Cambridge-based ZyloTech recently announced the first artificial intelligence-powered platform for advanced customer analytics. The platform, as the company claims, enables organisations to solve data quality issues and analyse all customer data continuously and in near real-time for superior insights in support of omnichannel marketing operations.
ZyloTech, formerly known as DataXylo, was founded in 2014 by Iqbal Kaur, a former director of analytics at Target, and CEO Abhi Yadav, a serial entrepreneur and MIT Sloan School of Management graduate.
The startup’s technology makes use of machine learning algorithms to integrate a company’s customer data from multiple sources as quickly as possible. The ultimate goal is to help companies make more money off their existing customers by reaching out to them at the right time with the right offers.
Analytics India Magazine spoke to Kaur and got insights into the company as well as the industry.
Analytics India Magazine: Would you like to talk about the customer analytics platform that ZyloTech is developing and what are the underlying technologies that you are using?
Iqbal Kaur: We realised that as customer data is growing exponentially, it’s getting much harder to curate all the data in a timely way and also no standard framework to do customer analytics which can help towards monetisation (cross/upsell) and retention in a hyper personalised way (individualise). So, with our patent-pending Automated Machine Learning (AML) technology we have created to fuzzy match customer data across silos and relevant feature engineering so that our embedded analytics engine with numerous machine learning algorithms including deep learning to generate relevant metrics but also find much deeper patterns which can help towards individualised offers and promotions. Our goal is to seamlessly help marketers and business users to leverage all their customer data towards customer monetization, retention and individualisation.
AIM: How is the company using AI and machine learning to solve data quality issues? Would you like to highlight a few use cases?
IK: As mentioned above we have built a bottom-up data pipe, which once enables data normalisation and with entity resolution creates an ongoing data match with a combination of both deterministic and probabilistic match. So, in the case of a Financial institution where they use several hundred data sources and the customer name is spelt in numerous ways i.e John Smith and J Smith. It can be unified and continuous curations happen in our dynamic data engine to further fuel quality data for embedded analytics layer.
AIM: How did the idea of founding ZyloTech materialise? How has been the growth story so far? Could you also add a note on the founding team?
IK: Zylotech was born in MIT as a lab project when both ex- GE executive – Abhi Yadav and I, shared the frustration of a lot of Big Data noise but equally big void of Big Insights for business. So while leveraging the MIT ecosystem and class help with some renowned Professors including Michael Cusumano (who is still a current Board Member) and Sandy Pentland to name a few, this idea shaped up as a Company, while now we have 250% YOY of growth rate with enterprise clients while serving customer-centric industries like Retail, Financial & High Tech.
AIM: What are the other deliverables ZyloTech provides in the industry?
IK: We are a profound thought leader in AI and Analytics space both in US and India. Our team is continuously working to contribute on Open source frameworks of core AI frameworks and data engineering technologies and further advancement of AI and Customer Analytics. We also encourage diversity and training more women data scientist and engineers.
AIM: What is the future of analytics and AI at ZyloTech?
IK: We are marching towards a category leadership position on Customer Analytics while being at the bleeding edge of innovation on AI and Customer Analytics. We will continue to educate our ecosystem on advancement and will continue to foster the ease for business users while AI doing the heavy lifting.
AIM: How has the AI industry evolved in India in terms of the overall technology adoption such as AI, analytics or big data?
IK: Just like other situations in India, within AI adoption & development to we have huge contradictions. On one hand, there is a lot of lip service, the noise around AI focus, but customers, start-ups and government are still not able to muster R&D budget, which is so critical for some real work. Similarly, everyone is trying to run faster by being broader or all over than deeper which is required here as the idea is to use AI as a toolbox to create an existing function/product excel in performance without complicating the usage for end users.
On the other hand, with many Global Innovations centres opening in India there is a lot going on with some real business challenges and data, which is also bringing a lot of wisdom and breeding talent in India.