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Maple Worker

AI-driven healthcare shift scheduling app

Company
Maple
Role
Product Design Lead
Timeline
Six weeks, 2025
  • Brand
  • Research
  • UX architecture
  • Interface design
  • Prototyping

The project

Clipboard Health partnered with Maple to explore AI-driven healthcare staffing. I led the design of Maple Worker, a shift scheduling platform for healthcare professionals, taken from concept to prototype as part of an experimental suite alongside Maple Care and Maple Scribe.

The problem

Healthcare facilities face persistent staffing shortages and scheduling inefficiencies. I analyzed the workflows of the nurses, CNAs and caregivers who fill their shifts, and four pain points stood out. The app’s onboarding answers each one in a slide.

  1. 01See how it was solvedFinding shifts that match their credentials takes too long.Onboarding: Powered by Maple AI
    Onboarding slide: Powered by Maple AI, AI-driven recommendations to find shifts that match your experience and availability
  2. 02See how it was solvedSchedules conflict, and shifts are hard to keep track of.Onboarding: Manage your shifts
    Onboarding slide: Manage your shifts, explore available shifts and book the ones that fit your schedule
  3. 03See how it was solvedPay is opaque: it is hard to see what they earn.Onboarding: Get paid with ease
    Onboarding slide: Get paid with ease, manage your earnings, split payroll into multiple accounts and set financial goals
  4. 04See how it was solvedGood work goes unrecognized.Onboarding: Track your progress & earn rewards
    Onboarding slide: Track your progress and earn rewards, with attendance tracking and shift statistics

How I solved it

One place to run their working life: intelligent shift matching plus the tools to manage schedules, recognition and pay. The recordings come from the interactive prototype of the worker app; its people, facilities and amounts are sample data.

01

Shifts matched to your credentials

I set out to match qualified professionals with shifts through AI, weighing credentials, performance and preferences. In the prototype, every shift names the credential it calls for, and Maple AI suggests the ones that fit.

Find shifts opens on the week, each date marked for day, evening or night shifts. Every card shows the credential it calls for (RN), the unit, the facility, the distance and the pay per hour.

02

Booking and tracking shifts in real time

I designed the flows for workers to find and manage shifts, and explored the facility side, where shifts are posted and tracked. Booking is instant, and a shift is tracked live from clock-in, with full visibility into each facility.

Date and hours, the credential and unit, a note from the facility, the agency, and the pay: per hour, in total, with Instant Pay.

03

Earnings in plain sight

I explored financial features to make pay visible. The prototype carries an earnings goal and Instant Pay; tax management and payouts to several accounts stayed in exploration.

The account opens on the financial goal: $6,500, 43% reached, $1,936 earned and $4,564 still missing, which the app turns into 92 hours of work.

04

Recognition for the work

To drive engagement through recognition, I introduced gamification: achievement badges, XP points and leaderboards.

The account adds it up: 512 XP, the latest achievements and a 4.3 rating from 27 reviews.

The system behind it

I defined naming and positioning within the Maple suite for brand cohesion, and created a purple identity that belongs to the Maple ecosystem. Under it sits a design system for dense data: iconography, shift color coding and a clear information hierarchy.
Maple Worker splash screen: the mark, the name Maple worker and the line Your daily shift companion over a photo of nurses
The splash: Maple worker, your daily shift companion

Palette

  • Lilac#A2A6FAAI suggestions, countdowns and XP
  • Plum#2A013CPrimary actions, the selected day and the ongoing shift

Shift marks

  • Day7:00am – 3:00pm
  • Evening3:00pm – 11:00pm
  • Night11:00pm – 7:00am
  • RewardsXP and badges

Outcomes & learnings

Changes at the startup kept the app from launching, but the project delivered:

  • A complete interactive prototype of the worker app, validated through stakeholder and user feedback.
  • Insights into how healthcare workers value pay transparency and recognition.
  • A design system ready to scale across the Maple suite.

What I learned

Money is easier to plan in hours: the goal shows what is still missing as hours of work.

Recognition means more when it can be lost: cancelling a booked shift costs XP, and the app says why.

Plans change, so a booked shift needs a way out that still covers the facility: hand it to a coworker.

Research and prototype testing pointed to less time to fill shifts and better worker retention. The app never launched, so none of it was measured.

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