Inspiration
As students, we often dedicate approximately two hours per day to job applications, which not only consumes valuable productive time but also hinders our opportunities for learning new skills and engaging in recreational activities. In our pursuit of a solution, we explored outsourcing the job application process. However, existing resources proved expensive, with fees ranging from 13% to 30% of the annual salary while offering limited benefits on a contract basis. It became evident that our struggle was not unique, as we discovered that many other students faced the same challenge.
What it does
Our innovation is revolutionizing the job application process by ensuring a response within 24 hours and employing LLM (Language Model) to rank candidates. By connecting the top 3% of applicants with recruiters within 48 hours of application submission, we streamline the recruitment experience. We do this with the help of a customized test which includes text, audio, and video questions.
How we built it
To bypass the conventional job application procedure and save significant time and effort in generating cover letters and awaiting company responses, we have implemented a system where candidates who rank within the top 3% are guaranteed an interview with a recruiter if they maintain their position for an additional 24 hours. Moreover, we pledge to deliver results within 24 hours while providing our service for 3% to 5% of the student's annual payment. On the other hand, Recruiters will be charged a monthly subscription fee, eliminating the need for initial screening rounds and reducing costs.
Challenges we ran into
One of the major hurdles we faced was integrating LLM models within a limited timeframe to achieve our desired outcomes. We intend to leverage Hume AI to analyze audio, video, and sentiment to address this.
Accomplishments that we're proud of
Our notable achievement includes the development of an LLM model that can be queried based on candidate information, providing valuable insights for the recruitment process.
What we learned
Throughout this project, we acquired knowledge on integrating APIs built on top of ChatGPT and gained expertise in training LLM models using personalized datasets,
What's next for SwiftHire
Moving forward, our immediate goals involve finalizing the product and applying to prestigious programs such as Skydeck and other business incubators.
Built With
- css
- html
- javascript
- phyton
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