Home Industry Ecosystems Capabilities About Us Careers Contact Us
System Status
Online: 3K+ Agents Active
Digital Worker 12 AI Agents Active

Enterprise AI Agentic Patient Financial Engagement Platform

Deploys a **Fortune 500-grade multi-agent AI platform** with propensity-to-pay ML models, risk assessment, payment plan optimization, multi-channel communication strategy, SDOH integration, GenAI patient advocacy, real-time eligibility, Good Faith Estimates, and comprehensive explainability including SHAP values and fairness analysis..

12 AI Agents
8 Tech Stack
AI Orchestrated
24/7 Available
Worker ID: patient-financial-engagement-worker

Problem Statement

The challenge addressed

Healthcare providers struggle with significant uncompensated patient care annually due to ineffective patient financial engagement, one-size-fits-all collection strategies, lack of propensity-to-pay insights, and compliance risks with TCPA/FDCPA regu...

Solution Architecture

AI orchestration approach

Deploys a **Fortune 500-grade multi-agent AI platform** with propensity-to-pay ML models, risk assessment, payment plan optimization, multi-channel communication strategy, SDOH integration, GenAI patient advocacy, real-time eligibility, Good Faith Es...
Interface Preview 4 screenshots

Agent Input Console - Patient demographics and financial information entry with feature engineering pipeline visualization

Agent Execution DAG - Real-time multi-agent workflow visualization showing 12 specialized agents with execution status and distributed tracing

Agent Thinking & Reasoning Stream - Live visibility into agent decision-making with observations, reasoning chains, and planning steps

Results & Success Dashboard - Final patient financial engagement outcome with propensity scoring, risk assessment, and recommended strategy

Multi-Agent Orchestration

AI Agents

Specialized autonomous agents working in coordination

12 Agents
Parallel Execution
AI Agent

Propensity-to-Pay Scoring Agent

Treating all patients with the same collection approach wastes resources on unlikely-to-pay accounts and alienates patients who would pay with appropriate engagement.

Core Logic

Calculates patient propensity-to-pay scores using ML models with feature contributions from income, employment, payment history, and engagement metrics. Provides SHAP value explanations, confidence intervals, and counterfactual suggestions for score improvement.

ACTIVE #1
View Agent
AI Agent

Financial Risk Assessment Agent

Default risk varies significantly by patient, and understanding risk factors enables proactive mitigation strategies.

Core Logic

Evaluates default probability with risk factor identification, calculates expected loss, identifies protective factors, and generates risk mitigation strategies with cost-benefit analysis and priority ranking.

ACTIVE #2
View Agent
AI Agent

Payment Plan Optimization Agent

Standard payment plans don't account for individual patient financial situations, leading to defaults and poor completion rates.

Core Logic

Optimizes payment plans using constraint-based algorithms considering patient affordability, NPV maximization, and completion probability. Generates multiple plan alternatives with trade-off analysis and auto-pay incentives.

ACTIVE #3
View Agent
AI Agent

Multi-Channel Communication Agent

Patients respond differently to various communication channels and timing, and generic outreach has low engagement rates.

Core Logic

Analyzes historical engagement data to determine optimal communication channel (email, SMS, phone, portal, mail), best contact timing, and personalized message templates with expected open/response/conversion rates by channel.

ACTIVE #4
View Agent
AI Agent

SDOH Assessment Agent

Social determinants of health significantly impact patient ability to pay, but this information is rarely integrated into financial engagement strategies.

Core Logic

Assesses five SDOH domains (economic stability, education access, healthcare access, neighborhood environment, social/community context), identifies applicable ICD-10 Z-codes, matches patients with community resources, and adjusts engagement strategies based on social factors.

ACTIVE #5
View Agent
AI Agent

Prior Authorization AI Agent

Prior authorization delays and denials impact patient financial responsibility and create billing uncertainty.

Core Logic

Evaluates clinical justification and medical necessity scores, identifies required documentation and gaps, provides payer-specific approval probability estimates, generates recommended actions, and develops appeal strategies when needed.

