Many organizations today are floating in a ton of data. This is good for powering AI agents, but less favorable when it comes to identifying which signals from all of that data actually matter.

The solution is AI-powered trend detection, and Hewlett Packard Enterprise Co. has developed an Agentic Trend Analyzer with Aible Inc. to address this issue for customers. Delivered through the HPE Unleashed AI program and powered by Nvidia Corp.’s RTX PRO 6000 Blackwell Server Edition GPUs, the Trend Analyzer is designed to help organizations continually detect emerging risks and opportunities across vast stores of data.

“If you don’t know the question to ask, it’s really hard to be as proactive as you need to be,” said Robin Braun (pictured, center), vice president of AI business development, hybrid cloud, at HPE. “It’s allowing us to be able to find that signal in the noise. There are all of the different reports about how much new data is coming in from the edge and being created in the world. It’s so important that there are early detection signals out there, but how can we help the business find it across millions of rows of data that are being reported every day?”

Braun spoke with theCUBE’s Rob Strechay for HPE’s “Unleash AI Momentum” series, during an exclusive interview on theCUBE, SiliconANGLE Media’s livestreaming studio. She was joined by Arijit Sengupta (right), founder and chief executive officer of Aible Inc., and Rob Sims (left), chief technologist, hybrid platforms, U.K. and international at CDW Ltd. They discussed how the companies are collaborating to help customers separate signals from the noise. (* Disclosure below.)

AI agents identify key market changes

The jointly developed product between HPE, Aible and Nvidia allows organizations to sift through millions of data patterns and pinpoint critical changes in customer purchasing, spending and inventory lifecycles. Sengupta described how this revealed new insights for one particular retailer.

“We found patterns in their customer purchase behavior that was showing up in certain cities and then slowly over time showing up in other cities,” Sengupta explained. “In just one city that pattern was worth $20 million. If you can detect that pattern early and see that pattern is now showing up in other cities, you can start reacting to it early.”

CDW has found that customers are seeking guidance in how to leverage the data they have in concert with multiple AI solutions. This involves balancing the hype around AI with the realities of implementation in order to reach a meaningful return, according to Sims.

“We actually coined this thing that we call ‘From AI Crazy to AI Nirvana,’” Sims told theCUBE. “It’s acknowledging that there is a lot of hype and a lot of noise in the market, and actually we need to make a measured journey to something that is going to deliver value to the business. When we take things like [HPE] Private Cloud AI, Aible, the Nvidia ecosystem, the open-source components that are in there, etc., it really allows customers to be confident in what’s actually processing their data.”

Generating trust and compliance

That confidence translates into an ability on the part of organizations to develop trust in how data is being used. Tools such as Agentic Trend Analyzer can help manage business volatility, yet it also takes a belief that AI’s capabilities will help practitioners ultimately make better decisions, according to Braun.

“As you’re going into something like Trend Analyzer, where you’re looking for decision intelligence … if you’re going to be making decisions, you have to trust what you’re making decisions on,” she said. “Otherwise, that has much bigger ripple effects for both the business and potentially your personal career aspirations. Understanding that it’s trustworthy, that it’s reliable, that it stays within that regulatory and compliance envelope that you need for these industries is so key.”

Braun’s point around compliance is a central factor in AI’s growth and acceptance within various industries. Aible has worked closely with HPE and Nvidia to ensure that Agentic Trend Analyzer can meet regulatory requirements.

“We work with some of the most regulated industries on the planet, and if you cannot be sure about the numbers, they cannot use it,” Sengupta noted. “We also log all of that calculation into Python code, in Jupyter Notebooks, in the customer’s environment. If a regulator ever comes in and says, ‘How did you get to that number?’ you don’t say, ‘Well, this AI magically told me so.’ You can hand them a deterministically crafted actual set of calculations and say, ‘This is the full trace back to where we got these numbers from.’”

The autonomous agents within Agentic Trend Analyzer are designed to identify emerging risks and new opportunities as they develop without relying on predefined rules or manual analysis. The goal is to let organizations sort through mountains of data and gain early, more complete visibility into what’s changing and why.

“For years, the ‘data problem’ in inverted commas is not a new one,” Sims said. “But the promises over the last few years of how we’re going to solve that have really come to life in the last six to 12 months with solutions like Aible, operationalized through things like Private Cloud AI and HPE. And that really changes the conversation then to, ‘We really can give you the insights to make better decisions, to deliver better services.’”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of HPE’s “Unleash AI Momentum” interview series:

(* Disclosure: TheCUBE is a paid media partner for HPE’s “Unleash AI Momentum” interview series. Neither HPE, the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE