AI Interviewer is a modern, web-based mock interview platform designed to simulate real interview environments. Built using React + TypeScript, it integrates with Firebase for data storage and Clerk for secure authentication. Deployed on Vercel, this application offers an AI-powered interview experience — complete with intelligent follow-up questions based on user responses.
- Users can start a mock interview session and answer a set of AI-generated questions.
- Interviews are categorized and stored using
interviewId(mockId).
- Unique system that dynamically generates follow-up questions based on the user’s previous answer.
- Follow-ups are contextually relevant and designed to simulate real-time interviewer curiosity.
- Each follow-up is linked to its
parentQuestion, forming a question tree.
- All user answers are saved in Firebase (
userAnswerscollection). - The system can detect if a follow-up was left pending or answered.
- Answers and their statuses are fetched and displayed intelligently.
- Only authenticated users can take mock interviews.
- Secure session management and profile tracking.
- All data including questions, follow-ups, and answers are stored in Firestore.
- Efficient querying for:
- Fetching user answers by question and mock ID
- Getting follow-up questions for a parent question
- Checking pending follow-ups
- Deployed on Vercel, providing fast, scalable delivery.
- User Logs In → Authenticated via Clerk.
- Starts Interview → Interview questions are fetched.
- Answers a Question → Answer is saved in
userAnswers. - AI Evaluates Answer → Generates relevant follow-up questions.
- Follow-Ups Saved → Stored in
FollowUpQuestionscollection with:interviewIdparent_QuestionfollowUps(array or object with{ question, answer, userAnswer })
- User Answers Follow-Ups → These answers are updated back to the same document.
- Final Result → Can be shown with analytics or completion status.