AI Scheduling Platform

Nurse scheduling is complex, with constantly shifting variables. In assistive care facilities, inefficient scheduling can lead to hundreds of thousands of dollars in wasted costs each year. Our AI-driven solution addresses this by supporting users at every level—surfacing key issues, optimizing decision-making, and automating repetitive tasks.

The Problem

When we first started the product, the company was focused on getting the product in the hands of users. This took the form of free pilots for all but one company. The sales demos went over really well and business leaders loved the power of AI to increase efficiency and drive down costs. The problem came with user adoption. The scheduler was often not tech savvy and needed much more control invisibility to adopt AI into the workflow. I advocated for us to meet the users on their comfort level and nudging user to AI incrementally.

An image of a simple AI suggestion model.

Orienting & Solving Issues

Compliance is critical in running a successful facility. The system proactively identifies issues that require attention and uses a genetic algorithm to score and rank the best scheduling solutions based on factors such as nurse type, time worked within the pay period, cost, performance, and seniority.

We learned that users often needed to visualize recommendations before accepting them. To support this, AI-generated scheduling suggestions are integrated directly into the schedule view, allowing users to see how proposed changes fit in real time.

Optimizing for Better Decisions

Previously, many users filled schedules manually, often without the necessary context. Our platform now provides data-rich, optimal recommendations at the point of decision. Whether assigning a single nurse or sharing a shift to multiple staff, the system ranks the most suitable candidates based on the specific scenario. Users can also distribute open shifts in tiers—similar to a marketing campaign—giving preferred staff more time to accept offers.

We optimized the onboarding of new staff schedules by identifying patterns in existing timesheets. This streamlined the many micro-decisions involved in creating nurse schedules, saving time and improving efficiency.

Off-loading and Monitoring Tasks

To reduce manual effort, the platform automates common scheduling tasks and provides a centralized dashboard to help users stay in control. As a result, facilities have saved tens of thousands of dollars per month while reducing scheduler burnout and improving overall scheduling efficiency.

Automated tasks with quick action responses help to remedy problems more quickly, and with less effort.