A System Built for the 1980s
The locum tenens staffing industry is a $5 billion market operating on infrastructure built decades ago. Spreadsheets track physician availability. Phone calls initiate matches. Credentialing packets are faxed. The technology gap between healthcare staffing and virtually every other professional services industry is stark — and costly.
Facilities pay 25–40% markup fees to agencies who add friction rather than intelligence. Physicians spend hours chasing paperwork they've submitted dozens of times. And patients wait longer because the physician who could cover a shift never heard about the opening in time.
This isn't a resource problem. It's an information problem — and AI was built for exactly this.
What AI Actually Does in Staffing
"AI in healthcare" has become a buzzword attached to everything from scheduling software to clinical decision support. When we talk about AI in staffing, we're specific about what we mean.
Intelligent matching — AI systems analyze physician profiles against open shifts across hundreds of dimensions: board certifications, geographic preferences, facility type, patient acuity mix, historical scheduling patterns, and credentialing completeness. What used to take a human coordinator 2–3 hours takes seconds.
Predictive demand modeling — Historical volume data, seasonal trends, local events, and population growth indicators can forecast when facilities will need additional coverage before gaps become emergencies. Proactive fills are cheaper and faster than reactive ones.
Automated credentialing workflows — Document tracking, expiration alerts, and state license monitoring can be fully automated. The physician submits once; the system handles the rest across every facility they work with.
Transparent pricing — When matching is driven by data rather than relationship networks, market rates become visible. Facilities can understand what drives pricing; physicians can see what drives their placement.
The Physician Side of the Equation
The conversation about AI in staffing often centers on facilities. But the supply side — the physicians — is equally important, and equally underserved.
A locum physician managing their own assignments across multiple facilities juggles:
- Multiple credentialing applications with overlapping paperwork
- Shift negotiations conducted across text, email, and phone
- Payment terms that vary by facility and arrive unpredictably
- No visibility into what facilities are paying comparable providers
AI platforms can consolidate this into a single experience: one credential set that travels across facilities, a unified inbox for shift opportunities, automated scheduling tools, and consistent payment infrastructure.
The physicians who adopt these platforms aren't just more efficient — they're more available. When administrative friction drops, providers can cover more shifts and earn more with less effort.
What We're Building at Rediworks
Rediworks started with a simple observation: urgent care is the primary care system's front line, and it's chronically understaffed because the tools are bad.
Our matching engine accounts for the specific demands of urgent care — high volume, broad acuity range, EMR familiarity, procedural capability, and patient experience. Urgent care isn't the ER and it isn't primary care; it requires physicians who understand the pace and scope.
We integrate credentialing verification into the matching process so that by the time a physician and facility are introduced, the compliance work is done. No surprises, no delays.
We launch in Colorado first — a deliberate choice. Colorado's urgent care market is competitive and growing, and the provider-to-population ratio is among the most strained in the region. If we can prove the model here, we can prove it anywhere.
The Road Ahead
Healthcare staffing will look fundamentally different in five years. The platforms that win won't be the ones with the largest rosters — they'll be the ones with the best matching intelligence, the most seamless credentialing infrastructure, and the deepest trust from both facilities and physicians.
The incumbents in this space are large, well-capitalized, and slow. The opportunity for AI-native platforms is real and it's now.
If you're a facility operator or a physician who's frustrated with how staffing has worked so far — join us and help build something better.