Opsis is spin-off from A*STAR based on 5 years of R&D in MedTech research. The technology has use-cases in:
• Tele-Health, where video care providers get real time emotional feedback on the state of the people in needs. Discover and interventions with any video platform or devices.
• Tele-Education with insights metrics on teaching content receptiveness and help educators to identify online learners: Confuse, Stress or Bored.
• Tele-HR for online recruitment or training with deepen behavioral analysis data for interpretation based on psychometric evaluation.
Awards and Accolades
• 1st place in the OMG Emotion Behaviour Challenge 2018
• 2nd place in EmotiW2016 competition (ICMI)
• 3rd place in EmotiW2015 competition (ICMI)
• 2nd place in Grand Challenge Competition (ACM Multimedia 2012)
The key differentiating from those in the market are:
• Only 1 in the world using psychology circumplex model resulting in more precise emotion measurements with 2 Dimension data points.
• Real-time processing and analysis for individual and large crowd group emotional state. Most competitors allow for only single analysis.
• Technology accounts for ethnicity differences with high accuracy of 93% vs 70% available in the market.
• Thousands of mood detection with interactive responds vs 7 basis labelling
• Deployment platform includes: APP, SDK, Raspberry Pi, Cloud Service

CEO and Co-Founder

Nominated by

Senior Director,
JETRO Singapore
Opsis offers non-intrusive Emotion Analysis for Tele-Health, Tele-Education, Tele-HR. They specialize in Emotion Recognition AI using Psychology Circumplex model and are the only one in the world using psychology circumplex model with 2 Dimensions subtle expressions analysis. Their technology accounts for ethnicity and cultural differences with high accuracy especially in negative expression. They have an accuracy of 93% and are able to distinguish subtle expressions and provide fine-grained emotional insights at a low computational cost with real-time emotion analysis. Their technology helps companies and schools to detect negative feelings of their employees and students during digital meetings to monitor their mental health. It is highly needed nowadays.