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Home Artificial Intelligence

Cubby Launches First AI Teaching Assistant for Law School Students

August 19, 2025
in Artificial Intelligence, GlobeNewswire, Web3
Reading Time: 5 mins read
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NEW YORK, Aug. 19, 2025 (GLOBE NEWSWIRE) — Cubby Law, the first AI teaching assistant for law school students, is launching nationwide Aug. 25. Powered by a proprietary AI model trained on thousands of real law school exams and case briefs written by a top Georgetown Law School graduate, the platform creates a personalized study plan and unlimited practice exams tailored to a student’s specific classes and professors at 225 American law schools.

Cubby Law’s launch comes amid a 20% surge in law school applications this year – the steepest rise in decades – creating unprecedented competition for incoming students. At the same time, AI is reshaping how students learn and prepare for professional life, creating new demand for tools that combine personalization, accuracy, and academic integrity.

“Law school is extremely competitive. A student’s future can hinge on a single final exam worth 100% of the grade,” said Cubby Founder and CEO Truman Sacks. “Cubby understands both the student and their professor’s priorities. With just a few uploaded documents, we can replicate a professor’s style and create a tailored plan that helps students master the material before high-stakes finals.”

In a spring 2025 pilot, more than 1,300 students applied for early access. Users reported average GPA gains of 0.25 to 0.55 points after studying with Cubby.

Cubby Law features a calendar built from each student’s syllabus, an interactive library of case briefs annotated with professor-specific insights, outlines that track progress, and an unlimited exam simulator with instant grading that mimics each professor’s style. Students can ask Cubby questions and receive feedback that cites relevant source material, ensuring reliability and identifying specific areas where students need additional practice.

​​“In my first semester, I knew the material but struggled to organize it under pressure. Cubby Law helped me figure out how to approach an exam from top to bottom and go in with confidence,” said Liam Willis, a JD candidate at the SMU Dedman School of Law. “I tried taking practice exams with generic AI tools, but they basically told me how great I was without pointing out my mistakes. Cubby critiqued my answers and showed me how to fix them. Cubby helped lift my GPA significantly the second semester.”

Cubby Law is backed by $2.75 million in seed funding from Eighty-Seven Capital’s Sam Hinkie, Ludlow Ventures’ Jonathon Triest, Discord co-founder Eros Resmini’s The Mini Fund, and Positive Sum’s Patrick O’Shaughnessy. Founder and CEO Truman Sacks, 24, is a two-time founder who sold his last company, Scout, to StockX in 2021.

Building on the success of its spring pilot, Cubby is delivering a significantly expanded platform for the fall semester, laying the groundwork for a new standard in how future legal professionals prepare to succeed in law school and beyond.

“Cubby is designed to enhance learning without undermining academic integrity – like better running shoes for a marathon,” Sacks said. “The platform operates in a secure, closed environment that prevents AI hallucinations and keeps student-uploaded materials private. It is trained on highly vetted content ensuring that every answer is accurate and grounded in real law and course materials.”

For more information or to sign up for Cubby Law’s waitlist, visit cubby.law.

About Cubby Law

Cubby Law is the first AI teaching assistant designed for law school students. From the first reading to the final exam, the platform delivers personalized study tools tailored to each student’s courses and professors. Powered by a proprietary AI model trained on real law school exams, Cubby provides structured practice, candid feedback, and clear guidance to help students achieve their academic goals.

A video accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/727ebf57-f94a-4a82-b6c3-87d90e4b4f2d

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