Data pipelines are absolutely crucial for Generative AI to work: Snowflake India MD, Vijayant Rai
In an interview with The Hindu, Snowflake India MD Vijayant Rai shares the data cloud company plans for Generative AI, and stresses that there is no AI strategy without a data strategy
Data cloud company Snowflake is at a critical junction. Its CEO Frank Slootman has stepped down after five years at the helm, and rivals like Databricks are looking to capture market share in the industry. Waiting in the wings is Sridhar Ramaswamy to charge as the company’s next chief. Both, Mr. Slootman and Mr. Ramaswamy, have indicated AI as a decisive factor as everybody is buying what Generative AI is selling. And Snowflake, with a market valuation of $62 billion, cannot afford to fall behind in terms of revenue growth.
The company has so far launched their own open-source large language model for enterprises called Arctic, previewed a GenAI-powered SQL copilot and even deployed AI models via its platform Cortex. But even with developments in this segment, Snowflake has carefully reeled itself in from succumbing entirely to the AI hype, maintaining a steady focus on helping customers with cloud transforming of their data and tamping down on costs.
THB: It’s been four years of Snowflake in India. How does the company view its long term plan here?
Vijayant Rai: Considering that India is one of the fastest growing developing economies in the world, the trajectory is only going upwards. There’s a huge number of opportunities and challenges here, which everybody believes that data will help solve. So, India is also moving towards becoming a data-driven economy. In that context, we are looking at India as a very strategic market. It has been identified as a fast-track market in terms of both investment and focus on global leadership. One of my goals is to essentially scale and build out the business from where we are at this moment. We are looking at big moves in terms of scaling our business in the enterprise segment across verticals, across commercial segments with market, small and mid-size businesses (SMBs). Because we believe that the space we are in, of data and AI, has a lot of potential, we also have the opportunity to lead this space and help provide solutions for very large-scale Indian problems. From that point of view, I think the opportunity is immense and India is a fast-track territory from Snowflake‘s internal growth perspective.
THB: Do you think Snowflake is lagging behind its competitors when it comes to artificial intelligence?
VR: Firstly, we are a cloud platform, which means that any new feature or functionality we introduce, including LLMs, will be native to the platform. The other principle is that the data doesn’t move out from the platform, the LLMs come to the data, which is a far more secure way of running GenAI. We already have a bunch of LLMs in private preview, including Document AI, which is for summarizing and contextualizing documents. We have an LLM specifically for SQL developers called SQL Copilot and we have another LLMs for universal search. We believe we have the right kind of products, which sit very nicely within our data story. We have to realize that AI is great and it is going to help customers improve their experience and accelerate their journey, but data is fundamental to all of this. Secondly, there is no AI strategy without a data strategy. So, it’s extremely important that customers have data in order, in the right shape and format to be able to then run AI on top of it. And from that perspective, the Snowflake Cloud platform is perfectly placed. I don’t think we are behind anybody. We’re probably ahead, and with the AI strategy which has been announced around our Cortex framework, I think we are going to see far more acceleration. But at this point of time, we have the right kind of roadmaps and products in preview which will help us move fast.
THB: How does Snowflake position itself in the context of GenAI?
VR: We continue to position ourselves as a data and AI platform as we have a unique architectural platform, where we will bring in AI/ML, and the data doesn’t go out. To a lot of customers in different segments, the security aspect is a big deal. We apply the same philosophy to build GenAI applications that leverage data. The customer has their data in the same place on the Snowflake cloud platform and the application actually reaches out to the platform. But GenAI applications need the right data to work so the data pipelines are absolutely crucial and foundational to GenAI applications. What we are seeing in the market now is customers accelerating their data journeys because of what they can get in GenAI because of the data.
THB: What do you think the challenges will be especially when it comes to India with regards to the adoption of GenAI?
VR: I think the first challenge is ensuring that you have your data on the cloud. That gives you the ability to work not only with structured data, like corporate databases, but even unstructured data. Because only then will you be able to break your data silos and integrate GenAI into your data to get the maximum value. The second is the whole challenge around having enterprises and other companies creating a data-driven culture, because last year was a lot of hype honestly. Its only now that we’re seeing a lot of companies starting to have initial use cases. Most of the initial use cases were around, for example, website chatbots, because that was quickly done. But privacy is the big challenge. How do you treat your data? How do you look at regulation if your industry is a regulated one? And then when you apply GenAI on top of that, the last thing you want is the results on the chatbot going out. This could create serious problems for the brand and the organization.
THB: Do you see IT spending in India increasing compared to the rest of the world?
VR: We definitely think so. Indian customers are looking at their data strategy very seriously and a lot of them are already planning to look for ways to move their data on to the cloud. So that’s a very positive sign. We are seeing pretty much every organization looking at how they can have a comprehensive strategy to utilise GenAI in the future and what the foundational things are that they need to fix first. Spends on data and AI are definitely coming up. And from a
perspective, I think IDC talks about a 23-24% CAGR in the next few years for the data market in India. So, I think I think we’re in a good space. And obviously, data is at the centre of all of this, so the spend on data and AI can only be expected to go up from here.
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