Sentiment AI

Sentiment AI

Sentiment AI

AI systems which measure the effect of human interaction behaviours on customer experience

United Arab Emirates

United Arab Emirates

For-profit, including B-Corp or similar models

Research shows that low-quality customer experiences alone could cost companies $3.8 trillion globally in 2025. Human interaction and relationship-building, at the top level, has been an intuitive domain. An 'art' not a science. Often the best salespeople, leaders, and customer relationship managers do not even know how they are so good at what they do. This means that many human teams can't a great culture, don't have great leaders, and deliver mixed customer experiences: not everyone can understand how to behave to create great experiences - there isn't much robust data to measure this. We build AI systems that measure statistically: 'how should I behave to create a great experience?'. And coach human teams on how to improve their interaction behaviours with customers and each other.

Our solution is a chain of multiple large language models which analyse human conversations to measure behavioural/emotional/language patterns. These language models pass this data into statistical machine-learning frameworks in order to measure the statistical effect of different behavioural patterns on business and human experience outcomes. We can answer the question 'how should behave to create a great team culture, customer experience, or sales interaction?'. We use this intelligence to coach human teams, and build behaviourally intelligent digital avatars for more 'human' digital interactions. Our human teams get behavioural nudges and insights to improve their interaction behaviours in key 'trigger' moments that have the largest impact on an interaction. And our digital avatars use a behaviourally adaptive 'scenes' architecture, which allows them to dynamically switch to a different set of behavioural principles and domain-specific knowledge in real-time based on the counterparty's own emotions/behaviours.

Our solution serves two groups: frontline conversational workers at risk of AI displacement and underserved communities with limited access to quality service interactions. For the 2.8 million customer service representatives in the US, we provide targeted coaching that improves their performance by improving their customer interaction behaviours to deliver better customer experiences. And improving their compliance to legal requirements and best-practices (e.g. call recording disclosure and KYC). Making them more competitive as AI transforms their roles. Without intervention, McKinsey projects 30% of these workers may need complete reskilling by 2030. For underserved communities, particularly the 67 million US residents speaking languages other than English and rural populations lacking local service options, we enable access to quality conversational services through emotionally intelligent digital avatars. These avatars break down barriers that currently result in 71% of limited English proficiency patients experiencing serious medical errors and 1.2 million UK adults remaining unbanked due to conversational obstacles.