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‘Confluent is helping enterprises with data governance following the advent of AI’ : Rubal Sahni, Area Vice President & Country Manager India, Confluent

Rubal Sahni, Area Vice President & Country Manager India, Confluent

In an exclusive conversation with CXO Media & APAC Media, Rubal Sahni, Area Vice President & Country Manager India, Confluent explains how Tableflow acts as a central place to connect different systems and stream data to downstream applications. This approach with data streaming allows businesses to use their data in real time, improve customer service, decrease risk and become more resilient, and be more operationally efficient.

What are the solutions and services currently in the Confluent portfolio that are available in India?

Confluent has a data streaming offering that meets every company’s needs – whether that’s fully managed with Confluent Cloud, self-managed with Confluent Platform, or “Bring Your Own Cloud” (BYOC) with WarpStream. Confluent Cloud is a good option for companies looking for something that’s fully managed and cloud-native. It simplifies data streaming and alleviates the burden of managing Kafka clusters and has instant provisioning, seamless scaling, and secures data moving across the organization.

Confluent Platform is an enterprise-grade distribution of Apache Kafka that is designed for on-premise deployments and has advanced features for stream processing, security, and governance. “Bring Your Own Cloud” (BYOC) with Warpstream is a service that allows customers to deploy and operate data streaming within their own virtual private cloud (VPC). This is good for organizations that have compliance requirements prohibiting data from leaving their VPC
and it provides more control over their data and infrastructure.

Which are the verticals witnessing maximum traction and what are their proportional contributions? What are the possible use cases?

Many organizations in banking, insurance, finance, telecom, entertainment, and manufacturing are turning to data streaming to unlock the most value from their data. For example, for companies in banking, insurance, and fintech, having trustworthy and real-time data is critical in decision-making. Recently, we’ve seen many companies using data streaming for real-time fraud detection and payment transactions. There’s also companies in these industries that are using data streaming to develop hyper-personalized customer experiences including customer 360s, real-time personalized offers, and dynamic pricing.

In the telecom industry, we have seen data streaming support the merger of business support systems (BSS) and operations support systems (OSS). Confluent provides a robust and scalable platform for real-time data processing and integration, which is helping to modernize and streamline operations.

How do the advancements in Tableflow address the concern of data coming from heterogeneous sources and the problem of applying analytics on them?

With the launch of Tableflow, we are essentially shifting data governance and processing to the left where data is generated or streamed. There are many benefits to this approach including reducing costs and easily moving data from the operational to the analytical estate to power real-time analytics. This allows businesses to make decisions in real time, instead of relying on outdated data that’s hours or even days old and is no longer accurate. By the time you act on this outdated data, the boat has already sailed; you’ve lost a customer. If you want to focus on moments that matter, it’s all about real time.

How does Confluent plan to address the challenges of enterprises looking to revamp their data infrastructure by totally revamping their existing platforms?

Every three to five years, organizations refresh their data infrastructure. With the advent of GenAI and the growing focus on data, it’s become paramount for businesses to examine their underlying data infrastructure stack. However, there’s no need to revamp or abandon existing investments in legacy platforms. Organizations can still extract value from these systems by bringing the data into Confluent, which acts as a central place to connect different systems and stream data to downstream applications. This approach with data streaming allows businesses to use their data in real time, improve customer service, decrease risk and become more resilient, and be more operationally efficient while saving on infrastructure and management costs.

What are the key pillars of Confluent’s GTM strategy and what are the key initiatives undertaken as part of the strategy?

Partners are a critical part of our go-to-market strategy. We work with all of the major cloud partners, such as Google Cloud, AWS, and Azure, local partners like Jio Platforms in India, and global systems integrators like Infosys. We collaborate with global systems integrators (GSIs), Indian GSIs, and regional partners who bring domain expertise in each area to deliver the best solutions for our customers. Additionally, we have a direct sales team that works closely with
our partners on joint sales efforts.

What are Confluent’s unique differentiators over other AI competitors?

Confluent helps customers leverage AI for real time insights. For any AI project, you need to use real-time data that’s fed into large language models, small language models, or AI agents. These can either be built internally by businesses or made using pre-built AI solutions.. Confluent plays a foundational role in the data layer which is like a composable, building-block model.

In this block model, Confluent is the underlying layer that can help businesses stream, process, connect, and govern data. On top of that, like building blocks, you can add agentic AI solutions—whether for industry-specific verticals, front-office customer interactions, middle- office operations, or back-office logistics and delivery.

For those enterprises migrating from a legacy environment how does Confluent help them to keep pace with new consumer expectations?

If customers are looking to migrate from legacy environments to Confluent, move to the cloud, or need support for AI initiatives, we have our own professional services team and service partners who can help make this happen. We help transform these organizations to real-time businesses by helping them re-visualize their data sources, bringing data into one place, and streaming it to various parts of their business.

What are going to be Confluent’s key focus areas in the next 12-18 months?

Over the next year at Confluent, we want to expand our partnerships with existing partners and work together on customer and prospect initiatives. We aim to transform data by marrying real- time data in the operational estate and analytical estate together to lower costs and improve their security and risk posture when feeding real-time data into their tools and platforms. We also want to elevate our customers’ experiences so they can better anticipate their customers’ needs in real time and capitalize on the moments that matter most as they happen.

Rajneesh De, APAC Media