What we built: An internal experiment with broader industry potential

CandyDates is an internal POC designed to improve candidate screening within recruiting workflows.

While originally created for the Santex recruiting team, the approach can easily be applied to other organizations using applicant tracking systems (ATS) that face similar challenges when reviewing large volumes of candidates.

The challenge: When finding the right candidate becomes a manual task

Today, recruiters spend a significant amount of time manually reviewing candidate profiles in Greenhouse.

This process involves analyzing:

• CVs

• Interview scorecards

• Notes and feedback from the hiring process

Beyond being time-consuming, this approach can also be:

• Subjective

• Repetitive

• Error-prone

• Inefficient when identifying top candidates quickly

As a result, the process of identifying the most qualified talent often becomes slower than necessary.

The solution: AI-powered candidate prioritization

CandyDates proposes an AI-driven recruiting assistant.

Starting from a Job Description, the system automatically analyzes all candidate profiles associated with the position and evaluates their relevance.

The AI processes data from:

• CVs

• Interview scorecards

• Recruiter notes

Based on this information, the system generates a prioritized ranking of candidates along with a match score, allowing recruiters to immediately focus on the most promising profiles.

The result is a faster, more objective, and more efficient candidate screening process.