Jade: developing AI capability for chatbots and predictive modelling

Jade logo

A couple of weeks ago I sat down with Eduard Liebenberger who is the head of digital at Jade to find out a little about their AI capabilities and plans. Eduard is passionate about AI and the possibilities it brings to transform the way we communicate with businesses.

In Eduard’s words, Jade’s core focus is around freeing people from mundane/repetitive tasks and instead allow them to apply their creativity/expertise to more challenging tasks – and the JADE development, database and integration technologies. Eduard and the team at Jade have been watching recent developments in AI and identifying which of these they can use to help their customers. Their first foray has been into conversation interfaces (chatbots). They’ve developed a number of showcases, including an insurance chatbot called TOBi which shows how the technology can be used to make a claim, change contact details etc. From their they have started rolling out this technology into existing customers.

The chatbot uses natural language processing and sentiment analysis. It aims to make businesses interactions with their customers more efficient by allowing them to communicate via conversations that don’t have to be in real time, like a phone call and are more intuitive than a web form. Jade’s main advantage with their existing customers is that they have already done the tricky integration work with the back-end systems and so can fairly quickly add a chatbot as an alternative to an existing interface. Jade’s focus on the digital experience means they invest heavily into making this a natural and human-like interaction. For non-Jade customers their attraction is their ability to deliver a whole solution and not just the chatbot.

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Another advantage Jade has is that through their existing customers they have access to a lot of data that can be used to power machine learning applications. One example Eduard talked about was a summer intern project with a NZ university to try and identify students at risk of dropping out.  This was done using the data in student record database which is powered by Jade and contains several years’ of records. In just a few weeks the interns built a predictive model that was able to predict which students were likely to drop out with 90%+ accuracy. Ed is a big fan of rapid development for these types of proof of concept projects and doesn’t believe it should cost a fortune to get value from AI.

Overall, I think it’s fair to say that Jade’s AI capability is nascent. However, it’s positive to see that they are looking to build capability, understandably with a focus on the business benefits to their customers. I’m keen to see how it develops.

For those that want to find out more, Eduard is delivering the keynote at Digital Disruption X 2018 in Sydney, and presenting at DX 2018 and the AI Day in Auckland, all later this month. He’s a busy man.

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