Snowflake CEO Sridhar Ramaswamy, a week after taking over for Frank Slootman, talked customer value, product positioning and integrating AI as the company’s succession speaking tour continued.

To put Ramaswamy's comments in context it's worth noting the cadence. Last week, Snowflake said Slootman would step down and remain chairman. Shares took a big hit. Ramaswamy and Slootman made the rounds with customers on the succession. Now there's an investor tour where CFO Mike Scarpelli appeared at a JMP Securities conference to note that Ramaswamy is more than just a technologist.

And on Tuesday Scarpelli rode shotgun with Ramaswamy at the Morgan Stanley Technology, Media and Telecom Conference. Ramaswamy reiterated that he knows scale from his experience at Google with a team larger than Snowflake's employee base and more than a technologist.

Here's a look at what Ramaswamy had to say on some core themes that'll matter to customers.

Snowflake's potential. Snowflake is a cloud data warehouse play that will have to earn its spot in the generative AI world. Ramaswamy's mission is to put data in the middle of all those AI applications and compete with upstarts such as Databricks.

Ramaswamy said he can take the legacy of Snowflake and build on it with "an increased sense of urgency, much more competitive paranoia and just the desire to get things done fast." He said:

"I signed up because I think Snowflake can be a $100 billion revenue company, not because I believe like in what we announced last year or what we are going to do this year, I think it is a similar kind of potential for Snowflake. It's that combination of proven ability to execute at scale plus the technology chops."

Moving faster and balancing teams and priorities. Ramaswamy said he can collaborate with teams within Snowflake to get things done.

"I don't think of myself as just a product leader. And that part is important. I worked extensively with business teams of all kind, helped products go from scratch to massive scale...

And having said that, I think there is enormous opportunity in product innovation, in being able to provide additional depth with our existing customers, but also significantly wrap-up new kinds of customers, new kinds of use cases.

Obviously, at any given point in time, there need to be priorities. We can't be everything to everybody at the same time. And we sort of have our work cut out in my mind for, say, the next quarter or two, that really it's about taking the slew of things that we have in public preview, whether it is transactional tables or interoperable storage or an application platform, all the things that we have announced in AI, getting them into GA, getting them into the hands of our customers, that is going to drive momentum for this year."

Extending Snowflake. Ramaswamy said Snowflake's promise is that there is a broader opportunity to extend its platform and ecosystem. The Snowflake platform and ecosystem is "an incredibly rich vein to be mined for many years to come."

He said:

"If you're using Snowflake, you don't have to worry about how your data flows from AWS to GCP. We take care of that. We take care of replication. We truly provide transport and framework almost that is able to bridge a lot of these things."

Customer value. Ramaswamy said Snowflake's consumption model is aligned with delivering customer value. Snowflake will do more work upfront to ensure it delivers that value. "There is power in this model and that our customers only pay for what they are using for," he said.

Ramaswamy said:

"We are also a lot more disciplined about how we work with customers and how they spend their money. We know that at the end of the day, the CIO has to go justify the Snowflake line item to their CFO. There's a lot more attention to how things are being implemented and making sure that the customer is getting enough value out of the spend."

Ramaswamy added that Snowflake's growth path is about winning use cases.

Cortex, AI integration and the roadmap ahead. Ramaswamy said Cortex is now in public preview and will be generally available in June at Snowflake Summit. He talked up Model Garden and model choices, but Cortex is the big focus. "Cortex hit public preview today. We hope to have it in GA by Summit time, which is early June. And we think this will be like a meaningful addition to our AI portfolio simply because it enables any person that can write SQL on top of Snowflake to also become an AI person out of the box," he said.

Ramaswamy added that Snowflake has learned a lot from its Snowpark launch.

"There's a slew of stuff that's coming to GA, but we need to almost bring a new lens to how we think about sales enablement, whether it's in the field, the CTO office or the sales engineers or even the account exec, and being able to confidently pitch and say that use case, you can do like very, very quickly on top of Snowflake.

While we like what Snowpark has accomplished, I would actually say the value of Snowpark is much more in it telling us what we need to do in the future."

The competitive landscape. Ramaswamy was asked about Databricks arguing that its platform is better suited for unstructured data. His answer:

"Snowflake actually does just fine with unstructured data. We support storing data in XML being able to access it, being able to write SQL queries on it, and being able to access it from Python.

So, I do not feel that is a competitive gap, it's more companies trying to highlight their strength. For example, with the Databricks notebook, which I have used a lot of, as I have with Snowflake, your typical modus operandi is that your data is sitting in S3, and you fire up a notebook and you try and access it from within that notebook. You might write Python or SQL code to be able to do it.

But what was remarkable about Snowflake is our ability to handle data at scale. So, for example, we loaded the entire Neeva index, which was multiple petabytes, it was all of our search pages, into Snowflake, and we're able to run interactive queries on not a very large warehouse.

We offer excellent performance for both structured as well as unstructured data. We also support these things called external tables where you can keep the data in S3, and you can create an external table that references that.

And then finally, for example, we have published benchmarks on things like Iceberg sitting in external cloud storage, in which we show that the performance on those tables is pretty similar to that of performance on top of regular Snowflake."

Overall, Ramaswamy said he felt good about Snowflake's positioning, but did note that "we are behind on the notebook." “There is a product in private preview. Just like with AI, where we went from not quite there to being world-class in six months, we will make sure that we ramp up with that much ferocity and velocity," he said.