An AI-First deployment transforms the revenue cycle from a human-bound bottleneck into an infinitely scalable asset. The system autonomously audits claims, identifies coding...
Schedule Technology ReviewThe Problem
Average hospital systems experience claim denial rates upwards of 12%, directly resulting from human data-entry errors, coding inaccuracies, and evolving payer rules that massive human billing departments cannot keep pace with.
Our Approach
An AI-First deployment transforms the revenue cycle from a human-bound bottleneck into an infinitely scalable asset. The system autonomously audits claims, identifies coding errors, and scrubs data against payer rule logic prior to submission.
Reduced overall claim denial rates by 54% while completely eliminating manual pre-claim audits, recovering an average of $3.2M annually per hospital campus.
Hybrid Architecture
Aria's hybrid approach combines locally-hosted models for sensitive data with targeted cloud API calls only where necessary — maximizing performance while eliminating unnecessary data exposure.
Runs entirely on your local infrastructure
Processes incoming data securely
Integrates with your existing systems
Orchestrates the complete pipeline
Implementation Architecture
Every Aria deployment follows a structured, transparent implementation process.
Mapping historical human claim review logic
Building the AI surrogate system trained on payer rubrics
AI intercepts and corrects all claims pre-submission
Security & Compliance
All PHI is sandboxed under highly rigid local configurations, guaranteeing complete HIPAA compliance. No patient identifier ever hits a public LLM cloud.
Engagement Timeline
Minimal disruption. Maximum confidence before full production handoff.
Weeks 1-2: Payer Logic Extraction
Weeks 3-4: Local Model Fine-tuning
Weeks 5+: Epic Systems Integration & Go-Live
Next Step
Schedule a complimentary technology stack review with an Aria solutions architect. No commitment — just an honest assessment of fit.
Schedule Technology Review → Free 30-min consultation · No obligation