eClapper — Emotional AI for Recommendation Systems
eClapper is an emotional intelligence API layer that integrates on top of existing recommendation systems. It detects users' real-time emotional state and re-ranks recommendations to improve relevance at the moment of choice — without requiring platforms to rebuild their existing stack.
Product
API-first, low-friction integration with existing recommendation infrastructure
Real-time emotional state detection through session interaction signals
Content Mood Mapping: assigns structured emotional signatures to products, content, or services
User Mood Insights: reveals how users feel in the moment, beyond behavioral data
Emotionally aligned re-ranking: improves final output quality via the eCmm API
Measurable impact: +35% conversion rate improvement, reduced churn, increased session time
Core Technology
eCmm (Emotional Content Mapping Model): maps content into multidimensional emotional signatures
Real-Time Mental Signature: detects present-time emotional context
72-mood taxonomy for precise emotional classification
98.4 Mood Score accuracy, 12ms response time, 99.1 Precision, 97.8 Recall
Use Cases
Streaming and media platforms (video, music, podcast)
E-commerce and retail discovery
Enterprise recommendation engines
Company
Founded: eClapper Project Inc.
Website: https://www.eclapper.com
Contact: team@eclapper.com
Pages
Homepage: https://www.eclapper.com
Privacy Policy: https://www.iubenda.com/privacy-policy/26619934
Cookie Policy: https://www.iubenda.com/privacy-policy/26619934/cookie-policy
eClapper — Emotional AI for Recommendation Systems
eClapper is an emotional intelligence API layer that integrates on top of existing recommendation systems. It detects users' real-time emotional state and re-ranks recommendations to improve relevance at the moment of choice — without requiring platforms to rebuild their existing stack.
Product
API-first, low-friction integration with existing recommendation infrastructure
Real-time emotional state detection through session interaction signals
Content Mood Mapping: assigns structured emotional signatures to products, content, or services
User Mood Insights: reveals how users feel in the moment, beyond behavioral data
Emotionally aligned re-ranking: improves final output quality via the eCmm API
Measurable impact: +35% conversion rate improvement, reduced churn, increased session time
Core Technology
eCmm (Emotional Content Mapping Model): maps content into multidimensional emotional signatures
Real-Time Mental Signature: detects present-time emotional context
72-mood taxonomy for precise emotional classification
98.4 Mood Score accuracy, 12ms response time, 99.1 Precision, 97.8 Recall
Use Cases
Streaming and media platforms (video, music, podcast)
E-commerce and retail discovery
Enterprise recommendation engines
Company
Founded: eClapper Project Inc.
Website: https://www.eclapper.com
Contact: team@eclapper.com
Pages
Homepage: https://www.eclapper.com
Privacy Policy: https://www.iubenda.com/privacy-policy/26619934
Cookie Policy: https://www.iubenda.com/privacy-policy/26619934/cookie-policy