Predict realistic college admissions using entrance ranks, board scores, and historical cutoff intelligence.
Without proper admission intelligence, students face critical challenges:
Admission cutoffs vary yearly with no clear patterns. Students don't know realistic chances.
Data spread across multiple sources. Hard to cross-reference ranks, marks, and seat allocations.
Students either over-apply (dreams) or under-apply (safe). No data-driven middle ground.
Counselors lack real-time data. Recommendations are intuition-based, not data-backed.
Our AI system analyzes multiple dimensions to power realistic predictions:
Benchmarks your rank against historical cutoff patterns across thousands of students.
Combines board marks with entrance rank for comprehensive candidate profiling.
Analyzes 5+ years of cutoff data to identify trends and predict future patterns.
Factors in total seats, category cutoffs, and state-wise allocations.
ML model trained on 50K+ admission outcomes. Achieves 85%+ accuracy.
Get ranked college suggestions with admission probability for each option.
Your profile details
Entrance & board scores
Historical analysis
ML processing
College matches
Students Analyzed
Colleges Indexed
Courses Mapped
Entrance Exams
Centralized repository of college cutoffs, seats, courses, and historical admission data
Engine analyzing trends, patterns, and year-on-year cutoff variations
ML model trained on 50K+ admission outcomes with 85%+ accuracy
Generates ranked college suggestions with probability scores
Conversational assistant explaining predictions and recommendations
Intuitive UI for entering profile and viewing personalized predictions