Enterprise AI infrastructure faces unprecedented demands today. As AI-powered applications scale, the need for seamless data orchestration across hybrid environments is becoming critical.

For Vast Data Inc., the goal has been to operationalize the entire AI pipeline. The company has emerged as a central player as companies seek infrastructure that can rapidly optimize data flows and quickly scale resources to support next-generation enterprise workloads.

The company’s new developments in enterprise AI infrastructure were a central focus of the Vast Data “Enter the Cosmos” event, which ran on October 1 with an exclusive broadcast with theCUBE, SiliconANGLE Media’s livestream studio. There’s an evolution of a new software layer pointing the way to the future of AI infrastructure, according to theCUBE Research’s Dave Vellante.

Jack Gold of J.Gold Associates LLC talks with theCUBE during the Vast Data “Enter the Cosmos” event.

“Will Vast become the next great AI infrastructure company?” Vellante purported during a live analyst segment for the event. “Right now, Vast is in a good position to be just that, with a healthy balance sheet, strong growth and cash flow positivity — which is exceedingly rare for a young company that’s growing as fast as Vast.”

theCUBE Research’s analysts explored the latest announcements during the event, talking with data platform experts, analysts and industry insiders about developments driving innovations in enterprise AI infrastructure and beyond.

Here are three key insights you may have missed from the Vast Data “Enter the Cosmos” event: (* Disclosure below.)

1. Vast has big plans for enterprise AI infrastructure.

Last year, Vast introduced its data platform on theCUBE, which has four components: the DataStore, DataSpace, DataBase and DataEngine.  It’s a parallel transaction database that does analytics, Vellante noted.

Dave Vellante of theCUBE analyzes the Vast Data “Enter the Cosmos” event.

“We heard about this novel lock management. It’s got full system observability, bridging the gap between structured and unstructured data, disaggregated shared everything,” he said. “It’s just really back to deep computer science roots for those of you who are interested in that kind of stuff, running anywhere. Vast calls this the [operating system] for the AI age.”

As a part of this year’s “Enter the Cosmos” event, Vast announced the Vast InsightEngine in partnership with Nvidia Corp., advancing the capabilities of enterprise AI infrastructure, which speaks to the Cosmos community that Vast is building out, according to Rob Strechay, principal analyst at theCUBE Research.

“[Vast is] aiming at AI and bringing it together,” Strechay said. “Also, there was the engine for insights that they’re building out, [which] is about how to move up the stack, and continue to move up the stack from a data perspective to be more of that data layer for people doing AI.”

Vast has origins as a storage company, with the goal of being a data company, a database company, and a key player in enterprise AI infrastructure, creating an operating system for AI. All told, Vast is indeed trying to move up the stack, reiterated Jack Gold, principal analyst at J.Gold Associates LLC.

“They’re trying to move up to a level that says, ‘Hey, without us, you can’t do AI from an enterprise perspective.’ And that’s actually probably a pretty good play for them because if they can move up the stack, one, they can charge more,” Gold said. “And number two, the visibility also helps them as they try to go to an [initial public offering] in the not-too-distant future. That’s certainly not a bad thing.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE Research’s coverage of Vast Data “Enter the Cosmos”:

2. There’s a goal to unlock unstructured data for AI transformation.

There are two problems that hold enterprises back from using large-scale AI across the business, according to Jeff Denworth (pictured), co-founder of Vast. The first is that a model can’t be trained with all of an organization’s business.

Vast’s Jeff Denworth talks with theCUBE Research’s John Furrier.

“I was with a Fortune 10 customer the other day. They said, ‘We probably have about 100 petabytes of unique data.’ GPT-3, just to give you a comparison, was trained on like 45 terabytes,” Denworth said. “And so there’s just more data sitting within an organization than what can be cost-effectively trained within a model.”

The second thing is that when one trains a model on any amount of data, the thing it can’t do is preserve the security policies on that data that was trained on, according to Denworth. If two individuals get the same model and have different permissions at the source data level, it doesn’t come through.

“The way that we saw this is that there was an opportunity to make what’s called retrieval-augmented generation, or AI retrieval, a lot more simple to deploy across the enterprise,” Denworth said. “It starts with unstructured data, which has always been our specialization.”

There are different ways to approach retrieval. But at the end of the day, what’s taking place is that file systems are evolving, according to Denworth.

“If you think about it, you now have another form of metadata in the form of vectors that makes your data conversational,” he said. “When you go down to your source data, you can get answers out of that data, not just lists of files or things like that. You’ve got a laptop here that presents all the files to you, but it doesn’t say what’s in those files. It doesn’t allow you just run a [large language model] to ask questions to that data.”

For 40 years, there’s been structured and unstructured data. The unstructured data is 20 times larger than the structured data market that sits in enterprise data warehouses and databases, according to Denworth.

“Well, let’s suppose that over the next couple [of] years, the unstructured data industry will disappear. Why is that? Because now you can query on all of your data, and I think it’s just a massive opportunity for organizations to unlock their data,” he said.

Seeing a world where all data is accessible, Vast announced its Vast InsightEngine in what could be a significant step forward in enterprise AI infrastructure development. The platform merges the concepts of data storage and database to create a transactional data warehouse on top of an unstructured data store.

Here’s the complete video interview with Jeff Denworth, part of SiliconANGLE’s and theCUBE Research’s coverage of the Vast Data “Enter the Cosmos” event:

3. There’s an eye on simplifying real-time data integration for RAG.

It’s no secret that many companies are excited about RAG. The problem for most is merely accessing the data to RAG the model, according to Gold.

“It’s hard to get the data in real-time, which is really what you need to do if you’re going to use AI in any production environment,” he said. “It’s costly. You may not even know where the data is.”

Vast is trying to approach this problem. The company has a specific approach on its hands, Gold noted.

“There’s a huge focus in the [Vast] announcement on real-time and the difficult challenges of AI retrieval, and they’ve announced an in-architecture vector database,” Vellante added. “They’ve got this globally because they talked about a consistent atomic file system, which eliminates the whole batch operations and is scalable.”

“What Vast is trying to do is: ‘I don’t care where your data is, just point us to the data [and] we’ll be the consolidator. We’ll bring it in, we’ll put it into one format [and] we’ll be able to do it in real-time,’” Gold further explained. “We’re breaking down the silos of data into more of a plane if you will, a mesh, that’s very valuable for RAG because that’s what gets you to the real-time environment. If you can’t do this in real-time, then RAG doesn’t work for most people.”

Vast has announced that its InsightEngine with Nvidia will be generally available in early 2025, and pressure is high to pull it all off, according to Gold.

“I’m assuming they can, or they probably wouldn’t have announced it, or [Nvidia Chief Executive Officer Jensen Huang] certainly wouldn’t have been on stage with them if he didn’t think they could do it,” he said. “I think it’s going to be a game-changer for these guys.”

Here’s the complete video playlist, part of SiliconANGLE’s and theCUBE Research’s coverage of the Vast Data “Enter the Cosmos” event.

Photo: SiliconANGLE

(* Disclosure: TheCUBE is a paid media partner for the Vast Presents: Enter the Cosmos event. Neither Vast Data, the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)