Overview
ReClass AI was built to close the gap between content delivered in the classroom and knowledge retained by students. The platform transforms passive lecture recordings into active, structured digital knowledge assets-searchable, summarised, and interactive.
Objectives
- Transform passive lecture recordings into active, structured digital knowledge assets-searchable, summarised, and interactive.
- Enable students to navigate directly to any concept within a lecture, eliminating time wasted scrubbing through full-length recordings.
- Provide 24/7 AI-powered academic support through a lecture-grounded AI Tutor, reducing dependency on instructor availability outside contact hours.
- Generate institutional data insights-analytics on topic coverage and engagement patterns to inform course improvement decisions.
Challenges
- Unstructured video archives-recordings stored as flat files with no topic segmentation, chapter markers or searchable metadata.
- Passive revision behaviour-students re-watching 60–90 minute lectures to locate a single concept, leading to inefficiency and disengagement.
- No on-demand academic support-questions arising outside office hours go unanswered until the next tutorial, creating learning gaps.
- Zero learning analytics-no visibility into which segments students engaged with, where comprehension was weak, or which topics generated the most queries.
Solutions
The ReClass Engine processes raw lecture recordings through a multi-stage AI pipeline, producing a structured digital knowledge asset with zero manual input from educators:
AI Transcription
Automatic speech-to-text with speaker differentiation and millisecond-level timestamp alignment-no manual effort required.
Topic Segmentation
AI identifies distinct subject sections within each lecture and assigns each a precise timestamp and descriptive label automatically.
Semantic Search
Content is vectorised for concept-level retrieval-students land at the most relevant lecture moment, not just a keyword match.
AI-Generated Summaries
Structured summaries distilling key concepts and insights from each session, available immediately after class ends.
AI Tutor Interface
Conversational Q&A grounded exclusively in the lecture transcript-students receive structured, source-accurate answers 24/7.
Data Insights Dashboard
Analytics on topic coverage density and engagement patterns, giving institutions actionable data for improving course delivery.
Impact
Faster Review-students locate any concept in seconds vs. scrubbing full recordings
Automation-zero manual effort from educators, fully automated end-to-end
Retention-improved knowledge retention through structured, searchable content