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HeyHi Pte Ltd

Headquarter
Singapore
Established
2021
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Profile
Segment                        :
Education Technology Company (EdTech), Online Learning Portal, Publisher/ Content Provider
Phone                             :
+6592323945
Address in Singapore  :
284 River Valley Road #01-01 Singapore 238325
Email                               :
All Office Locations
Singapore
Flagship Event
About
HeyHi is a unique AI-enabled assessment and personalised learning system that empowers educators to teach and personalise education efficiently and seamlessly in a highly collaborative learning environment. With teaching versatility for both ‘live’ and self-paced instructions in a flexible learning environment – online, on-site and hybrid, we magnify learners’ opportunities and enhance their borderless learning journey.
Key Programmes/Products/Services
Our products:

HeyHi Assessment: A holistic e-assessment and diagnostic solution
- Question Bank-based Content Management System
- AI Worksheet Generator for personalised & adaptive assessment
- Manage your own question bank, in addition to ~150,000 ready-to-use questions
- Auto-marking with instant feedback
- Detailed analytics reports to identify learning gaps

HeyHi Collaboration: A dynamic Learning Space that mimics real classroom experience
- Video conferencing solution with interactive online whiteboard for collaborative learning
- Optimised to engage learners for real-time online collaboration
- Synergistic teaching tools from ease of drag-drop file access from personal library to live interaction via intuitive writing and drawing
Community wall

HeyHi Academy: A centralised content library to scale teaching efficiently & seamlessly
- Digital content library accessible from anywhere
- Enable digitalisation, organisation and productisation of educators’ lesson contents and materials
- Facilitate different mode of lesson delivery – drip-feed, self-paced & adaptive learning

Data & Artificial Intelligence Technology
- Augmented with AI-powered algorithms
- Analyse and make diagnosis based on data with further optimisation using machine learning technology in Recommendation System
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