AI-Powered Retirement Plan Participation Intelligence System

Core Logic

The Orchestrator Agent serves as the master planner for the entire enrollment optimization workflow. Built on Claude claude-sonnet-4-20250514 (Anthropic) with temperature 0.3 for deterministic planning, it decomposes high-level goals into discrete tasks, routes work to specialized agents based on capabilities, monitors execution across all phases, and manages inter-agent dependencies. The agent employs two primary tools: Task Planner for goal decomposition and timeline creation, and Agent Router for capability-based work assignment. It implements sophisticated error recovery with retry logic and graceful degradation, maintains execution state across the 8-phase workflow, and provides real-time progress updates. Cost tracking shows $0.003 per input token and $0.015 per output token for full transparency. The agent's outputs include execution plans, progress reports, and coordination messages. Core capabilities include task decomposition and planning, agent routing based on capabilities, progress monitoring and reporting, error recovery and retry logic, inter-agent coordination, and budget and timeline management. Model configuration uses Anthropic provider with claude-sonnet-4-20250514 model at temperature 0.3.

Core Logic

The Data Analyst Agent specializes in comprehensive employee data analysis for enrollment optimization. It executes SQL queries against employee databases (1,000+ records, 1200ms latency), runs ML inference for propensity scoring (model accuracy: 91%, 800ms latency), and performs K-Means clustering for behavioral segmentation (k=6, silhouette score: 0.72, 2000ms latency). The agent produces detailed outputs including propensity scores indicating enrollment likelihood, barrier analysis identifying obstacles (complexity, procrastination, mistrust, financial concerns), and clustering results grouping employees by behavioral characteristics. Each tool invocation is logged with latency metrics and cost tracking. The agent implements the ReAct pattern with explicit reasoning chains showing thought processes, observations from data, and analytical conclusions. Core capabilities include SQL query execution for employee data, ML model inference for propensity scoring, K-Means clustering for segmentation, barrier identification and analysis, statistical pattern recognition, and feature contribution analysis. Tools used include SQL Query Engine (1200ms latency) for employee data queries, ML Inference API (800ms latency) for propensity scoring models, and Segmentation Engine (2000ms latency) for behavioral clustering. Output types include propensity scores, barrier analysis, segment profiles, and feature importance rankings.

Core Logic

The Strategy Designer Agent creates behaviorally-informed campaign strategies tailored to each employee segment. Operating with temperature 0.7 for creative strategy generation, it applies behavioral economics principles including loss aversion (framing missed matching as 'leaving money on the table'), social proof (highlighting peer enrollment rates), default options (recommending auto-enrollment), and anchoring (strategic contribution rate suggestions). The agent uses the Campaign Optimizer tool (1500ms latency) to evaluate strategy effectiveness and the A/B Test Simulator (1000ms latency) to predict performance of message variants. Outputs include channel-optimized campaigns (email, SMS, web portal, in-person), personalized messaging templates, optimal timing recommendations, and projected conversion rates by segment. Each strategy includes detailed reasoning chains explaining why specific approaches were selected for each behavioral profile. Core capabilities include behavioral economics application, personalized messaging design, channel optimization, A/B test design, conversion projection, and nudge strategy creation. Behavioral techniques applied include loss aversion framing, social proof messaging, default option recommendations, anchoring strategies, and commitment devices. Model configuration uses temperature 0.7 with creative and persuasive style.

Core Logic

The Compliance Reviewer Agent validates all campaign components against regulatory requirements using a conservative, deterministic approach (temperature 0.0). It executes comprehensive checks using the Compliance Rule Engine for policy validation against ERISA, DOL, IRS, and CCPA requirements, and the Risk Assessment Engine for identifying potential compliance risks and required mitigations. The agent produces detailed compliance reports with status indicators (PASSED, WARNING, FAILED) for each regulatory framework, specific recommendations for addressing any findings, and risk scores with mitigation strategies. All validation decisions are logged to immutable audit trails with cryptographic hashing. The agent enforces guardrails including mandatory review of any content mentioning specific investment returns, automatic flagging of potentially discriminatory language, and verification of required disclosures. Outputs include compliance certificates, risk assessments, and remediation roadmaps. Core capabilities include ERISA fiduciary compliance validation, DOL guideline enforcement, IRS rule verification, CCPA privacy compliance, risk assessment and scoring, and audit trail generation. Compliance frameworks covered include ERISA, DOL, IRS, CCPA, and Internal policies. Model configuration uses temperature 0.0 with conservative and deterministic style. Guardrails include content filter, PII detection, budget limits, action validator, and bias check.