Powered by the Marciano Method
BetaThe Intelligent Assessment Platform
Fairgrade weighs every peer reviewer by demonstrated credibility, so a classroom grades as reliably as an expert — richer feedback for students, defensible results for instructors, at a fraction of the cost of doing it alone.
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Every dot is a reviewer. Its weight is credibility — earned, not granted. The center is the grade they agree on.
The problem
Assessment stopped scaling.
Grading deeply is so expensive — in late nights, in stretched teaching teams, in instructor attention — that courses quietly stopped asking students to think in full sentences.
One pair of eyes
all the feedback most submissions ever get, however hard teaching teams work
~60 hours
of instructor time consumed by grading a single course
A, B, C or D
where rich assignments retreat when feedback can't scale
And now AI can do the homework. The answer isn’t fewer essays — it’s more feedback than any one grader can give.
The insight
The crowd knows more than its average.
Simple averaging of many opinions works surprisingly well — juries, markets, and ask-the-audience have proven that for centuries. But averaging treats every opinion as equal, and throws away the most valuable thing a crowd produces: its structure.
How the votes distribute, who agrees with whom, who has been right before — that structure carries information. Reading it is the difference between the Wisdom of the Crowd and Wisdom in the Crowd. Try it yourself.
Twenty people answered a question with four options. You can see the votes — nothing else.
Computed live from a simple accuracy model. The production Marciano Method goes further: it estimates every voter’s accuracy individually, from their track record — Wisdom in the Crowd.
The method
Two unknowns, solved together.
You can’t know whose opinion to trust until you know the answer — and you can’t know the answer without weighting opinions. The Marciano Method estimates both at once: scores imply credibility, credibility re-weighs scores, and the loop runs until the two agree with each other.
Dashed line — the grade the instructor gave working alone · scale 55–95
A simplified model of the Marciano Method, running live in your browser. Credibility is earned by agreement with the emerging consensus — and re-earned every time you interfere.
The platform
From assignment to analytics in four steps.
1Build
Create your assignment and design a rubric — criteria, weights, exemplars.
2Assign
Smart peer assignment distributes reviews fairly and balances workloads.
3Grade
Students give and receive structured reviews on every submission.
4Analyze
Compare peer consensus with scoring insights, finalize, and publish.
AI-assisted scoring is optional — a calibrated second opinion surfaced beside peer consensus, for the instructor to review. It is never the source of trust.
The evidence
A decade of proof, not a pitch.
5,000+
students in pilots
60+
courses at NYU Stern
~60 hrs
saved per instructor, per course
10 years
of research behind the method
$100K
Rennert Prize, NYU's Entrepreneurs Challenge
“The rubric was SUPER helpful, as well as grading other people’s work. I honestly wish other classes let us do this — sometimes we submit our answers and don’t get any feedback at all, which isn’t exactly useful for learning.”
“I think Fairgrade is pretty cool — and the underlying technology obviously has applications outside of the grading functionality. It was an interesting addition to the coursework in lieu of homework.”
Piloted at NYU Stern. Source: NYU Stern, June 2020 →
The inventors
Invented by the professors who lived the problem.
Sonia and Anthony Marciano are professors and economists who, between them, have taught at NYU Stern, Wharton, Chicago Booth, and Harvard. The Marciano Method grew out of a decade of research — refined in their own classrooms, with their own students.
Dr. Sonia Marciano
Co-founder · Co-inventor of the Marciano Method
Professor & economist
Dr. Anthony Marciano
Co-founder · Co-inventor of the Marciano Method
Professor & economist
Yash Goel
Co-founder · President & CTO
Formerly Walmart US · founder, Flicksys
Beyond grading
Grading is the first proof.
The engine under Fairgrade doesn’t know it’s grading essays. It knows how to estimate the truth from many observers of uneven reliability — a problem that appears wherever forecasts, reviews, expert panels, or open questions meet a crowd. We’re proving it one classroom at a time.
For instructors
Get your grading nights back.
Set up your first assignment in minutes. Free for your first course — no credit card required.
For institutions
Reallocate budgets to what matters.
Structured pilots, FERPA-ready architecture, and evidence from 5,000+ students. Let’s design one for your department.
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