* Disclaimer: This project is a generalized concept based on real-world scenarios. All proprietary data and branding have been removed or adapted.
This project shifted high-volume agent enablement from passive training to a model rooted in measurable performance outcomes and adaptive learner experience (LX).
The core design implements adaptive pathing, directly addressing the gap between experienced hires being bored and novices feeling overwhelmed. The solution's success is defined by holistic, performance-based KPIs (Empathy Index, Time-to-Resolution), ensuring training measures real-world job competence, not just knowledge recall.
The custom React framework ensures zero-latency interactions and scalability, while the conceptual SCORM 1.2 wrapper enables seamless reporting across an enterprise LMS. This blend highlights the capability to manage the full product lifecycle, ensuring learning architecture drives business results.
01. ANALYSIS (THE WHY)
Traditional onboarding fails to build strategic communication skills or prepare agents for the real-time stress of an angry customer.
02. DESIGN (THE BLUEPRINT)
I developed a user-centric "AI-OS" concept where the learner practices skills within an immersive, high-tech workstation environment.
03. DEVELOPMENT (THE BUILD)
Custom React Application built to manage complex branching logic and provide zero-latency behavioral feedback.
04. IMPLEMENTATION (DELIVERY)
Designed for full WCAG AA accessibility and seamless integration into enterprise learning systems.
05. EVALUATION (METRICS)
Success metrics validate that the simulation is accurately predicting on-the-job performance.