ACA Compliance Guardian
Deploys a coordinated swarm of 10 autonomous AI agents that analyze employee data against current ACA regulations, predict compliance risks using ML models, simulate optimization scenarios, generate IRS forms (1095-C, 1094-C), and create actionable remediation plans. Agents operate with configurable autonomy levels and make real-time decisions while maintaining full audit trails.
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
Multi-agent compliance analysis dashboard showing 10 AI agents working in parallel with real-time status indicators, agent activity log with benchmark analyst and scenario planner actions, live API calls monitoring, and workflow phase progression from initialization through final report generation
ACA Compliance Report summary displaying Fair Compliance grade (84% score), key metrics including 64% coverage rate, 94% affordability, $36,160 penalty exposure, executive summary with recommendations, analysis quality scores, and data pipeline validation status
Compliance findings detail view showing specific violations with AI agent reasoning traces, including affordability threshold exceedances and full-time employees without coverage offers, with confidence scores and actionable remediation recommendations for each finding
What-If Scenario Analysis interface presenting four AI-generated optimization strategies with compliance impact projections, penalty reduction estimates, implementation costs, and ROI analysis including recommended hybrid optimization approach for maximum cost-benefit ratio
AI Agents
Specialized autonomous agents working in coordination
Orchestrator Agent
Coordinating 10 specialized agents across 9 workflow phases requires intelligent task routing, priority management, and decision escalation to ensure efficient, complete analysis.
Core Logic
Serves as the master coordinator using GPT-4 Turbo for task planning and agent assignment. Operates with full autonomy for workflow routing and priority adjustments. Monitors all agent activities, aggregates results, and escalates decisions requiring human review based on confidence thresholds.
Data Analyst Agent
Employee datasets contain inconsistencies, missing values, outliers, and format variations that can cause compliance analysis errors if not properly validated and normalized.
Core Logic
Performs comprehensive data validation including schema checking, anomaly detection, and pattern recognition. Uses statistical analysis to identify outliers in hours data, flags data quality issues, and autonomously handles outlier treatment decisions. Calculates employee classification statistics and data quality scores.
Compliance Expert Agent
ACA regulations are complex, frequently updated, and require expert interpretation. Applying rules like look-back measurement periods, safe harbor calculations, and penalty assessments requires specialized knowledge.
Core Logic
Leverages GPT-4 with RAG (Retrieval Augmented Generation) over IRS publications and regulations. Interprets 2025 ACA requirements including the 9.02% affordability threshold, applies look-back measurement method rules, calculates potential penalties under 4980H(a) and 4980H(b), and classifies compliance findings by severity.
Risk Predictor Agent
Reactive compliance only catches violations after they occur. Organizations need predictive capabilities to identify employees likely to cross the full-time threshold before it happens.
Core Logic
Runs Monte Carlo simulations with 10,000+ iterations to model hours variability and predict threshold crossing probabilities. Uses custom ML models to analyze hours trends, calculate risk scores for variable-hour employees, and estimate days until potential threshold crossing. Generates proactive alerts for high-risk employees.
Form Generator Agent
IRS Forms 1095-C and 1094-C require precise code mapping, complex conditional logic, and strict XML schema compliance. Manual form preparation is slow and error-prone.
Core Logic
Automates IRS form generation using rule-based code mapping for Lines 14, 15, and 16. Validates all forms against IRS AIR system XML schemas, generates employee 1095-C forms and the 1094-C transmittal, and flags validation errors. Operates without autonomous decision authority due to regulatory precision requirements.
Explainer Agent
Compliance findings and technical ACA terminology are difficult for non-specialists to understand. Executives need plain-language summaries and actionable recommendations.
Core Logic
Uses Claude 3.5 Sonnet with higher temperature for natural language generation. Translates technical compliance data into stakeholder-friendly executive summaries, writes clear recommendations, generates communication content for different audiences, and produces the final comprehensive report with key metrics and next steps.
Regulatory Monitor Agent
ACA thresholds, penalty amounts, and filing deadlines change annually. Organizations need real-time awareness of regulatory updates to maintain compliance.
Core Logic
Simulates connection to IRS regulatory sources to fetch latest ACA guidance, threshold updates, and deadline changes. Autonomously detects regulatory changes, alerts the compliance expert agent, and updates internal reference data. Tracks key dates including Form 1095-C distribution and IRS electronic filing deadlines.
Remediation Agent Agent
Identifying compliance violations is only half the battle. Organizations need actionable, prioritized remediation steps with clear ownership, deadlines, and cost-benefit analysis.
Core Logic
Analyzes compliance findings to generate prioritized remediation roadmaps based on risk severity and ROI. Creates specific action items with assigned owners, deadlines, automation flags, and estimated savings. Builds phased implementation timelines and autonomously identifies which remediation steps can be automated.
Benchmark Analyst Agent
Organizations lack visibility into how their compliance posture compares to industry peers, making it difficult to justify investments or identify improvement opportunities.
Core Logic
Compares organizational metrics against industry benchmark data including average compliance scores, coverage rates, and penalty exposure. Calculates percentile rankings, identifies performance gaps versus top quartile performers, and autonomously classifies benchmark results and recommends improvement initiatives.
Scenario Planner Agent
Organizations need to evaluate different compliance improvement strategies before implementation to understand cost-benefit tradeoffs and choose optimal approaches.
Core Logic
Runs what-if analysis simulations modeling scenarios like extending coverage to all full-time employees, reducing hours for at-risk workers, or adjusting premium contributions. Uses Monte Carlo simulation to project compliance score improvements, penalty reductions, and implementation costs. Autonomously generates optimization recommendations with ROI analysis.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
4 technologies
Architecture Diagram
System flow visualization