Latchability

Latchability is a medical-device software company building tools that help clinicians assess infant feeding and neurological development. I joined as the lead software engineer, responsible for taking the product from early prototype toward a clinical-grade, connected application.
The Problem
Assessing how an infant feeds is a meaningful early window into neurological health, but the signals clinicians rely on are subtle and hard to capture consistently. Latchability set out to turn those signals into objective, repeatable measurements — giving care teams better data, earlier.
My Role
As lead engineer I owned the software end to end: system architecture, the iOS application, the connected-hardware integration, and the backend that stores and surfaces results for clinicians.
- Architecture & SRS: Defined the system architecture and software requirements to support a regulated development path.
- Mobile application: Built the clinician-facing iOS app, from UI wireframes through a testable TestFlight build.
- Connected hardware: Integrated the measurement device over Bluetooth for reliable, real-time data capture.
- Backend & data: Stood up the server, database, and data pipeline with security and privacy designed in from the start.
Approach
The work was structured around a milestone roadmap — wireless prototype, architecture and wireframes, frontend, connectivity and backend, then hardening, verification, and validation. Building a medical product means designing for reliability, security, and a clear regulatory pathway at every step, not as an afterthought.
Design Challenges
- Signal fidelity: Capturing clean, clinically-meaningful data from a small, low-power connected device.
- Regulated software: Balancing fast iteration with the documentation, verification, and validation a medical device demands.
- Privacy by design: Handling sensitive health data with security and compliance built into the architecture.
Latchability is in active development. Details shown here are high-level; the product and its clinical data are confidential.