Aeyesafe · B2B · SaaS · Healthcare
Real-Time Alert System for Senior Care
Senior Care SaaS Platform
Aeyesafe · December 2023
Users: Nurses, Care Homes Administrators
Signals: In-room motion sensors → real-time alerts.
This platform helps scientists explore massive, complex datasets and reveal patterns they couldn’t see before.
As the founding designer, I shaped the product from its earliest sketches to its release-ready interface. I defined the UX strategy, guided all design decisions, and built the foundation for a scalable system that supports real scientific breakthroughs.
My role: Product Designer
What I owned: Problem framing, research, interaction model, alert logic UX, visual system, edge cases, and launch readiness.
PROBLEM TO SOLVE
Caregivers in senior care facilities receive a constant stream of alerts while working under severe time pressure. When alerts aren’t clearly prioritized or owned, critical issues can get lost in the noise, increasing safety risk for residents.
How might we design a real-time alert system that doesn’t just surface events,
but actively coordinates caregivers around who needs to act, how urgently, and what happens next—
under real operational constraints.
WHAT I THOUGHT WOULD WORK
I started by designing a centralized alert page to give caregivers full visibility into everything happening across the facility.
The assumption was: if all alerts were visible in one place, response quality would improve.
This was a fast, low-risk way to validate whether visibility alone could reduce missed incidents.
Reality Check: Talking to Caregivers
To validate the alert-page approach, I conducted interviews with two nurses and one care home administrator.
The goal wasn’t feature feedback — it was understanding how alerts fit into real caregiving workflows.
This immediately challenged my core assumption.
““When I’m helping a resident, I don’t have time to keep checking an alerts page.””
The issue wasn’t alert visibility — it was coordination under time pressure.
Caregivers didn’t struggle to find alerts; they struggled to know when to stop what they were doing and act.
Alerts were being treated as information, not as time-bound tasks.
That reframed the problem entirely.
Design Shift: Interruption, Not Monitoring
Critical alerts couldn’t wait to be checked — they needed to interrupt caregivers in real time.
This meant shifting from passive monitoring to active interruption.
The alert system had to surface urgency without requiring navigation or context switching.
That’s when pop-up alerts became essential.
System Expansion: Monitoring AI Failures
Because alerts were driven by non-variable AI devices, failures were inevitable.
Administrators needed visibility into false positives, missed alerts, and response patterns.
This wasn’t about analytics — it was about trust and continuous system improvement.
Reporting became part of the alert system, not an add-on.