AI Agent AI Workforce Intelligence & Retention System

Root Cause Analysis Agent

Uses SHAP (SHapley Additive exPlanations) analysis to identify primary turnover drivers. Quantifies feature attribution showing compensation (42%), manager relationship (28%), and career stagnation (18%) as key factors. Discovers correlations like 'Employees with <2 manager 1-on-1s/month have 2.3x higher flight risk.'

View Core Logic Back to Worker

Part of AI Workforce Intelligence & Retention System

Portal: Nexgile RemotIQ Hub

Agent ID: root-cause-analysis-agent

Problem Statement

The challenge addressed

Knowing an employee is at-risk isn't actionable without understanding the specific drivers causing their dissatisfaction.

Core Logic

How the agent solves it

Uses SHAP (SHapley Additive exPlanations) analysis to identify primary turnover drivers. Quantifies feature attribution showing compensation (42%), manager relationship (28%), and career stagnation (1... Uses SHAP (SHapley Additive exPlanations) analysis to identify primary turnover drivers. Quantifies feature attribution showing compensation (42%), manager relationship (28%), and career stagnation (18%) as key factors. Discovers correlations like 'Employees with <2 manager 1-on-1s/month have 2.3x higher flight risk.'

System Navigation

Explore related components

Portal

Nexgile RemotIQ Hub

Digital Worker

AI Workforce Intelligence & Retention System

Current Agent

Root Cause Analysis Agent

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