About Justine
Our platform uses advanced AI to provide fair, consistent, and comprehensive evaluations of hackathon projects based on multiple dimensions.
Our Mission
We built Justine to revolutionize how hackathon projects are evaluated. Our mission is to provide a fair, consistent, and comprehensive judging system that:
- Eliminates human bias from the judging process
- Ensures all projects receive equal attention and thorough evaluation
- Provides detailed feedback to help participants improve
- Scales to handle hackathons of any size
- Creates transparency in the evaluation process
How It Works
Multi-dimensional Analysis
Our AI analyzes projects across five key dimensions: Business Value, Innovation & Uniqueness, Technical Implementation & Quality, Impact & Potential, and Feasibility & Future Vision.
Comprehensive Artifact Analysis
Each submission is evaluated through analysis of multiple artifacts: demo videos, slide presentations, and code repositories, creating a 360° view of the project.
Detailed Feedback Generation
Beyond scores, we provide detailed explanations, identified strengths, areas for improvement, and actionable recommendations for future development.
The AI Judging Process
Video Analysis
- • Speech-to-text conversion of narration
- • Visual content analysis of demos
- • Presentation quality assessment
- • Key topic and concept extraction
- • Delivery effectiveness scoring
Slide Analysis
- • Text extraction from slides
- • Diagram and chart interpretation
- • Presentation structure analysis
- • Problem statement clarity assessment
- • Visual design quality evaluation
Code Analysis
- • Repository structure evaluation
- • Code quality assessment
- • Design pattern recognition
- • Documentation completeness check
- • Technology stack analysis
Our Technology Stack
Backend Infrastructure
Scalable cloud architecture with load balancing to handle concurrent submissions
Media Processing
Advanced computer vision and audio processing for slide and video analysis
Code Analysis
Static code analysis tools and repository structure evaluation engines
Large Language Models
State-of-the-art AI models for natural language understanding and feedback generation