Capability · Workflow Automation & Revenue Cycle Modernization
AI-enabled RCM, predictive staffing, and touchless workflow architecture for hospitals and health systems.
Eyebrow: Capability · Workflow Automation & Revenue Cycle Modernization
H1: Half of U.S. hospitals will run generative AI by end of 2025. Architecture decides which half saves money.
Sub: 31.5% of hospitals reported EHR-integrated generative AI in use and another 24.7% plan adoption within a year, per JAMA Network Open analysis. McKinsey projects a 30–60% cost-to-collect reduction for touchless RCM. Deloitte reports 85% of surveyed U.S. healthcare technology executives plan to increase agentic AI investment over the next two-to-three years. The technology is not the constraint. The architecture that decides where AI is applied, and where it should not be, is the constraint.
Primary CTA: Request a workflow-automation diagnostic → /engage/rfp
Our founder's public record includes predictive staffing models delivering 92% accuracy across multi-hospital operations. Staffing is the highest-cost, highest-variance function in a hospital. It is also the function where predictive architecture pays back fastest.
Roughly 46% of hospitals and health systems already use AI in revenue-cycle operations, per an AKASA/HFMA pulse survey. The question is not whether. The question is which functions, eligibility, coding, denial prediction, propensity-to-pay, earn ROI at your organization's data maturity.
CMS-0057-F requires impacted payers to return prior-authorization decisions within 72 hours (expedited) and 7 calendar days (standard) with API compliance beginning January 1, 2027. Underneath the API standard sits an operational reality, provider directory freshness, clinical documentation exchange, and prior-authorization workflow, that must be redesigned end to end.
Hospitals lose an estimated 3–5% of net revenue annually to revenue leakage. tens of billions across the U.S. system. AI is a leverage tool, not a standalone fix. The organizations that convert AI adoption into recovered revenue are the organizations that redesigned their architecture *first*.
Half of surveyed healthcare leaders say their organizations have already implemented gen AI, and the conversation has shifted from "whether" to responsible ROI.
A four-week read of the organization's data maturity, workflow standardization, and process architecture, the prerequisites AI actually depends on. If the diagnostic reveals the organization is not AI-ready, we redesign the architecture before deploying automation.
Prioritized 90-day plan mapping where automation, where AI, and where human judgment. Explicit ROI targets and measurement cadence.
Continuous coaching of RCM leadership, clinical documentation improvement teams, and IT delivery, the layer that determines whether the automation stack becomes architecture or becomes another layer of technical debt.
Quarterly rhythm of automation-portfolio review, model-drift audit, and workflow-pattern optimization. Automation without ongoing optimization decays.
The AI question is architecture, not technology.
Primary CTA (gold): Request a workflow-automation diagnostic → /engage/rfp
Every engagement begins with a four-week diagnostic sized to your team's bandwidth.
Request a diagnostic