Prep.AI

Inspiration

In today’s competitive job market, it's alarming to see MBA graduates from top schools struggling to secure employment, while many immigrants find themselves overlooked despite their qualifications. For these candidates, landing a job can often hinge on a single interview—the make-or-break opportunity that can determine their future.

Breaking into Product Management can feel like a formidable challenge without the right guidance. The role demands a deep, holistic understanding of business, collaboration across cross-functional teams, and a strong obsession on delivering an exceptional customer experience. There’s no one-size-fits-all formula to measure a candidate’s potential as a product manager, making the path even more intimidating for those without prior experience. Inspired by this gap, we’re driven to provide a solution—one where candidates can upload their resume and the job description of their desired role, and in return, receive a tailored interview experience that helps them effectively prepare, sharpen their skills, and build confidence for their actual interview.

What it does

Our product allows customers of all backgrounds to interview for PM roles and receive feedback on their interview. We also perform an analysis on the interview transcripts and give feedback on the interview on a scale of 1 to 10.

How we built it

We used Reflex for both the front-end and back-end web development, enabling us to build a fully functional web application entirely in Python without needing to handle separate frameworks or languages for the front-end.
We built a Full stack app that uses vapi ai to record and transcribe interviews.
We further exploit the capabilities of vapi to generate questions and follow ups to ask the user using gpt 4.0 model
We also use the gpt4.0 model and prompt engineer the vapi app to analyse the transcribed interviews and rate the users feedback based on our defined rubric.

Challenges we ran into

Zeroing in on a voice agent was very difficult as there were a lot of options and each model had their own pros and cons.
Prompt engineering to get the right feedback from the voice agent was hard to perform.

Accomplishments that we're proud of

We were able to build an AI voice agent that can conduct product manager interviews, capable of providing target company based interviews.
Gained exposure to voice agents and explored the prompt generation to enhance the accuracy of the ai model.

What we learned

We learnt about the extensive capabilities of vapi and voice agents in general.
We learnt how to use AI agents to take interviews and give feedback to customers.
Learnt the python reflex framework and used it develop the FE & BE.

What's next for Prep.AI

We plan on analysing the performance of the candidate in the interview and assigning a schedule that he/she can follow to improve his interview score.
Introduce a progress tracker that updates iteratively based on the mock interviews taken by the candidates.
Use Prompt engineering to further refine the evaluation rubric iteratively to generate more accurate and authentic reports.
Take in the resume and job description of the candidate into the knowledge base creating context for each user that interacts with the AI voice agent, and tailor interview experiences.