Bianca Anghelina, Chief Executive Officer and Founder of Aily Labs, joins John Furrier, Co-Founder and Co-Chief Executive Officer of SiliconANGLE Media Inc., in theCUBE's NYSE Studio for the AI Retail Trailblazers series. They explore cutting-edge artificial intelligence applications in retail and the significant role Aily Labs plays in transforming decision-making processes for major enterprises.
In this insightful discussion, Anghelina shares their expertise on integrating AI and mobile technology to revolutionize decision intelligence. The conversation, hosted by theCUBE Research, delves into how Aily Labs is pioneering the shift from traditional analytics to agent-driven decision-making, impacting profitability and efficiency across retail segments.
Key takeaways emphasize the tangible business impacts of AI, as described by Anghelina: improved inventory optimization and growth in top-line revenue are achievable when enterprises embrace agentic integrations. Furrier highlights Aily Labs' innovative approach as vital to companies thriving amidst the AI evolution.
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In this interview from the theCUBE + NYSE Wired: AI & Retail Trailblazers event, Bianca Anghelina, founder of Aily Labs, joins theCUBE’s John Furrier to unpack how “decision intelligence” is moving from static dashboards to always-on, agent-led guidance for enterprise leaders. Anghelina explains Aily’s AI mobile app approach and why the next wave of value in retail will come from connecting data across the value chain then putting agents to work as decision advisers with measurable P&L impact.
The discussion digs into what it takes to operationalize ag...Read more
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What is the process of transitioning from analytics to generative decision-making in AI?add
What experiences led to the founding of Aily and how did those experiences relate to the importance of AI in decision-making?add
>> Hello and welcome back to theCUBE. I'm John Furrier, your host. We are here at our NYSE CUBE Studios. Of course, we have our Palo Alto Studio connecting Silicon Valley and Wall Street tech and capital coming together as part of the NYSE Wired program. It's a CUBE original, where we go out and talk to the leaders. This is the AI Retail Leaders Trailblazer series. We talk about the leaders making things happen. Bianca's here from Aily Labs, great to have you. I like A-I-L-Y in there, so Aily Labs, but it's got AI in there, so obviously AI and retail, the talk of the show here at NRF, and certainly all around the world. Set the table for us, what do you guys do? Because you're in the heart of the agentic transition we've been covering on theCUBE. We did things on paper, it goes to the web and then mobile, now we're in an era of AI moving to autonomous. This is the shift, it's obvious to everybody. What do you guys do?
Bianca Anghelina
>> Totally, yes, indeed, and we are combining actually mobile with AI. We are the pioneer of the first AI mobile decision intelligence app, which is meant to really accelerate decisions for big enterprises, and especially what everybody's now looking for, optimize the P&L impact across the functions of a company.
John Furrier
>> On the tech side, we're seeing the surge, NVIDIA, everyone talks about the chips and the systems, the supercomputing capability, that's thundering away. That's continuing to usher in the agents, the agentic infrastructure. Jensen Huang at CES, just a week and a half ago, talked about physical AI, and that's coming into cars and our life. Certainly, when we get through agentic, we're going to see physical converges with digital. But right now, where the action is is taking those models, where people are using, the consumers have voted, they're using it, that's the new interface. Now, a new kind of middleware is developing. I use that old school term. But it's software making it all happen, this is where the action is. Take us through how you see that emerging and how businesses are leaning into it, the people who play with this and get playful with it, who are curious and experiment, are winning. Take us through how you see that.
Bianca Anghelina
>> Totally. I think just fresh from NRF, I can confirm that what you call as mid-layer agents are really front stage, both for tech companies, but also for retailers. And we see really everything, from agentic commerce to enterprise agents. We play in the enterprise agents space, and our vision is to indeed make AI through agents more accessible in a much more way we are used to interact, on a private way.
John Furrier
>> Talk about the decision side of it, you mentioned that, because the old vibe was we have dashboards, we have all this data, we have decision analytics, and now you have a whole nother level of experiences exploding. What's the new outcomes that folks are looking for as they transition? Some are like, "Wait, we're fine. I don't think so." Take us through, because they have data, retailers have the data, and the money certainly is going to be voted with, whether people are doing retail shopping, the numbers don't lie, and they're very acute to that. Talk about this transition from analytics to generative decision-making in AI.
Bianca Anghelina
>> Yeah, totally. So that's exactly what we are doing at Aily through our AI app. And I would say that the first step is actually to moving really from the vast amount of data into connecting the data, really connecting the data across the value chain, especially in retail, across R&D, commercial, manufacturing, supply and finance, to really be able to get to a multi-million impact to the P&L, which everybody expects. Now, how do we do that? We are deploying agents on top of those connected data sets, and the agents are not just simply chatbots which will answer questions, but they are operating as real decision advisors on top of the data. And the way how we configure it is, depending on the industry, they optimize for a specific goal which is relevant for the industry. So to give you an example on one of the enterprise agents, which I think is relevant really across retail, CPG, but also life science, is our inventory optimization agent, which is meant to really allocate inventory based on internal and external data in a much more real-time and efficient way. And what we see is indeed that this can directly impact the top-line. We see that the business impact can actually be from 5% to 10% of the top-line if applied in a consistent way and embedded really into the decision-making process.
