the difference between a targeted next move and a shot in the dark.
Patients can leave critical junctures unsure about what comes next
Technical jargon can be overwhelming, and time is at a premium in care settings. Understanding new information, lab results, and the patient's role in their own care is a serious challenge and successful understanding bears completely on long term results.
LLM tools gather information quickly yet have infinite patience
An LLM-based tool can rapidly gather the latest information on a medical condition, its research, and the care needed to treat it. It can integrate that information with patient-reported symptoms and history to arrive at plausible next steps for an investigation or diagnosis.
At the same time, it can explain that information at whatever level of detail a patient requires.
This arms patients with the right questions to ask doctors and specialists, making each visit more likely to produce real progress.
The scientific landscape is exploding and good tools can accelerate literature discovery for doctors and patients
An unconstrained language model is dangerous in this context
Using a model to review medical literature is powerful, but it also requires the ability to audit what was read. General purpose LLM tools are not optimized for this high-stakes work.
A carefully designed process for guiding and constraining the model behavior is key. Emerging strategies in agent and context engineering provide the path to a clear chain of evidence and auditable reasoning.
Even with these advances, the key is to accelerate understanding by patients and doctors, not to replace their judgments and insight.
The frontier is now in the agent, not the model
[No tight coupling]