Transforming our hiring process with an in-house GenAI agent

Based on the agentic search approach, we developed an AI agent integrated into our internal system. This AI agent reads and analyzes job descriptions, extracts key requirements, and queries our database. Through a sophisticated ranking heuristic, it evaluates and ranks potential candidates based on role alignment.

The results include a detailed breakdown of each candidate's strengths and weaknesses, offering immediate value to our recruiters by enabling faster, more informed decision-making.

We collaborated with Microsoft’s AI Co-Innovation Labs for an intensive one-week in-person engagement, resulting in a powerful proof-of-concept solution utilizing Azure Open AI, Azure AI Search, and Azure Document Intelligence to implement intelligent search capabilities on our data modeled in Microsoft Fabric.

By leveraging Azure Open AI and other Azure services integrated with Microsoft Fabric, our system now analyzes job descriptions and matches them with ideal candidates from our OneLake curriculum database. This solution efficiently processes thousands of resumes, ranking candidates based on their fit for job criteria and providing insights into their strengths and weaknesses for the intended role.

Through an iterative development process shaped by real-world feedback from our capacity team, we created a solution that addresses our biggest challenges: time-to-hire and match quality. This innovation transformed a previously time-consuming, manual process into a streamlined, AI-driven workflow, significantly enhancing our recruitment efficiency and effectiveness.