Case Study | Emotionise

About Emotionise ai

Connecting emotionally with the target audience leads to better engagement and sales, so imagine if AI could help provide that emotional intelligence. That is the idea behind the creation of Emotionise AI. They have trained their AI in an innovative and unique way to help target the concerns, desires, and emotions of the audience when creating content or communication. Emotionise AI has trained AI to generate emotions and transform your content and commination based on how the target audience feels to increase user sales and engagement.

Challenge

Businesses and organizations spend millions on trying to connect emotionally with the audience by creating engaging content. However, few businesses actually reach their sales target. Due to recent advances in neuroscience, businesses are aware that their users don’t remember content unless they emotionally connect with it.

Marie reached out to HST Solutions in order to train the AI to understand the emotion, desires, and concerns and create content and communication that targets those emotions. The challenge is to accurately understand what Marie was trying to accomplish and make sure the correct training data is collected so that the training for the AI is not compromised.

Technology stack:

.Net Core | Azure Functions | Razor | Azure Data factory | Azure SQL | Azure containers | Miroservices

Services:

  • Product Strategy
  • Software Architecture, Analysis
    and Design
  • UI / UX Design
  • Born in the Cloud Software Stack
  • Full Life-Cycle Application
    Development
  • API Automation

Reference:

Jason Poonoosamy Head of DMS Market Access

Solution

The solution was to create a neural network which teaches the AI to process data inspired by the human brain. HST worked closely with Marie using her expertise in psychotherapy and her knowledge of the TV industry, to train an AI that helps the user create content and communications based on the audiences concerns, desires, and emotions to increase sales and engagement. Using Cloud Based NLP and AI Technology, Emotionise AI generates exactly what the user’s target audience is feeling and it is the only content creation AI trained with emotion at its core.

Our approach towards building the neural network followed the below path:

The first step was creating a supervised learning model, this is where the team at HST started training the AI model with
labeled datasets.

This allowed the AI to build its knowledge regarding the different range of emotions available and the type of content based on that emotion.

Once the AI model was trained, the next step was to develop an unsupervised learning model where the AI starts learning new content and emotions without any human intervention.

With regressive fine tuning and providing metric learning allowed Emotionise AI to become the powerful AI it is today.

The HST team followed an agile driven software development process which led to the great success of Emotionise AI.

The result, the AI model consistently produces highly accurate content.

Emotionise AI now generates exactly what the user’s target audience is feeling and it is the only content creation AI trained with emotion at its core.

Technology stack:

.Net Core | Azure Functions | Razor | Azure Data factory | Azure SQL | Azure containers | Miroservices

Services:

  • Product Strategy
  • Software Architecture, Analysis
    and Design
  • UI / UX Design
  • Born in the Cloud Software Stack
  • Full Life-Cycle Application
    Development
  • API Automation

Reference:

Jason Poonoosamy Head of DMS Market Access

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