The story behind Applyless

Applyless didn’t begin as a company. As an international student, I watched talented students spend hours searching for jobs, tailoring resumes, and sending applications — without ever knowing whether they were making good decisions. Most job applications were based on hope rather than evidence.

The more I spoke to students, the more I realized the problem wasn’t a lack of ambition. It was a lack of clarity. Most people don’t know which opportunities are worth pursuing, what employers are actually looking for, or whether they’re improving their chances with every application. Universities face a similar challenge: they invest heavily in career support but have limited visibility into what happens between graduation and employment.

I started building Applyless during my final year studying Software Engineering at the University of Technology Sydney. The first version was simple: an AI system that scored opportunities against a student’s profile and recommended whether to apply, review, or skip.

Then I launched it. I thought it would just start working. It didn’t — zero signups, and the feedback was blunt: the product felt unpolished and the value wasn’t clear. My first instinct was that the problem was distribution, that I just didn’t know how to get it in front of people. That was true, but it wasn’t the real problem. The deeper issue was the model itself. A consumer job tool works against its own economics: the better it works, the faster the student gets hired and leaves. You pay to acquire someone who, by design, won’t stay.

Talking to students, careers teams, university leaders, and founders across Australia and India made the alternative clear. The real challenge wasn’t helping one student apply for more jobs. It was helping institutions support thousands of students with personalized career guidance while understanding what actually drives graduate outcomes.

Applyless evolved from a student job-application assistant into an AI employability platform for universities. Today we’re building infrastructure that helps institutions deliver personalized career guidance and give placement teams better visibility into student outcomes — while helping students spend less time guessing.

We’re still early. We’ve launched things that didn’t work, pivoted, and rewritten large parts of the platform. My goal isn’t to build another AI product. It’s to give every student a clearer path from education to employment.