RoboHack2 by MLH

We have been preparing for getting our internships and placements. That journey has been tough and the only real way we could get some interview practice was by getting selected for an interview or asking our seniors. The 2nd option comes with a lot of anxiety. So, we wanted to build a tool that can remove that anxiety from mock interviews and help us get confident and prepared before the actual interview.

Our project provides a platform for students and job seekers to prepare for interviews through live feedback and analysis of their answers. It also provides a feedback report with a selection probability score for your desired role. We also consider the resume score according to the job description for more accurate results. Our aim is to help identify strengths and weaknesses and help the candidate leverage their strengths and minimize their weakness. Candidates after their actual interview can add their interview experience on interview experience forum for getting points.

Our project is mainly built using ReactJs, Node JS and Python

1. Frontend has been prepared using ReactJS and Wix by Velo
2. We have used Wix by Velo to make our interview experience forum and landing page
3. We have used Cohere.ai for the improving the speech to text transcription
4. Cohere.ai has also been used for generating feedback based on the response of the candidate
5. We have used Machine Learning to calculate resume score
6. Feedback report is sent to the candidates email ID using SendGrid API by Twilio

Domain.com has been used to get a custom domain - INTERVIEW-COACH.TECH Here the Coach is represented by AI Interviewer Check it out at link

It was our first time using Cohere.ai. This had a steep curve of learning by was indeed very fun to use. Time was also a major challenge.

We managed to get the project going within the time and we were able to integrate Wix, Cohere and Twilio together. This felt really satisfying.

Learnt to work with new technologies within such a short time and integrating them together

• Having a personalized resources section for candidates to check out after interview for learning
• Having a job opening page with selection probability score based on your resume score and interview score
• Implementing point based system for those who post their interview experience
• Further improving the model feedback