ExamReportAI is an AI-powered diagnostic platform that converts raw exam scores into actionable, student-specific learning reports — freeing educators from manual grading and empowering every student with a personalised study plan.
India has over 260 million students in secondary and higher-secondary education. The vast majority of them receive only a letter grade after examination — with no insight into which specific topic or question type is responsible for their underperformance. ExamReportAI's AI engine changes this at scale: institutions adopt the platform for free, and students receive a hyper-personalised diagnostic report with a 14-day remedial battle plan for ₹25 — less than the price of a notebook.
M.Sc. Physics graduate with a deep understanding of India's coaching institute ecosystem. Currently working as a PGT Physics teacher in a CBSE-affiliated school, he witnessed firsthand every day how manual grading robbed teachers of time they could spend actually teaching — and how students walked away from exams with no actionable feedback. With a passion for technology and its transformative potential, he built ExamReportAI to democratise AI-driven diagnostics.
Google Cloud's AI-native, global-scale infrastructure was the only platform suited to ExamReportAI's unique demands.
Fully serverless deployment. Zero-config autoscaling from 1 to 10,000 concurrent requests. Cold-start-minimised containers for instant report generation.
LLM-powered diagnostic analysis. Parses marks, detects error patterns, and generates hyper-personalised remedial content at scale using Gemini.
Multi-tenant database with Row Level Security. Each institution's data is enforced at the database level — ensuring ironclad privacy.
Async-first REST API serving all portals — educator, student, admin. Built for high concurrency during peak exam seasons.
Wallet top-ups, micro-transactions, and educator payouts. Seamless integration for frictionless ₹25 report generation.
Student answer sheets are processed in ephemeral compute environments and never persisted to long-term storage.
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