Everpure’s CEO Addresses Media at Pure Accelerate 2026

During Everpure’s Pure Accelerate 2026 conference, media and analysts sat down with Charles Giancarlo, Everpure’s CEO, for a candid discussion on channel partners, the organization’s data management strategy, and its new products.

Below are Giancarlo’s responses to key queries asked by a variety of talented tech journalists and analysts from a number of different IT publications and research firms.

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What is your message to partners for the rest of the year regarding new products, strategy, and the company’s new direction and how are partners reacting?

There are two parts to our message:

One is that we continue to be – we believe – the channel’s best partner in our core area which is data storage. When they expand the product line, we make it more powerful. It’s the only truly integrated product line in the business that is a single operating system managing every type of storage that customers want – with the exception of the mainframe. It’s one system that they learn and bring out to all of their customers. And we continue to invest in that. In fact, more than anybody else in the industry. 

The second part of our message is that we’re beginning to see – and I think others are beginning to see this as well – that the structure of customers’ IT environments is about to change. We’re going to go from the application-centricity that we’ve all pursued as high-technology players for the last 25-to-30 years and we now have to transition to more of a data-centric model.

We’re going into data primacy. Customers have fragmented data. They have their own version of what that data means. To try to make any sense of this, or even pull together something as you would think straightforward as an invoice, requires the integration of all these different data sources, many of which don’t agree with one another.

That’s what’s keeping a lot of IT organizations very busy. AI promises make that situation more complicated.

So we believe where the IT world needs to go is toward a data primacy model, where enterprises control their own data. They control their own context – shared context – for those data sources of truth. Then agents of any type – whether it’s an application, a SaaS service, a workflow, or AI agents – can work on those sources of truth.

And that opens up a huge opportunity for the channel because all of that requires a lot of expertise, a lot of help, and a lot of services. So we believe that is a great opportunity for the channel.

Are channel partners excited about this vision, and do they see it helping their businesses and customers?

At a 50,000-foot level, I’d say yes, but as you very well know, there are all different types of channel partners.

Some of them are probably going to remain infrastructure- and hardware-focused. Then you go across the full spectrum. On the other side of the spectrum are system integrators, and they’re like this is mana from heaven for them. Any new opportunity, any new architecture, is automatic strategic work as well as actual implementation.

And then you have everything in between.

Doesn’t this strategy potentially make many software vendors in the enterprise data stack less relevant?

Well, yes and no. I wouldn’t – but we could argue that point to some extent.

What I would say is that when we were considering this, it’s not so much a strategy as it is an observation about where we think the IT world needs to go.

When we started thinking about this nine months ago, I was very concerned that this is an observation about where we think the IT world needs to go.

When we started thinking about this nine months ago, I was very concerned that this is so new and different. Are we going to be able to get the message across? If we raise the flag, will we be alone?

Since then, we’ve been clearly watching messaging that’s coming from a wide spectrum of different players in this industry.

What we’re seeing is there is a target now. We think we’re close to the bullseye, but we see others coming in from all different directions toward the same point. They’re coming from their own points of view, obviously, but we do see some convergence around this idea that the data actually has to be primary. It has to start with a source of truth.

You have everyone from people who provide ETL tools coming to this. All of the usual suspects that you would imagine, some of which have been acquired, are now thinking we help customers get to their source of truth.

You have the individual SaaS players trying to figure out how they fit into this because the idea that every enterprise is going to give every one of their SaaS players the majority of their data is clearly falling flat. So they’re trying to figure out “how do we get access to the customer’s data?”

So we see people starting to coalesce around this idea.

Whether we’re right in the bullseye or not, we’ll learn that over the next year. But I think there’s getting to be more and more convergence – not just us, but others around us.

A competitor accused your company of profiteering. How do you respond?

Well, I think we have a proof point.

The proof point was that we indicated on our fourth-quarter call that we were operating at the lower end of our gross margin range, and we did. That was a decision that we made.

That tells you whether or not we’re profiteering.

Our gross margins go up – we’re effectively a middle man for semiconductors. We have a lot of software and so forth, but our physical bill is affected by the price that we have to pay for semiconductors, which is going up somewhere in the six-to-eight-times range in the last six months. It’s breathtaking.

