Sense

Sense Education develops an AI-driven assessment and feedback platform aimed at higher education institutions. The system takes individual student submissions, applies AI pattern recognition to group them into "solution archetypes," and lets educators give targeted feedback to each group so that every student receives an individualized assessment. A confidence-based grading component evaluates submissions against rubrics and routes instructor attention to the submissions that most need human review, while a tutoring component provides on-demand guidance based on learning patterns and common errors, and a learning analytics component reports on knowledge gaps and instructional efficacy.

The platform is designed for open-ended work with multiple valid approaches but clear success criteria, including computer science coding assignments, business case studies, engineering problems and text-based submissions. Sense positions the product around the argument that universities must shift from testing recall to evaluating reasoning and problem-solving as AI becomes widely available, and that growing class sizes make one-on-one feedback economically unfeasible without automation. The company states it is fully FERPA compliant, applying access controls, encryption and privacy protocols to student data, and that submissions can be passed to Sense with anonymized IDs.

Business model

Sense sells its assessment platform to educators and institutions under multiple pricing structures, including per-submission, per-course and per-learner licenses as well as company-wide, departmental and school-wide enterprise agreements.

Licensing/subscription pricing charged per submission, per course, per learner, or via departmental, school-wide and company-wide enterprise contracts.

Traction

The company reports platform outcomes including a 70% reduction in manual grading, 60% reduction in grading time, 95%+ accuracy, grades released 2.5x faster, a 73% reduction in teaching-assistant requirements, a 50% reduction in student complaints, and a 90%+ success rate for its tutoring system in improving student work. A cited deployment at a tech university clustered 14,000 code submissions across 70 exercises to inform course revisions; additional unattributed testimonials come from a head TA at a large state university and an online adult student.