Student Risk Early Warning System Submission Summary
Student Risk Early Warning System is an AI-powered analytics platform that helps educational institutions identify, understand, and support at-risk students before they drop out.
Every year, thousands of students leave education not because they lack ability, but because warning signs like absenteeism, stress, disengagement, and financial hardship go unnoticed. Our solution uses AI-driven risk scoring and Tableau Next visual analytics to detect these signals early and convert them into actionable insights for educators.
The system continuously analyzes academic, behavioral, emotional, and socio-economic indicators to calculate a dropout risk score for every student. These results are visualized in Tableau Next dashboards, which clearly show:
Who is at risk
Why they are at risk
How urgent intervention is
By combining AI intelligence with interactive visual analytics, StudentRisk enables schools to move from reactive reporting to proactive student success management.
The platform is built on a modern, scalable architecture:
Data Layer: Student data from Google Sheets and Salesforce Data Cloud
AI Layer: Risk scoring models generate probability of dropout and key risk drivers
Analytics Layer: Tableau Next provides real-time dashboards and trend analysis
Action Layer: Salesforce Agentforce AI delivers intelligent recommendations and decision support
This allows advisors, counselors, and administrators to take the right action at the right time — whether it’s academic support, counseling, financial aid, or engagement outreach.
Student Risk Early Warning System transforms raw student data into clear, explainable, and life-changing insights, helping institutions retain more students and improve long-term outcomes.
Built by Suresh Kumar Thulasi Ram
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