Inspiration
What inspired me to build Appli.io was being in the job grind. I was looking for new graduate jobs which was causing me to send out on average 10 applications per day. Since I was sending out so much, it became even harder to track, to the point if I got a response back it was like "I applied to this?" So, one day it came to me. What if there was a way for me to go back and track all my job applications without having to manually do it. That's how I gained the inspiration for Appli.io.
What it does
Appli.io is a simple Google Chrome extension, that once you sign in on Gmail, goes through your emails and scrapes any info pertaining to job applications and places them on your dashboard, users are able to filter from 1 month up to a year of applications which is the point of no return. The dashboard acts like an excel sheet and each role and email has a job status associated with it depending on the contents of the email. As well as the bot can also detected when you're filling out an application in the background. This doesn't stop there. Appli.io also has a resume diagnostic which grades each bullet point on your resume and gives back suggested bullet points to make it better. As well as for companies you get an interview for you get an interview prep bot. Also, it comes with a deep scan of each company you applied to, so you get the information quick and easy, understand hiring trends and what is going on at the company.
How we built it
Appli.io is built using React for the frontend and leverages Gemini 3 and the Groq API for AI-driven analysis. Emails are parsed and processed, then sent to the Groq API to classify application status and extract structured data. The system is designed to efficiently handle large inboxes while maintaining accurate, real-time updates in the user dashboard.
Challenges we ran into
One major challenge was reliably parsing unstructured email data and producing consistent AI classifications across different companies and email formats. Additionally, API rate limits restricted large-scale testing, as analyzing thousands of emails required careful optimization to minimize unnecessary calls while preserving accuracy.
Accomplishments that we're proud of
Making the platform fully functional and ready to hit the market.
What we learned
This project reinforced the importance of thoughtful feature selection, user-centric design, and building scalable AI systems under real-world constraints.
What's next for Appli.io
What's next for Appli.io is launching on the Google Chrome store and being able to scale all the features that is integrated with AI so we can handle more users.
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