John Furrier
>> Bianca, I love how you brought in the top-line, because a lot of people will go to efficiencies. Clearly, there's some AI benefits there. But in retail, obviously they love the top-line, don't get me wrong, but we are seeing evidence of people actually blowing their numbers away, record revenue, who have been leaning into agents in the past year, now going into 2026, are super excited, because they're now seeing evidence, top-line revenue, not just productivity. Certainly, there's tons of examples there. This kind of debunks this notion of, well, people are using AI in half the projects or whatever, 80%, that MIT study, which was completely BS, in my opinion. All the data from NRF points to the opposite. Do you agree, and what would be your comment to this phenomenon of people starting to see value in the execution?
Bianca Anghelina
>> Yes, I'm absolutely convinced about it, as that's also the core of our app. Of course, faster decision-making is about productivity and making the organization more efficient. But what our agents are designed for are to generate more growth, to optimize seasonal products, to forecast them in the first place much more accurately, which is something which in retail is very important. So in the case of our platform, we really see that optimization potential. And one part which agents, I think, now also enhance is the interaction with humans with AI. So I think you mentioned it a bit at the beginning, the beauty of agents is that it's more of a virtual employee, where I think employees can actually give their feedback much better and interact much better with the agents, versus a software which is complex to operate within or Excels or PowerPoints.
John Furrier
>> It's interesting, there's a lot of moving parts in the flywheel here, and you mentioned earlier about the manual processes and people having these things and paper to mobile, now we've got AI. When you make good decisions, good things happen. When you make bad decisions, wrong inventory, wrong time, sales are down, there's operational burden. So if you make good decisions, you get the operational leverage benefits and you get the top-line, so that flywheel's connected. Can you give an example, Bianca, of where you're seeing some of this play out in your customer base? Because I think this is the phenomenon that I see as a key value extractor, because you get the proof points, one, in the operations, you see the revenue bump, you get some success. That's a cultural momentum movement for the company. Everyone goes, "Oh, I believe it now, I see it." A lot of people don't believe it until they see it. There's a lot of that confidence in the market now, where people have been enthusiastic, but they're like, not skeptical, but they're like, "Show me the proof." Execution risk is more the issue, not strategy. What are some examples where this decision intelligence plays out?
Bianca Anghelina
>> Yeah, totally. So I think I'm coming back to the example of the inventory allocation agent, where the results are visible with the launch, for example, of a new collection. What in the past was done with a lot of Excels and uncertainty, now, with the agents, companies have a much better way to actually understand all their past collections and launches which they had, independently of the field of retail, and get to a much better, much more accurate initial allocation of products across their shops, regions, countries. So that's something which is then visible immediately in the first sell-through month, let's say, of a new campaign. Now, the beauty and the efficiency of those agents is they continue to learn, and it's the same set of agents which propose the initial allocation which will then continue in real-time to optimize by seeing what is happening in real-time day-by-day in the different shops or on the shelves.
John Furrier
>> Supply chain to the experience, all in between, everything's there.
Bianca Anghelina
>> Exactly. And I think that the other part, to link it now to another agent which we see coming more and more to the front-line employees, is really an agent for supporting the shop managers, where, on one side, they get much more real-time insights on how to allocate their resources on the ground, to really make sure that they cover all the demand they have. But through agents, they also have the possibility to give some of these signals from the shop floor back into the agent which is optimizing the supply. So the beauty, I think, of agents is really the orchestration and connecting now the front-line employees with basically all the operations in the background, as well as with the strategic optimization, back to the top-line impact which this can generate.
John Furrier
>> Well, I really appreciate you taking the time to come on our Trailblazer series. You're blazing the trails, you're on the front-end of it. The autonomous story is going to be real, it's playing out in real-time in front of us. Really appreciate that. I have to ask you, as a founder, what's the origination story? Did you wake up one day and say, "Hey, I'm going to go build agents." What was the motivation? What was the origination idea? What was the story?
Bianca Anghelina
>> Yeah. Thank you so much for having me first, and thanks for the question around the origin. I worked in corporate across different industries, pharma, as well as automotive and banking, and I was experiencing firsthand exactly this topic of slow decision-making, and how important the speed of getting from data to insights and really act can actually change the trajectory of the business. And I've basically implemented AI for my own function and realized the impact very quickly, which inspired me to really found Aily and prove that AI at scale is possible and can be delivered in a what we call easy-to-use app.
John Furrier
>> Well, we love what you do, we appreciate it. And again, agents, I call it the middleware layer, because it's software, but it's really going to have the value of taking advantage of the AI infrastructure that is continuing to accelerate. We've got supercomputing capabilities, we're going to have more compute options, more software, all the memory that's coming online. And then, as these agents come in, it's going to open up full convergence of our lives, physical, digital, all one thing. Whether you're buying something with a cryptocurrency wallet or shopping online, commerce will be completely reinvented. Bianca, thank you so much for taking the time.
Bianca Anghelina
>> Thank you so much, John.
John Furrier
>> We'll keep in touch. Definitely loved having you part of the network. I'm John Furrier, host of theCUBE. We are here at the New York Stock Exchange, again, the Retail AI Leadership series. The trailblazers are making it happen. These are the people who are starting companies, affecting change, making news and creating innovation. As the world changes, as AI changes our lives, it's going to change all the experiences that go along with it in every vertical. We're doing our part to bring that to you. Thanks for watching.
John Furrier