Abstract:
This paper introduces JobIt, the third and final component of the ECES labor market analysis system, designed to bridge this gap. JobIt is a proprietary conversational AI system that transforms the project’s comprehensive labor market dataset into a dynamic, interactive resource. Built on an agentic Retrieval-Augmented Generation (RAG) framework, JobIt combines the reasoning of Large Language Models (LLMs) with specialized, high-fidelity tools, crucially, an SQL Agent that grounds all quantitative analysis in an ECES-verified dataset, ensuring accuracy and mitigating model hallucination. The system’s dualmode architecture enables users to generate complex, interactive visualizations and conduct deep, conversational inquiries using natural language. By translating user intent into executable code and structured queries, JobIt democratizes data exploration, empowering policymakers, researchers, and analysts to unlock nuanced insights from complex datasets without requiring specialized programming skills.
