Grady | Fully Automated Grading for Higher Education

Overview

Grady offers a fully automated grading process for higher education that is in the process of been rigorously validated in pilot programs across multiple university programs and disciplines. By eliminating traditional manual grading responsibilities, institutions across the U.S. can reallocate billions of dollars (estimated 4B+ dollars annually) worth of faculty and teaching assistant time annually toward research, instruction, and student mentorship.

Unlike partial AI solutions that merely assist human graders, Grady conducts end-to-end grading with no human oversight required under normal operation. At the same time, it retains a systematic failsafe: instructors can override any disputed decision if necessary. This balance—complete automation with rigorous academic control—differentiates Grady positioning it as the authoritative solution for modern universities and colleges.

How It Works

Grady’s Quality Grading Process (QGP) is guided by a multi-step workflow that ensures transparency, accountability, and superhuman grading accuracy demonstrated with statistical confidence 99.9% in the human trials of the prototype system.

1

Assignment Integration

Instructors upload or sync tests and assignments through the institution’s Learning Management System (e.g., Canvas, Blackboard). Grady operates quietly in the background in an end-to-end, fully automated rubric extraction based on proprietary machine learning tools. If desired, rubrics can be configured or adjusted by faculty for maximum alignment with course objectives.

2

Automated Grading

Grady’s research-backed machine learning algorithms independently evaluate each submission against the specified rubric. No human grader intervention is required, removing bias and error while reducing faculty workload to nearly zero.

3

Feedback Delivery

Students receive AI-generated grades and written feedback rapidly, often within hours of submission. This timely, detailed response enhances learning outcomes by providing formative guidance for improvement.

4

Appeals & Oversight

In the event a student disputes a grade, a remark request triggers an automated re-evaluation by a secondary AI model. If questions remain, the case is flagged for instructor review. This structured oversight workflow assures fairness and guards against errors, with instructors retaining final authority.

Features

Each core feature is designed to address the operational and pedagogical needs of universities.

⚙️

Fully Automated Grading

Eliminates manual grading entirely, enabling institutions to save significant budget previously allocated to TA hours.

🔍

Superhuman Accuracy

Validated by extensive trials, ensuring consistent, objective, and impartial assessments across all student work.

📝

Detailed Feedback

Provides rubric-based comments and suggestions that help students understand their performance and improve learning outcomes.

🔒

Secure LMS Integration

Syncs seamlessly with major LMS platforms (Canvas, Blackboard) and ensures compliance with FERPA and institutional data policies.

⚖️

Fairness & Transparency

AI-driven grading eliminates human bias, while the remark request process and instructor overrides guarantee academic integrity.

🌐

Scalability

Designed for large courses and cross-department use, Grady can handle thousands of submissions with negligible latency.

Research & Credibility

Grady is the culmination of years of rigorous academic research and pilot human trials. Our development team comprises university professors with extensive experience in both AI and academic education in a multitude of settings across the globe. Early pilot programs have demonstrated that Grady reduces grading time by 100% for normal workflows, surpasses human graders in consistency, and empowers students with fast feedback that can accelerate mastery of course material.

In controlled trials, Grady achieved superhuman accuracy with excessive statistical confidence, confirmed in side-by-side comparisons with human TAs. Our team has authored whitepapers on these findings, illustrating our "no-human-in-the-loop" approach and the benefits of structured oversight for exceptions. These detailed whitepapers are available upon request, and our research efforts remain ongoing to ensure reliability in diverse course contexts.

Security & Fairness

Academic institutions rightfully demand systems that protect student privacy and ensure equitable treatment. Grady adheres to FERPA and other relevant standards, implementing end-to-end encryption and secure storage of grading data. Each AI decision is recorded in an audit log, enabling administrators to review and confirm that grading practices are consistently applied.

To address fairness, Grady employs standardized rubrics and follows the Quality Grading Process (QGP). Students have the right to challenge any grade through a remark request, which triggers an AI re-check. In the sporadic event where uncertainties remain, instructors serve as final arbiters. This combination of student-driven appeals and faculty oversight mitigates errors, promotes transparency, and aligns with the core academic values of consistency, objectivity, and impartiality.

Differentiation

Grady sets itself apart from AI solutions that continue to depend on human graders for finalizing scores. Every other product currently available still requires human intervention, contradicting the goal of modernizing and streamlining academic programs by eliminating the costly and repetitive burden of grading. In contrast, Grady fully automates the grading process, eliminating the need for human graders in the standard workflow, with manual involvement limited to handling remark appeals or flagged anomalies.

100% Automation vs. Partial Automation: No teaching assistants needed in standard operation.
Academic Validation: Developed by professors, backed by NSF-funded trials, and peer-reviewed for reliability.
Structured Quality Control: Student remark requests, secondary AI checks, and instructor escalations ensure fairness without day-to-day manual grading.

With these capabilities, Grady stands as the only solution that merges comprehensive automation with an instructor-led fail-safe, offering superior accuracy, lower operational costs, and advanced educational benefits.

Frequently Asked Questions (FAQ)

Is Grady truly fully automated?

Yes. Under normal operation, Grady eliminates the need for human graders entirely. However, instructors may review or override grades on an as-needed basis, particularly when a student files a remark request.

How do instructors maintain control over grades?

Instructors can configure and approve rubrics at the outset. If a student disputes a grade, Grady runs a second AI evaluation. Unresolved disputes are elevated to the course instructor, who has full authority to alter any grade as warranted.

What subjects or assignment types does Grady support?

Grady supports a broad range of subjects, from STEM problem sets to humanities essays. Our flexible rubric engine and natural language processing components accommodate diverse assignment formats.

How secure is the grading data?

Grady upholds strict data privacy and security protocols, including end-to-end encryption, FERPA compliance, and robust authentication to protect student records and academic integrity.

What evidence supports Grady’s claims of improved learning outcomes?

Extensive research and development, including rigorous human trials indicate near-instant grading turnaround times, empowering student engagement and mastery. By providing rapid, detailed commentary, Grady enables excellence in learning.

Our Team

Periklis Papakonstantinou

Associate Professor, Rutgers University.
Researcher in AI and cryptography with decades of teaching experience in undergraduate, MSc, and MBA programs globally.
System designer and developer of Grady.
Funded by NSF & NSF-China.

Tasos Sidiropoulos

Associate Professor, University of Illinois at Chicago.
Specialist in algorithms, computational geometry, and AI with international teaching and research experience.
System designer and developer of Grady.
Secured $1M+ in NSF funding.

Our leadership team has conducted research and taught at institutions including MIT, Tsinghua University, University of Toronto, University of Illinois, Rutgers University, Toyota Technological Institute - Chicago, and The Ohio State University. These experiences have shaped our commitment to scholarly rigor and evidence-based design.

Contact Grady

We welcome inquiries from university administrators, department chairs, and program committees looking to adopt AI-based solutions for grading. To learn more or schedule a personalized demonstration, reach us at:

Email: corporate@gradyai.com

Request a Demo General Inquiry