Emotuit Engagement Analytics

Engage Student & Improve Learning using facial expression recognition & machine learning.

Using facial expression recognition, machine learning and big data analytics, we are able to understand exactly how students are responding to online learning content. This allows us to provide insight into which students are at risk and which students need support. Moreover, we can help improve content by feeding back information when content isn't engaging to students. 

We are revolutionary expression and emotion analysis along with machine learning to ensure that we can use personalized analytics, meaning we understand what the responses you're exhibiting mean to you. Not what an average is, but for you. 

Our solution is built on technology. The AI, Machine learning and big data analytics allows us to take the feed of information we get and really understand more about the students and learners. Without it, this wouldn't be possible. 

Successful pilots and data to show the efficacy of improved learning using our systems compared to normal. That and rolling out to universities and colleges. We are in the process of rolling out to ASU and they're helping us better our solution as we go. 

To have our analytics as the core behind what people use when they want to understand more about students. The forefront for personalized learning using accurate data. 

We have spent time marketing ourselves and ensuring people know what we do. We're now looking to work through vendor partnerships to make sure we can roll out successfully to their companies/ clients through integrations

100 - small pilot group which will be getting bigger. This is just to start and help us make changes to our software as we go. 

100000 - would love to hit 100,000 students in the next 12 months - we can do this via colleges and universities with online presence. Now that side of learning is growing a lot, it's vital they understand their students and content. After 3 years I'd like to see 1 million students using emotuit. This will allow for much better content creation and reaching students/ predicting dropouts and mitigating these before they happen. 

Our VP of R&D has over 10years studying the links between emotions and learning and we have over 10yrs in working with highly complex IT solutions and the education space. 

We charge $2.50 per student license per year, to the university or college. This makes it very easy for the universities to scale up and down numbers with us, and we have other products in the pipeline to help faculty understand their data more, which will help us upsell our data solutions. 

We have had such small amounts of funding, that we are as self funded as we can be and with the long sale cycles in EdTech this is really hard. We would like to use solve to help us get over the cashflow problem and provide us the platform to get some great case studies that enable us to sell easier to universities and schools. 

Sales Cycles and data driven outcomes, as mentioned above really.