Soham Mehta

3,500 resumes. One role. No way to read them all. That is the moment I decided to build something. My sister was hiring for a single position. 3,500 applications landed in her inbox. She knew exactly what she was looking for, but manually screening 3,500 resumes takes months. Months she did not have. Months the best candidates were not going to wait around for. And I kept thinking - how many...

Custom ranking parameters are the right approach. The moment you let the hiring team define what actually matters for the role instead of relying on generic keyword filters, the quality of the shortlist changes completely. Scaling that beyond 50 resumes is where it gets really interesting.

The screening piece is where the real value is. We looked at data across 100,000+ resumes - 80% of applicants didn't meet even half the basic requirements. The biggest win for any recruiting team isn't finding more candidates, it's spending less time on the ones who were never going to make it.

The shift from manual screening to AI-native evaluation is long overdue. The real question is whether the screening is just keyword matching dressed up as AI, or actual contextual evaluation of every candidate. That's the difference between filtering out great people and actually finding them.

Love the AI approach to recruiting. The industry is overdue for this shift - we've screened over 100,000 resumes and found that 80% of applicants don't even meet half the basic requirements. The more tools that help recruiters focus on the right candidates instead of drowning in volume, the better for everyone.