ACTIVE #6
View Agent
AI Agent

Good Faith Estimate Agent

The No Surprises Act requires accurate price estimates for uninsured and self-pay patients, with compliance penalties for non-compliance.

Core Logic

Generates itemized Good Faith Estimates with provider and facility charges, validates compliance requirements, calculates patient responsibility, tracks estimate validity periods, and manages dispute rights documentation.

ACTIVE #7
View Agent
AI Agent

GenAI Patient Advocacy Agent

Patient communications about financial obligations often lack empathy, clarity, and actionable guidance, damaging patient relationships.

Core Logic

Generates personalized patient communications using GenAI with adjustable tone profiles (empathetic, professional, casual, urgent), reading level adjustment, multi-channel content adaptation, financial options explanations, and patient rights information.

ACTIVE #8
View Agent
AI Agent

Real-Time Eligibility Verification Agent

Inaccurate or outdated eligibility information leads to incorrect patient responsibility calculations and billing disputes.

Core Logic

Performs real-time eligibility verification with detailed benefit summaries, deductible tracking, out-of-pocket accumulator status, service-specific coverage details, and data freshness indicators.

ACTIVE #9
View Agent
AI Agent

Explainability & Fairness Agent

AI-driven financial decisions require transparency for compliance, audit requirements, and patient trust.

Core Logic

Provides multi-level explanations (executive summary for CXOs, technical details for engineers, business context for BAs), SHAP value visualizations, decision tree breakdowns, model cards, demographic parity analysis, equalized odds metrics, disparate impact calculations, and calibration by group.

ACTIVE #10
View Agent
AI Agent

Guardrails & Compliance Agent

Patient financial engagement must comply with HIPAA, TCPA, FCRA, FDCPA, and ECOA regulations with proper contact rate limits.

Core Logic

Enforces compliance guardrails for all regulations, performs content moderation, detects and masks PII, manages contact rate limits by channel, verifies consent status, and generates comprehensive audit trails with PHI access logging.

ACTIVE #11
View Agent
AI Agent

Strategy Synthesis Agent

Multiple agent outputs must be synthesized into a coherent, actionable engagement strategy with clear next steps.

Core Logic

Synthesizes outputs from all agents into unified strategy recommendations (self-service, assisted, high-touch, hardship, collections), generates prioritized action plans, provides expected outcome projections including collection probability, time to resolution, patient satisfaction, and net recovery.

ACTIVE #12
View Agent
Technical Details

Worker Overview

Technical specifications, architecture, and interface preview

System Overview

Technical documentation

The Patient Financial Engagement Digital Worker is an enterprise AI agentic platform designed for Fortune 500 healthcare organizations. It provides a comprehensive patient financial engagement solution with 10 specialized interface tabs targeting different audiences (CXO, Technical, Business Analysts). The platform features advanced agentic capabilities including real-time agent thinking/reasoning chains, inter-agent communication, tool invocations tracking, and memory retrieval systems. Healthcare AI modules include Prior Authorization AI, SDOH (Social Determinants of Health) assessment with Z-code identification, Good Faith Estimate generation for No Surprises Act compliance, and GenAI-powered patient advocacy communications. The system provides full explainability through SHAP value analysis, counterfactual explanations, demographic fairness metrics, and HIPAA/TCPA/FDCPA compliance guardrails.

Tech Stack

8 technologies

Multi-tab audience-targeted interface (CXO, Technical, Business)

DAG-based agent orchestration with real-time reasoning chain visualization

Propensity-to-pay ML models with SHAP explainability and fairness analysis

SDOH assessment engine with community resource matching and Z-code identification

GenAI patient communication generation with tone profiling and reading level adjustment

Good Faith Estimate generation compliant with No Surprises Act requirements

Model registry with drift detection, A/B testing, and performance monitoring

HIPAA/TCPA/FDCPA compliance guardrails with rate limiting and consent verification

Architecture Diagram

System flow visualization

Enterprise AI Agentic Patient Financial Engagement Platform Architecture
100%
Rendering diagram...
Scroll to zoom โ€ข Drag to pan