Our prices have gone up by far less than that, and we’re operating at the lower gross margin.

So I think that’s the proof point.

We’ve been following competitors’ price raises. They’ve been sooner than ours, and they’ve been larger than ours. You can do that research.

So I would argue we’re not profiteering and the proof is in our financial results.

Is there a correlation between agentic AI adoption and storage growth?

There will be. I think AI uptake has been strong in the enterprise, but not so much on-prem. It’s largely in the cloud because enterprises are still largely experimenting.

If you’re experimenting, you don’t want to be buying a $10 million AI farm that you’re not quite sure what you’re going to do with yet. So you’re effectively leasing space or leasing capacity from an AI provider of one type or another.

I would say that as inference starts to grow, you don’t want me answering the same question as if it’s for the first time every time the same question gets asked.

You want to be able to store results.

A lot of AI, especially in the early days, didn’t store results beyond a few prompts.

As organizations want to use it, they’re going to want to retain more.

There were a couple of announcements over the last six months about token maximization. I never understood that. I’ve yet to meet business leaders from token maximization.

You want to use tokens, but they cost money. For the same answer, you want to minimize the amount of tokens, and storage helps a lot in that environment.

As we start seeing continuing usage of AI, I think it will build out storage.

Storage is cheaper. It’s cheaper than memory, and it’s cheaper than total regeneration.

Why should customers begin the transition to a data-primacy model now instead of waiting?

Well, it is a multi-year journey.

We are doing this internally. It’ll probably be about a 2.5-year journey for us to reconcile all the data sources that exist for us in all of these different application environments and create systems of record and the governance around those systems, which is really critical.

But what is the outcome of that?

First of all, we should be reducing the amount of human labor associated with processes that are held together with bailing wire and Excel spreadsheets.

It should actually reduce the number of copies of data, which is a really critical thing for many purposes.

One is it lowers your attack surface for cybersecurity. They have a lot of reliability issues. So it should reduce the number of copies.

You just have to improve the industry and hopefully get rewarded for it, not focus on the short term. It makes no sense to try to increase the amount of storage that customers need if you can come up with a way of reducing it.

The question is ‘what is the goal that they set for themselves?’ It may not change what they do this year, but if they’re going to head towards data privacy, it may change the way they perform this year’s activities.

How do you help customers solve the organizational challenges of data-centric IT?

This is an area, and this is related to the first question, which is: what does it mean for the channel?

You can’t solve the problem by just having one group involved, right? One of the reasons why there’s that proliferation is because a lot of these apps reflect workflows in those individual organizations that makes it very comfortable for them. Now, the considerations around the core elements of those workflows that exist in each of the different functional organizations have to come together and come to agreement.

As you now focus on your new workflows or your new environments, think of it in terms of how it’s going to affect how you organize your data. Because at the right enterprises, they truly don’t have control of their source of truth. And what you want now is an enterprise source of truth.

How are customers responding to this new architecture?

As we spoke to our most advanced customers, they’ve actually known that data is the core of their environment.

Now, they go through M&A and all sorts of other things so they’re always reintegrating, but at the same time, they’ve probably already gone the furthest in greeting these sources of truth, these systems of record.

Not that it’s complete across the entire organization, but they understand that that’s the center of where they need to get to, and they’re constantly working to do that.

I think it’s like any other new architectural way of doing things, in traditional IT, which is your most advanced customers into it first and they perhaps have to do it themselves.

Once you reach roughly a million dollars or two million dollars in market opportunity, the system integrators think this is a great startup opportunity. The SIs get involved and then they can bring it to a larger portion of the enterprise. It’ll happen like any other revolution.

How are you changing your go-to-market strategy?

It’s a fairly extensive addition to what we are able to provide in the go-to-market area. We’re very much bulking up in this area. We’re hiring extensively.

We will have four deployed engineers who know a lot about our product and how to deploy it, but more importantly, can help consult with customers to be able to deploy it and start to go down this path towards data privacy.

A lof of that will be in training of our partners who start to lead in this area overall, so that’s a really important part.