AI-Powered Claims Processing System
Deploys 8 specialized AI agents orchestrated through a LangChain-based workflow engine with circuit breaker patterns. Processes claims in under 2 minutes with 94.
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
AI Agents
Specialized autonomous agents working in coordination
Orchestrator Agent
Coordinating multiple AI agents across a complex claims processing workflow requires managing dependencies, handling failures gracefully, and synthesizing outputs from parallel executions while maintaining SLA compliance.
Core Logic
Implements DAG-based execution graph with circuit breaker patterns (Hystrix) and back-pressure handling. Uses Claude 3 Sonnet for workflow coordination with 200K token context window. Manages agent communication through message passing, triggers state transitions, and routes priority claims. Provides automatic escalation after 15-minute SLA breach.
Document Processor
Medical claims arrive with diverse document formats including physician statements, diagnostic imaging, lab results, and treatment plans that require accurate data extraction for downstream analysis.
Core Logic
Applies GPT-4 Vision for multi-modal document analysis with 128K context window. Performs OCR text extraction achieving 97% confidence, document type classification using CNN patterns, and completeness validation against CMS requirements. Extracts 28+ structured fields per claim with bounding box coordinates for audit trails.
Medical Analyst
Validating medical necessity requires expertise in ICD-10-CM codes, treatment-diagnosis consistency, and clinical guidelines that vary by condition category including musculoskeletal, cardiovascular, and mental health claims.
Core Logic
Leverages Claude 3 Opus with specialized medical knowledge for ICD-10 lookup and validation, treatment plan analysis using decision tree classification with Jaccard similarity scoring, comorbidity interaction analysis, and medical necessity assessment against clinical guidelines. Supports M (musculoskeletal), I (cardiovascular), F (mental health), and S/T (injury) code categories.
Fraud Detector
Insurance fraud costs the industry billions annually through provider fraud rings, temporal manipulation, claim buildup schemes, and document tampering that evade simple rule-based detection.
Core Logic
Implements Isolation Forest anomaly detection with O(t x psi x log psi) complexity using 100 trees and 256 sample size. Calculates z-scores for feature analysis, performs NPI registry verification, analyzes provider claim patterns, and detects temporal anomalies (Friday PM submissions, pre-retirement claims). Achieves 94.3% true positive rate with 0.8% false positive rate.
Risk Assessor
Accurate disability duration prediction is critical for reserve estimation and financial planning, but varies significantly based on diagnosis, patient demographics, job requirements, and treatment protocols.
Core Logic
Executes Multiple Linear Regression model trained on 512,347 historical claims with R-squared of 0.847 and MAE of 1.2 weeks. Applies coefficients for age (+0.08 weeks/year over 40), BMI (+0.12/point over 30), comorbidities (+1.8 weeks each), physical job requirements (+2.4 weeks), and surgery (+4.2 weeks). Generates 95% confidence intervals using t-distribution and Kaplan-Meier survival analysis for return-to-work probability.
Benefit Calculator
Calculating disability benefits requires applying complex actuarial formulas including progressive tax brackets, regulatory caps, elimination periods, coordination of benefits, and Loss Development Factors for accurate reserve estimation.
Core Logic
Implements ERISA-compliant actuarial engine with O(log n) complexity using binary search on 2024 federal tax brackets (10%-37%). Applies plan-specific benefit percentages (STD: 50-70% salary, max $2,500/week; LTD: 50-66.67%, max $15,000/week), calculates Social Security and Medicare deductions, and applies Loss Development Factors (STD: 1.15, LTD: 1.35) for reserve estimation.
Compliance Checker
Disability claims must comply with overlapping federal regulations (FMLA, ADA, USERRA), state-specific requirements (CA CFRA, NY PFL), and ERISA plan document terms while generating required notices within regulatory deadlines.
Core Logic
Uses Claude 3 Haiku with 200K context for rapid compliance verification. Checks FMLA eligibility (12 months tenure, 1,250 hours), validates state-specific leave requirements, generates required notices (eligibility, designation, medical certification requests), and tracks compliance deadlines. Produces audit-ready documentation with regulatory citations.
Decision Synthesizer
Combining outputs from multiple specialized agents into a coherent, explainable final recommendation requires aggregating confidence scores, resolving conflicts, and generating human-readable justifications with supporting evidence.
Core Logic
Employs Claude 3 Opus for decision synthesis with explainability generation. Aggregates 7 agent outputs using weighted voting, calculates final confidence scores with calibration data, generates SHAP values for feature attribution, produces counterfactual explanations, and visualizes decision paths as traversable trees. Determines human review requirements based on confidence thresholds.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
6 technologies
Architecture Diagram
System flow visualization