How AI matching can improve recruitment

A popular role can draw hundreds of applications, and recruiters spend much of their time on first-pass screening. AI matching helps right there: it ranks candidates by how well they fit the role, so the most promising ones come first.

What does matching actually do?

The matcher compares the role's requirements (experience, skills, location, work mode, salary range) with candidate profiles. It doesn't just count keywords: it understands that "szoftverfejlesztő" and "developer" mean the same thing, or that accounting experience is relevant to a finance assistant role.

The result is a match score with a short, readable explanation — for example "5 years of React", "based in Budapest", "salary expectation within range".

People decide, not the machine

Good matching supports decisions; it doesn't make them. Every application stays visible — the score only changes the order. Crucially, the system must not consider factors like gender, age or ethnicity, and these are kept out of matching entirely.

When is it coming to Melo?

We're building AI matching now, and it will be available to employers soon. Candidates benefit too: we'll recommend the best-fitting jobs based on their profile. Meanwhile, Melo's search already understands Hungarian and English job titles, inflected word forms and searches typed without accents.