Bring your own questions or have us generate them — either way, every answer key is independently verified and every question is deep-tagged, so you know exactly where each student stands. Pick your path, size your bank, and see a real per-question estimate.
Both paths end in the same place: a bank where every answer key is independently verified and every question is deep-tagged down to the micro-skill. The only difference is where the questions start.
Already sitting on a bank — say 150,000 questions exported from Testpress or any other platform? Hand over the raw export as it is. We deep-tag every question down to the exact micro-skill, so your existing bank becomes fully diagnostic — at a fraction of building one from scratch, since there's nothing to author.
No bank yet, or need fresh coverage? We author questions for every chapter and topic in the syllabus, pitched exactly at NEET / JEE-Mains difficulty — real exam level, never JEE-Advanced overkill or textbook-trivial. Each one is independently verified and deep-tagged from the start.
Harder questions cost more — a multi-step JEE-Mains Maths or Physics problem takes far more work to solve, verify and tag than a straight recall item, so pricing is per difficulty tier. Choose your path, set the counts for your bank, and the total updates live.
We author, verify and deep-tag every question at NEET / JEE-Mains level. Priced per difficulty — harder questions take more work to produce.
Estimates are indicative and assume a mostly-text bank. Question sets that are heavy in figures, graphs or long comprehension passages run higher, since each figure has to be read and understood before it can be tagged. Volume arrangements for banks above 50,000 questions are available — talk to us for a formal quote.
A 30-tag-per-chapter scheme is a solid start — it can flag which chapters a student is weak in. But a chapter is a big place. The value of deep tagging is that it keeps going: past the chapter, past the topic, down to the exact micro-skill and the specific misconception behind a wrong answer — and it keeps that picture current as the student changes.
Thirty tags name the chapter. Deep tagging maps the whole syllabus to thousands of micro-skills — and reads every answer on many signals (timing, confidence, the exact misconception behind the choice), not just right-or-wrong. That's the difference between knowing which chapter and knowing which sub-skill.
"Aarav is weak in Human Physiology."
True, but it covers a hundred sub-skills. A teacher still has to re-teach the whole chapter and hope the real gap is in there somewhere.
Aarav knows his hormones. He only trips when a question asks him to link a feedback loop across two organs — and each time, his wrong answer reverses the feedback direction. He's slow and unsure on just those. The fix is one sharp concept, not a whole chapter.
Same student, same test. The 30-tag view sends a class of forty into a full-chapter revision. The deep view hands each of the forty a two-minute fix aimed at their own exact gap — and updates the moment they improve. That is the difference between grading a bank of questions and understanding a student.
Because the companion reads the same fine-grained picture, it doesn't start from zero every time. It skips what the student already knows and teaches the one thing in the way — in the student's own words, at the exact moment they need it. Here's the same wrong answer, handled three ways.
The difference isn't a smarter answer — it's a smarter starting point. A generic assistant answers the question. The companion answers the student: it knows their history, targets the exact gap, teaches only that, and marks the skill as improving once they get it — so the next nudge is already aimed somewhere new.
To tag a question deeply and guarantee its answer key, the work has to actually solve it. A multi-step JEE-Mains Maths or Physics problem demands minutes of careful reasoning; a biology recall item is nearly instant. That gap — often 4× or more — is exactly why the estimator prices per tier rather than one flat rate.
The area of the region bounded by the curves y = x² and y = x is:
The sum of the binomial coefficients in the expansion of (1 + x)¹⁰ is:
A solid sphere rolls without slipping down a 30° incline. Its acceleration is (g=10):
pH of a 0.01 M weak acid, Kₐ = 1×10⁻⁵:
Projectile at 45°, 20 m/s. Range (g=10):
Highest first ionization enthalpy?
Dihybrid cross RrYy × RrYy — fraction homozygous recessive for both:
"Powerhouse of the cell"?