Vantle is an AI-powered teaching platform that integrates into existing courses to make student understanding visible through weekly assessments where students explain concepts in their own words. It generates concept maps from uploaded syllabi and provides instructors with targeted insights into where comprehension is breaking down, down to individual students. The platform never computes grades, leaving all evaluation decisions to the instructor.
Funding
Funding not disclosed
Founders
Product
Problem
Traditional education measures student work rather than actual understanding, leaving comprehension hidden in the mind and invisible to instructors. With AI tools now capable of producing correct answers without genuine understanding, the gap between work and knowledge has widened, making it harder for educators to identify when students truly grasp concepts or merely reproduce correct outputs.
Solution
Vantle runs inside existing courses and makes understanding visible by adapting coursework into a structured format that reveals student comprehension. Instructors upload their syllabus, and Vantle proposes a week-by-week breakdown and a concept map showing how each topic builds on others, both of which instructors can edit. Throughout the term, students complete short assessments built from course material that require them to work problems independently, explain concepts to an AI that misunderstands, and judge flawed work. Vantle analyzes every student's written responses and provides weekly reports showing where understanding is solid, where it is breaking, and the root cause of breakdowns, tracking whether instructor interventions successfully address gaps.
Target Audience
Primary customers are university and college instructors teaching concept-heavy courses who need deeper insight into student comprehension than traditional assignments and exams provide.
Features
- Syllabus upload with automatic generation of weekly course structures that instructors can modify
- Concept mapping that visualizes prerequisite relationships between topics and identifies where learning chains break
- Multi-part assessments requiring students to solve problems, teach concepts to an intentionally flawed AI, and critique misleading answer
- Weekly class-level analytics showing aggregated understanding, pinpointing which concepts are failing and tracing failures to earlier root causes
- Individual student dashboards showing each learner's written responses alongside their understanding profile
- Instructor review queue for grading with one-click override capability and tracking of instructor agreement rates
- System that never computes grades, preserving full instructor control over assessment outcomes