Coordinating a distributed healthcare workforce is complicated. Home health agencies, telehealth providers, and staffing firms all face the same operational challenge: coordinating clinicians across locations, regulatory requirements, and fluctuating patient demand. Even small mismatches between clinician availability and patient needs can lead to long wait times or compliance risks.
With telehealth usage remaining high and home-based care continuing to expand, healthcare in the U.S. is increasingly delivered outside traditional facilities. Today, nearly a third of the roughly $5 trillion spent on healthcare goes toward administrative work. Shearman argues that as care becomes more distributed, that administrative burden will only grow.
Joe Shearman, co-founder and CEO of Planbase, saw an opportunity to apply AI to what he calls healthcare's "coordination layer." He and his co-founder Jack Light started the company to build an AI-native workforce management platform for distributed care teams. The goal was to build a system that automates repetitive coordination work that burdens clinics.
Realizing The Scope Of The Staffing Problem
Before founding Planbase, Shearman spent three years as an engineer at McLaren Automotive, where his frustration with clunky enterprise software pushed him toward building tools himself. He later co-founded elando.ai, a demand-forecasting startup that served hundreds of fast-food locations and thousands of employees.
Shearman says the experience at elando exposed a constraint they had not fully appreciated at first. "When you are deploying algorithms but do not control the underlying software, the data model, the APIs, and the way users interact with it, you hit limits quickly," he says. The models could generate forecasts, but adapting them inside someone else's system proved far harder.
When he and Jack Light turned to healthcare, a more regulated and operationally complex industry, they chose a different approach. They founded Planbase as an AI-native workforce management platform for healthcare, designed from the ground up to control its own data model and use large language models rather than relying solely on traditional machine learning.
Planbase competes with incumbent platforms such as UKG and Workday, as well as healthcare-specific scheduling vendors like QGenda and Shiftboard. Shearman argues that many of those systems are built to generate a schedule and then leave it to operators to manage what happens next.
Software vendors have long marketed AI-powered scheduling, but Shearman argues the approach has been flawed. "Software companies have been selling AI scheduling for 20 years," he says. "Every generation claims you can press a button and produce the perfect schedule." In reality, he says, those systems depend on rigid optimization models that break down once conditions change.
"Scheduling isn't a one-shot math problem," he points out. "Running a healthcare operation is more like an ongoing conversation than a single optimization event."
Shearman believes large language models make that shift possible. They allow operators to surface data, automate routine tasks, make decisions, and call traditional optimization models when needed.
How Planbase Works
After onboarding, Planbase connects to a clinic's medical record system to pull in clinician rosters and scheduling data. The platform then uses AI agents to handle much of the coordination work behind the scenes.
For example, when a doctor calls in sick at 7:15 a.m., the system identifies credentialed clinicians within a 30-mile radius, checks licensing rules, sends automated SMS outreach, and proposes replacements within minutes.
"The platform is organized around specialized agents," Shearman says. "Some focus on scheduling changes, others handle compliance checks, payroll coordination, or data analysis."
Traction And What Comes Next
Planbase joined Y Combinator's Summer 2024 batch ahead of its launch. The company later raised a $2.1 million seed round in 2025 from Y Combinator, LocalGlobe, and a group of angel investors. The company now works with digital health providers such as Thirty Madison and OpenLoop Health, whose platforms collectively reach millions of patients each year. Shearman says the funding will be used to expand the engineering team and continue developing Planbase's workforce orchestration system.
