Grade smarter.
Not harder.

AI-powered grading that aligns to your rubrics, anonymizes student work, and delivers consistent results. Visualize distributions, apply curves, and track class performance at a glance.

T
M
S
K
Trusted by 200+ educators in early access
Student Submission Anonymized
Student 24
AI Analysis Verified
87 / 100
Thesis Clarity 23/25
Evidence & Support 20/25
Organization 22/25
Grammar & Style 22/25
"Strong argument structure. Consider adding a counterexample in paragraph 3 to strengthen the thesis."
Bias-free grading
Step 01

Drop it in. We'll handle the rest.

Set up your rubric, dial in how you want grading handled, then upload a folder of student work. FairGrader picks it up from there.

Build or import your rubric

Define categories, point scales, and expectations — or import a rubric you already use.

Set your grading style

Adjust strictness, feedback tone, and grade a few examples so FairGrader learns how you grade.

Upload a folder of submissions

Drop a whole class worth of PDFs or Word docs at once. FairGrader processes them in parallel.

A
Rubric
Thesis & Argument 40 pts
Evidence & Support 25 pts
Organization 20 pts
B
Grading Style
Strictness
Tone Encouraging
Calibration 3 examples graded
C
Upload
Drop folder or files
.pdf .docx
Anonymization Auto
Submitted as Sarah Johnson
Graded as Student #2847
Names are stripped before any AI engine sees the work
Verification Report Consensus Reached
Engine A
87 / 100
Engine B
86 / 100
Engine C
88 / 100
Final Score (weighted avg) 87
Variance: ±1.0 Confidence: High
All 3 engines agree
Step 02

Graded blind. Verified for accuracy.

Student names are stripped before grading begins — bias never enters the equation. Then multiple AI engines grade each submission independently against your rubric. Results are cross-validated so no single model's drift can slip through.

Automatic Anonymization

Student identities are removed before any AI model sees the work. Grades are based on merit alone.

Multi-Engine Consensus

Multiple AI models grade independently. Results are compared and reconciled before you ever see them.

Flagged Disagreements

When models disagree on a score, the submission is flagged for your review — never silently pushed through.

Step 03

Review everything. Change anything.

Every graded submission lands in your dashboard with the original work and AI feedback side by side. Resolve flags, override scores, edit comments, or kick a paper back for regrading. Nothing is final until you say it is.

Side-by-side review

Original submission on one side, annotated feedback on the other. Read exactly what the AI scored and why.

Resolve flags and disagreements

Flagged submissions are highlighted. Review them, override the score, or send them back for another pass.

Export when you're done

Download annotated PDFs for students and a CSV for your gradebook. All in one click.

Submission Review
Flagged Student #2847
Original
Feedback
Thesis 36 / 40
Evidence 20 / 25
Organization 12 / 20
Grammar 13 / 15
You have the final say
15 min 30 papers, graded
Zero install Browser. Log in. Go.
FERPA-ready Encrypted & anonymized
Human support Real people, real answers

Built to be simple.

Clean dashboards. Obvious navigation. Nothing hidden three menus deep. If you've used a spreadsheet, you can use FairGrader.

If it takes more than 5 minutes to learn, we'll fix it.

Stop grading until 2 AM.

Join the waitlist and be first in line when FairGrader opens up. Early access members get lifetime pricing.

No credit card required. Free during early access.

You deserve this.