Accelerating AI Impact with PX42 and UBIX

Charles Skamser

Happy New Year and welcome back to Inside PX42—it's Charles Skamser here, CEO of PX42, joined as always by Catherine Spenser, and today, we have Peter Caron with us. Peter is the VP of Data Science with our partner UBIX. UBIX is a pioneer at the intersection of Generative AI and Reinforcement Learning, driving business-led actionable insights and automation. Their patented no-code SaaS platform contextualizes and presents data from inside and outside the enterprise in minutes, not days, enabling complex AI and Machine Learning innovation. Getting past the marketing hype, I like tell our clients that UBIX is the only AI-driven decision-support solution on the market serious about democratizing data and AI by bringing the power of complex analytics to everyone. So, if you haven't heard of them, you need to listen up and take a look!

Peter Caron

Thanks for inviting me, Charles and Catherine. This is Peter Caron and It's a pleasure to be here to discuss how UBIX has enabled business leaders from the global 500 across all markets to create new business outcomes at scale in minutes, without the need for data scientists or application developers. And, more importantly, to talk more about how UBIX has evolved its platform to now support the no-code development of complex AI Agent solutions with Reinforcement Learning. We believe we are an emerging leader in driving the intelligent enterprise through Agentic AI and the right platform to make it happen for those organizations who just haven't been able to move from POC to production at scale.

Charles Skamser

Peter, we are excited to have UBIX as our partner and you on our podcast. So let's get started. Today, we will be dialing into a topic that's honestly on every enterprise leader's mind right now: how do you get past endless trials and finally see AI making a measurable difference on the ground? We've talked before—especially in our last episode—about system architecture, governance, all the things under the hood that really make agentic AI work in the real world. Today, we're zooming in on what happens when you bring all that together, pairing PX42’s AI-first consulting framework and methodology with UBIX’s industry-leading no-code, business-led AI Agent development platform. It's the toolkit for helping Global 500 clients leap from “interesting pilot” to “wow, this is in production and driving outcomes” in what, under one week in some cases?

Peter Caron

Yeah, and Charles, I think you nailed it. I mean, putting these two approaches together changes the game. UBIX has always been about that rapid bridge—from concept to ROI—removing those technical obstacles that usually slow everyone down. But it's the way PX42 designs and operationalizes the AI Agent vision, especially with big, multi-agent deployments, that gets me fired up. We're seeing folks in finance and retail—people who used to wait months just to approve a data pipeline—start to assemble, test, and iterate multi-agent solutions using the UBIX platform. And with the AI-first consulting overlay from the PX42 team to ensure it's all robust, governed, and aligned with business goals at scale, we have a partnership that can deliver exactly what the Global 500 needs to finally move Agentic AI projects from POC to production and start to realize transformational business outcomes at scale.

Catherine Spencer

This is Catherine. And what's so refreshing, Peter, is this isn't just another technology for the sake of it, is it? There’s always so much talk about “business-led AI”—to the point where it's, frankly, become a bit of a cliché. But seeing actual, business-driven outcomes, led by domain experts who don’t have a data science background—that’s another thing entirely. And Charles, I believe you had a recent story from that global retail client who ramped up their multi-agent initiative at lightning speed?

Charles Skamser

Oh, absolutely—I love this story because it really flips the usual script. This retailer came to PX42, stuck in POC limbo like so many, drowning in custom reporting tools, legacy data silos, you know how it goes. They’d been burned by “AI in a box” before, so there was some healthy skepticism. We walked in with the UBIX platform and our outcome-first methodology. In a matter of weeks—literally under 60 days—they’d assembled a multi-agent environment, each agent mapped to a clear business function: inventory optimization, real-time margin analysis, even dynamically recommending promotional campaigns as the data streams changed. What clinched it wasn’t just the speed, but the fact that business analysts—not just IT—could adapt and orchestrate these agents themselves. So, results were measurable—reduction in inventory waste, faster margin decisions—and governance was baked in from start to finish. It’s the sort of leap-frog that’s just not possible with siloed custom ML projects.

Peter Caron

Right, and that’s where the no-code side is so foundational. We’re not talking citizen data science as just a buzzword. We’re seeing everyday leaders—whether they’re in supply chain, ops, or finance—actually hands-on with agents, building and iterating on their own, but still within the operational safety nets you mentioned.

Catherine Spencer

It’s a complete mindshift. Because it goes beyond just technology—it’s a reimagining of who gets to participate in innovation. And Charles, your anecdote there is a vivid reminder: this is business-led AI, realized. Not theoretical—real, measurable business transformation.

Peter Caron

I’m just gonna pick up on that, because the democratization angle really is at the heart of what’s changed. Look at UBIX’s three pillars—no-code deployment, same-day onboarding, and the ability to unify data across all business functions. That’s the toolkit for digital transformation. I worked with an enterprise manufacturing client who had six or seven departments manually pulling together their data every month. Everything lived in spreadsheets, honestly, and reporting was always, I mean, outdated the moment you printed it. We came in with UBIX, plugged into their systems, and within hours—not weeks—they had a dynamic, self-service analytics environment. Suddenly, a line manager or a financial controller could launch their own reports or agents, gain predictive insights, and make decisions in real time, without requiring an IT ticket.

Charles Skamser

I love it, Peter, and I hear similar things in retail and financial services too. The funny thing is, most organizations think their technology is the main barrier when it's typically the people and the process. You know, we used to say, “AI is a team sport,” but what matters now is removing the bottleneck—letting business folks become active participants, not passive recipients of whatever comes out of an analytics team two weeks later. And part of how PX42 and UBIX do that is just by lowering the barrier to action. If you can ask a good question, you can run an agent or a workflow. No coding, no translation layer needed.

