The story

Built to help every student
get a fair chance

Interview Intel started with a simple observation — job searching is already hard enough, and the tools students use to manage it haven't kept up.


Students are managing hundreds of applications

After talking to students going through job searches, the same story kept coming up. Hundreds of applications sent. Long waits. Company ghostings. Rejections with no feedback. And through all of it — tracking everything in a Google Doc, a spreadsheet, or just trying to remember which company was which.

Interview emails pile up fast. The one with the interview time gets buried. The one asking you to confirm gets forgotten. The deadline to respond passes. And the opportunity is gone — not because the student wasn't good enough, but because the process was overwhelming.

That felt like a solvable problem. So I built Interview Intel.


Three things I will never compromise on

Every student who works hard deserves a real chance

Talent is everywhere. Opportunity isn't. I built this to make it less likely that an interview or deadline gets lost in a crowded inbox. — not because they weren't capable enough.

Technology should reduce stress, not add to it

Job searching is already one of the most stressful things a person can go through. Every feature in this app exists to take something off your plate — not to add another thing to manage.

Programmers have a responsibility to help people

I can build things that genuinely make life easier for people who need it. That’s not just an opportunity — it’s a responsibility I take seriously.


Built with real problems in mind, down to every detail

The features in Interview Intel are built around problems students actually run into during a job search. The urgency classifier exists because people miss deadlines. The prep guidance exists because people don't know what to study. The task generator exists because people forget to follow up.

Every part of this app is designed for students by a student.


The person behind the project

Ilker Baran

Ilker Baran

Backend engineer · Python, Flask, Celery, ML/LLM

I built Interview Intel around a real engineering problem: processing job-search emails reliably in the background, combining a machine-learning classifier with LLM-based extraction and guidance, and moving that work from threads to a Celery task queue.

I documented the architectural decisions as the project evolved, including the parts that did not work as well as expected. It is a personal project that I use in my own job search and continue improving as I learn more about backend systems and applied AI.