India-Specific · Competitive Exams & Coaching
Test series AI analyticsBuilt for coaching admins.
The challenge
Admins currently struggle with high manual overhead and delayed feedback loops, often identifying a student's conceptual gaps only after they fail a high-stakes mock test.
How AI Professor™ helps
The platform centralizes exam grading and pupil tracking through real-time syllabus heatmaps that pinpoint exactly which NCERT or JEE/NEET sub-topics are causing mass failure. Admins utilize the RAG-enabled Coach Mode to generate remediation plans and automated parent dashboards that justify student progress with granular data.
Why coaching admins pick AI Professor™
Most "test series ai analytics" pitches are a thin wrapper around a generic LLM. AI Professor™ is the opposite: deeply integrated with competitive exams & coaching workflows, with branding, rosters, syllabus, exams and admin controls every decision-maker recognises.
What's in the box
A branded portal, an AI Teacher persona for every subject, 24×7 doubt-clearance, auto-graded worksheets and exams, handwriting evaluation, parent dashboards in regional languages, and a real admin console — usage, safety incidents, faculty workload.
Pricing & deployment
₹37 per student per month. A 14-day pilot covers branding, syllabus loading, teacher onboarding and parent communication. Full rollout typically takes 4–6 weeks.
Compliance & safety
Aligned with NEP 2020, CBSE, ICSE and Indian State Boards. Indian data residency. Mandatory K-12 safety filter.
Frequently asked questions
How does the AI handle regional board variations in test patterns?
The platform utilizes syllabus-aligned RAG technology to ingest specific state board textbooks and previous year question papers. This ensures that the analytics engine recognizes the specific marking schemes and weightage distributions unique to regional patterns like WBJEE or MHT-CET.
Can the system generate parent-facing reports automatically after a mock test?
Yes, the platform triggers automated parent dashboards immediately after the exam grading is complete. These reports move beyond simple scores, providing visual progress trackers and comparative percentile analysis to manage parental expectations and improve institutional transparency.
What is the difference between standard OMR reporting and AI analytics?
While OMR reporting only provides correct/incorrect data, AI analytics performs topic-level tagging and longitudinal tracking. It identifies if a student consistently fails 'Rotational Mechanics' due to a foundational gap in 'Vector Algebra,' rather than just recording a low score.
How does Coach Mode assist faculty during the post-test review session?
Coach Mode identifies the top three 'killer questions' missed by over 70% of the cohort. It provides teachers with alternative pedagogical explanations and related practice problems to address mass misconceptions instantly, rather than wasting class time on questions everyone got right.