Find a precise cutoff
Search by institute, program, category, pool, year and round.
Projects01 / 02 · Case study
Education · Data explorerJEE Cutoff
JEE Cutoff
Explorer.
Making years of scattered admission tables feel like one calm, honest decision-making tool.
INTERFACE PREVIEWExplore possibilities.
IIT Delhi · Computer Science
OPEN · Gender-neutral · Round 6
Historical contextOpening → closing rank
01 / The problem
Cutoff data was available. Understanding it was not.
JEE aspirants often move between counselling PDFs, college pages and spreadsheets just to answer one question: what could my rank realistically unlock?
The hard part is not displaying a number. It is keeping the counselling system, year, round, category, quota and seat pool attached to that number so two different rank lists are never compared as if they were the same thing.
02 / The approach
One path from counselling system to a useful answer.
The experience starts with the counselling system, then narrows to a college set, program, year, round and rank-list context. Every filter exists to remove ambiguity, not to make the interface look powerful.
Official JoSAA and JAC Delhi records stay distinct from secondary College Pravesh rows. Source notes remain visible beside the results so the tool stays useful without pretending every dataset has the same meaning.
See historical movement
Use opening, closing and year-by-year context instead of one isolated rank.
Keep sources honest
Separate official records, secondary tables and rank-list semantics.
03 / Data architecture
A data model that respects how counselling actually works.
The interface is backed by structured, year-and-round datasets rather than hard-coded cards. The filtering layer keeps institute, program, quota, category and seat-pool values together while the UI formats ranks for people.
selection context
System → College → Program → Category → Round2020–2026Historical coverage
IIT · NIT · JACMultiple counselling systems
Open / closeRank semantics kept visible
04 / What I learned
Good data UX is mostly about refusing to hide complexity.
The biggest lesson was that a polished table cannot rescue an unclear data model. Labels, source boundaries and empty states are part of the product’s credibility.
I also learned to design the decision path before designing the visual surface: first make the user’s question precise, then make the answer feel effortless.
01 / Live projectExplore the current cutoff explorer.
Open jeecutoffs.in