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Teach faster. Assess smarter.Research with AI.

Intangible gives professors a single place to manage classes, generate assessments, access shared resources, and collaborate on research—powered by AI.

Professors are expected to move at industry speed—without industry tools.

  • Content creation, quizzes, grading, and tracking takes too much time
  • Resources are scattered: drives, PDFs, WhatsApp, old notes
  • Updating curriculum to match new tools/roles is hard
  • Research moves slowly when collaboration and workflows are unstructured

High responsibility. Low infrastructure.

Scattered Workflow

📄
PDFs
→
📊
Sheets
→
💬
WhatsApp Groups
→
📧
Emails

One workspace. Four superpowers.

Classroom Management

  • Manage classes, announcements, attendance-style tracking (if needed)
  • Share material in one place
  • Keep everything organised semester-wise

AI for Quizzes, Assessments & Rubrics

  • Generate quizzes, assignments, case prompts
  • Create rubrics + evaluation criteria in minutes
  • Build assessments mapped to skills (not just memory)

One Resource Hub (All Subjects)

  • Single access point for notes, case studies, references, past papers
  • Department-wise and subject-wise resource organisation
  • Easy sharing across professors and batches

Research Collaboration + Requests

  • Discover professors working on similar themes
  • Send collaboration requests + form research groups
  • Track research progress and tasks inside the platform
C

Classes

Class Management View
Q

Quiz Generator

AI Quiz Creation
R

Resource Library

Resource Hub
🔬

Research Collab

Research Collaboration

Research with AI support—without compromising academic rigor.

  • Literature discovery + quick summaries (with citations)
  • Help structuring papers: outline → draft → refinement
  • Submission readiness: checklists, formatting, references
  • Track versions + collaborate with co-authors
AI

Research AI Workspace

Query
"Machine learning applications in educational assessment"

Summary

Machine learning has shown significant potential in transforming educational assessment through adaptive testing, automated grading, and personalized feedback systems. Key applications include predictive analytics for student performance and intelligent tutoring systems.
1. Smith, J. (2023). "ML in Education" - Journal of EdTech
2. Chen, L. (2022). "Adaptive Assessment Systems" - AI Review
3. Kumar, R. (2023). "Personalized Learning" - Ed Research Quarterly

When professors get better tools, students and colleges win too.

  • Better learning experience (more relevant, structured assessments)
  • Faster feedback loops for students
  • Stronger academic reputation through research output
  • Colleges become more "execution-ready" with consistent systems
👨‍🏫

Professors

  • Better tools
  • Faster workflows
  • More research output
→
🎓

Students

  • Better learning
  • Faster feedback
  • Structured assessments
→
🏛️

College Outcomes

  • Stronger reputation
  • Execution-ready
  • Consistent systems