Recruiters and colleges struggle to screen large numbers of candidates fairly and efficiently. Traditional hiring methods are slow, biased, and do not properly evaluate real skills. ScreenerPro was built to solve this problem using AI by automating candidate screening, mock interviews, proctoring, and performance analysis in one platform.

What it does

ScreenerPro is an AI-powered hiring and interview platform that helps recruiters and institutes assess candidates through:

AI mock interviews with camera and microphone enabled

Real-time proctoring (tab switching, full-screen enforcement, cheating detection)

Resume-based dynamic questioning

Skill, confidence, and behavior scoring

Public job board and hiring campaigns

Mentor and SIG modules for colleges

Verification links for interview reports

The platform provides detailed insights into candidate performance and significantly reduces manual screening effort.

How we built it

We built ScreenerPro using Flutter Web for a responsive UI on both desktop and mobile. The backend uses Firebase Authentication and Cloud Firestore to securely manage users, interviews, reports, and job data. We integrated AI APIs such as Gemini and OpenAI for question generation, answer evaluation, confidence scoring, and smart interview flows. Proctoring is implemented using browser APIs and Flutter Web listeners to detect tab switching, focus loss, and full-screen exit.

Challenges we faced

Implementing secure proctoring on Flutter Web

Designing real-time AI interview flows that feel natural

Structuring Firestore data for scalable hiring campaigns

Handling Google Sign-In and Firebase authentication issues

Managing performance while using video, audio, and AI processing together

What we learned

Designing secure online assessment systems

Real-world integration of Firebase and REST APIs

Using AI in real production features

Working around Flutter Web limitations

Building a scalable SaaS architecture

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