Pathway

Pathway’s EchoNext reads a routine ECG and surfaces patients who are likely to have structural heart disease. It requires no expensive tests and no new hardware. As an FDA-cleared AI software as a medical device (SaMD), every change must be planned, documented, and verified.

Pathway approached me at a critical juncture: transitioning from a research project incubated within a health system to a commercial product. Their data scientists needed support with product strategy and operations through their public launch.

As a small team, Pathway needed just enough structure to work together without adding unnecessary process. I implemented and facilitated a lightweight product development lifecycle (PDLC)—from strategy to shipping—along with a Notion workspace to support day-to-day work.

FDA clearance requires documenting much more rigorously than a typical startup. Notion workflows, combined with AI agents, ensured their quality management system (QMS) self-documents simply by moving through the product lifecycle.

The transformation equally required a shift in culture: new rhythms, roles, and rituals to keep the team aligned, motivated, and shipping quality production work.

A process only works if a team adopts it. I facilitated the lifecycle with the team through product launch, coaching team members 1-on-1 and adjusting as we learned, so the systems fit the way they actually work.

By the end of the engagement, EchoNext successfully rolled out commercially to health systems and announced a partnership with OpenEvidence, an AI tool used by 65% of US doctors.