Catherine Spencer

And isn’t that such a critical turning point for enterprise AI adoption? As we highlighted in the last couple of episodes, the hard part isn’t building a pilot—it’s scaling out, right? Moving from “here’s a cool experiment” to “here’s an operational capability that everyone can use.” So, Peter, when you worked with that client, what challenges did you see with scaling from pilot to production? Was it all just resistance to change, or were there real technical hurdles too?

Peter Caron

That’s a great question. Honestly, it’s almost never just technical. I mean, yeah, there’s the legacy tech challenge—data silos, old ERP systems, all that. But the bigger challenge is change management. People are used to relying on IT or the analytics team. UBIX’s approach, by enabling same-day onboarding and instant integrations, sidesteps that whole “wait in line for resources” problem. And because it’s built to be plug-and-play, you really do cut down the dependency on specialized AI or data talent. That’s what moves the needle in real-world adoption.

Charles Skamser

It’s amazing how many cycles we waste on waiting for some centralized resource to get around to fitting our request. The old model just doesn’t fly anymore. If you want continuous innovation, the people closest to the problem need the tools in hand. And, as we keep saying—without sacrificing governance or trust. If you democratize access without controls, you just wind up with chaos; UBIX and PX42, together, strike that balance by letting business innovate inside clear, secure guardrails.

Catherine Spencer

That, for me, is the magic here: rapid deployment and real self-service, without compromising enterprise standards. Truly democratized AI, but with discipline. And it’s not just hype; as you said, Peter, when the manufacturing folks are out of their spreadsheets and into actual real-time analytics, the cultural change becomes as important as the technical one.

Charles Skamser

So let’s carry that thread forward: once you've democratized access and gotten everyone hands-on, the next challenge is serious operationalization. Catherine, I know this is a topic close to your heart—PX42’s Agent Factory Methodology, the ecosystem, all those pieces that make business-led innovation repeatable, secure, and scalable across, you know, the entire enterprise. Want to pull us into what that really looks like?

Catherine Spencer

Absolutely, Charles. I tend to say that innovation without governance is a recipe for panic, not progress. So, our Agent Factory Methodology and our wider PX42 technology ecosystem are all about embedding security, compliance, observability, and auditability from day one—not as an afterthought. When I advise CDOs, particularly in regulated industries, the first hurdle isn’t “can we build it?” It’s “how do we ensure every agent’s decision can be explained, traced, and aligned with policy?” I recently worked with a Chief Data Officer at a healthcare client who was, frankly, exhausted by one-off AI experiments. She'd seen models pop up, deliver some value, then disappear for lack of governance. With PX42’s playbooks, we mapped out a continuous value loop: every deployed agent could be audited, refined, and even retrained, while still operating within regulatory and ethical boundaries. It turned experiments into business assets. And honestly, that approach was shaped by hard lessons from my experience in the London financial sector, where compliance isn’t just a checklist—it’s business survival.

Peter Caron

That’s the part where a lot of agent-based projects fall over—they get to production, but then you lose track of what agents are doing or why they decided something. UBIX and PX42 together bring observability—so you've got dashboards, live audit trails, and explainability built into every workflow. I saw this in a recent enterprise deployment in manufacturing: the agents made a call on optimizing shift patterns, and because of the embedded governance, every step was logged, traceable, and could even be surfaced for review by an audit team. No hidden decisions, no compliance surprises.

Charles Skamser

And we shouldn’t overlook sector specifics, right? In finance, you’ve got to meet audit standards out of the gate; in healthcare, it’s patient privacy and traceability; in manufacturing, shift to safety compliance and uptime. PX42’s tech ecosystem isn’t one-size-fits-all. You get flexible delivery through our Agent Factory Methodology, but with modular governance baked in—so adoption scales without losing discipline. That persistent audit trail and robust feedback loop is what lets the value keep compounding instead of tapering off. It’s why, if you look at our client results, you’ll find ROI and, crucially, trust, keep improving quarter-on-quarter, rather than dropping off after the initial AI excitement fades.

Catherine Spencer

Exactly. It becomes a sustainable transformation, not a short-lived innovation theatre. If you build that repeatable, explainable loop—from strategy to execution to feedback—you create a self-correcting, continuously improving AI-powered enterprise. It’s what distinguishes the winners we’re seeing across sectors right now.

Peter Caron

Couldn’t agree more, Catherine. When you get operational discipline and business-led velocity together, that’s when AI stops being magic and starts being core infrastructure for continuous value creation.

Charles Skamser

Alright, well, we could talk about loops and playbooks all day, but I think that's a pretty solid wrap for this session. Thanks, Catherine and Peter, for sharing real stories—not just theory. And thanks to everyone listening for joining us as we explore how PX42 and UBIX are making the intelligent enterprise actually achievable. We’ll be back soon with more industry insights and practical lessons. Catherine, Peter—always a pleasure.

Catherine Spencer

Likewise, Charles. Take care, everyone—and don’t forget to include AI in your plans for 2026! In partnership with PX42 and UBIX, AI Agents can have an impressive impact on your business this year!

Peter Caron

Charles and Catherine. What a pleasure it was to be here today. Thanks for inviting me. Can't wait to come back and talk more about how PX42 and UBIX can help drive the Intelligent Enterprise with AI Agents.