Mumbai-based Netcore Cloud (formerly known as Netcore Solutions) was founded in 1997 by tech entrepreneur Rajesh Jain. The artificial intelligence(AI)-powered marketing company equips brands and businesses with predictive intelligence and personalised engagements to serve customers better. It has partnered with the likes of Once Upon A Trunk, Mobile Premier League, Flipkart, and more recently, BYJU’s to enhance their customer engagement and experience. According to the company, Netcore Cloud’s AI-powered recommendations contributed to 28 percent of Once Upon A Trunk’s overall revenue.

In an interview with Analytics India Magazine, Group Technology Officer Bijal Sanghavi discusses the technology behind Netcore Cloud’s customer engagement and experience platform. 

Bijil is an alumnus of the State University of New York, Binghamton. He has over two decades of experience across various roles — product development, project management and user experience, implementation, and customer success management. Before joining Netcore Cloud, he was the Vice President of Zycus Technology, leading the product and engineering teams. 

Edited excerpts from the conversation: 

AIM: What is the problem that Netcore Cloud is trying to solve? How does it go about the process? 

Bijal Sanghavi: The role of the CMO and growth manager is key to the success of any organisation, and yet most of the time, the tools they use fail to provide them with a unified view of the customer. We, at Netcore Cloud, work at the forefront of modern-day technology, be it AI or machine learning (ML), hyper-personalisation or data analytics, across our multiple product suites to provide CMOs and growth managers with more intelligent methods of consumer acquisition, engagement, and retention. 

We do the above through our customer experience (CX), product experience (PX) and personalisation suites, which are most relevant for today’s digital-first world. 

AIM: What was your flagship product? When was it launched?

Bijal Sanghavi: Our customer experience suite, built on top of our CPASS API engines, was launched in 2015 and is one of our signature products. Today, these are strengthened further with personalisation and product experience suites.

AIM: Explain the tech behind Netcore Cloud’s customer engagement and experience platform? How does it work?

Bijal Sanghavi: Today, a lot of product and growth managers rely on behavioural and product analytics. Data is used towards developing a better understanding of how customers are interacting with apps and websites. This information is then used to improvise on product experience. Vertica Systems empowers us with the ability to secure real-time analytics. Real-time aggregations by Vertica backs us for routine analytics, like the showcasing of dashboards. Additionally, to find deep insights and run ML use cases on this data, we perform pre-aggregations that feed into the synchronous use cases.

AIM: How does Netcore Cloud use the power of AI and ML? 

Bijal Sanghavi: Netcore Cloud, with its wide portfolio of products, is in a very advantageous position to make proper use of AI/ML. With our presence across multiple channels, we are empowered with a plethora of information that our AI engine uses to keep learning about the customers on the fly.

With omnichannel personalisation both on-site and off-site, we are in constant touch with customers across their journey. When they land on a client’s website/app, our personalisation engine, Raman, evaluates their past behaviour and traits. Based on this understanding, it shows the products that are more relevant to them. If they inadvertently browse to part from the website, our nudges ‘ever so casually’ push them towards the right set of products. Even when not on the website, our AI engine uses emails, SMS, WhatsApp, WPN, and APN, to send them tailor-made communication to drive them towards the website or app. 

AIM: Tell us about the full-stack of Netcore Cloud. What technologies do you leverage? 

Bijal Sanghavi: Netcore Cloud, today, offers multiple product lines, each having its independent tech stack. It makes use of a hybrid infrastructure, coupled with the ingestion of consumer behavioural events being documented on the Cloud.

The backend for Netcore Cloud is an asynchronous event stream, where the ingestion layer is written using AWS Lambda and Golang. Redis is used as a queue for asynchronous processing of events across the system. Also, we use Apache Kafka and RabbitMQ for message queuing. Additionally, event processing from queues takes place in Java, Perl and Golang at different places. Post-processing, these events are handed over to MongoDB, which acts as a data lake.

Elasticsearch is also used as a data lake for our email API product line and analytics. For routine analytics, like showing dashboards, we rely on real-time aggregations using Vertica. To find deep insights and run ML use cases on this data, we do some pre-aggregations to help drive synchronous business processes based on this machine intelligence. All the applications UI are written in Angular, with PHP as the backend and MySQL as the primary database for meta-data. Armed with these advanced technologies and Apache Storm, we successfully enabled our brands to hyper-personalise their products to every user. Therefore, every customer interaction triggers a unique communication journey to customers over the various communication channels of our cPass layer.

AIM: Does Netcore Cloud use technology for hiring purposes? Would you please elaborate on how? 

Bijal Sanghavi: At Netcore Cloud, we leverage the benefits of an Applicant Tracking System (ATS) to conduct our daily hiring scrum meets. Since, technically, hiring funnels are no different than sales funnels, we focus on the funnels and drop rates at each stage of the hiring funnel. Additionally, a lot of hiring managers are continually scouting for talent on LinkedIn and Twitter. Finally, we leverage hackathons and testathons as fantastic engagement initiatives to build a thriving talent pool.

AIM: Future plans? What does the roadmap look like for the company?

Bijal Sanghavi: Moving forward, we are working towards enhancing our customer data platform, which combines data from multiple tools to create a unique customer profile. This tool is handy to marketers to create personalised and hyper-personalised marketing campaigns. 

With three back-to-back acquisitions over the last two years, the first being Quinto.ai (Conversational AI platform) followed by Boxx.ai (AI-First Omnichannel Personalisation and Recommendation Engine) and Hansel.io, we have accelerated our evolution from an Intelligent Customer Engagement and Communications platform towards building the Intelligent CX cloud. Moving forward, we are identifying companies and technologies for acquisition that will enable us to add further value to the brands that work with us. 

In the days to come, we will also focus on data analytics usage towards providing brands with an even more improved understanding of their consumers. 

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