When I was a hiring manager, here's what actually happened on the ground:
Case 1: My HR department received close to 150 resumes for a single role. They pre-screened and sent me 25. Out of those 25, I selected only 2 to move forward.
That means 148 resumes were wasted effort for everyone involved.
Case 2: I was also working with multiple staffing vendors competing for the same role. The problem? Most of the time, the candidates they submitted weren't even suitable. Different vendors, same bad-fit profiles just more noise to filter through.
I ve been building JobsCrow to solve a problem I kept seeing with recruiters and hiring managers: tons of resumes, very little time, and a lot of manual filtering.
JobsCrow lets you upload or forward resumes, then uses AI to read them, extract key info, and auto build a ranked candidate shortlist based on your role requirements. Instead of scanning every resume, you get an ordered list of the most relevant candidates with a quick overview of their experience, skills, and red flags.
Right now, it works best for tech and knowledge work roles, but I m actively improving the parsing and scoring across more job types. I m especially interested in edge cases that traditional ATS / resume parsers struggle with.
JobsCrow prevents costly candidate mismatches through AI-powered resume parsing and intelligent matching. Connect job seekers with employers efficiently. Find jobs or hire talent today.
