Share:

Building for Uncertainty: Stefan Groschupf on Reimagining Supply Chain AI at Manifest 2026

A Legacy Behind the Mission

At Manifest 2026 in Las Vegas, Scott Luton sat down with Stefan Groschupf, CEO & Founder of Centrum AI, to discuss how a new generation of technology is being purpose-built for today’s supply chain realities, rather than  yesterday’s assumptions.

What began with a lighthearted joke about multivitamins quickly turned personal. When Scott quipped that “Centrum” reminded him of a vitamin from the eighties and nineties, Stefan shared the real inspiration behind the name. “My dad… the biggest building he constructed was called Centrum,” he explained. “That was the inspiration. His legacy, a head nod to him.”

For Stefan, the company name represents more than branding; it reflects a mission rooted in impact and responsibility.

 

Designing for Today’s Reality

“We’re building a new tech platform for the supply chain industry that is really built on the foundation of the reality today,” Stefan said. That reality includes uncertainty, dirty data, data silos, and geopolitical shifts that are reshaping global trade.

He offered a simple example: in many ERP systems, a lead time is entered as a fixed number — say 15 days. “That’s of course nonsense,” Stefan noted. “It’s anywhere between nine days and 18 days… and if it’s 18 days, it may change on Monday.” Yet companies continue to optimize inventory and production based on static assumptions.

Centrum AI takes a different approach. “We take uncertainty as a foundational element,” Stefan explained. Instead of relying on fixed attributes, the platform works with probabilities, reflecting how supply chains actually behave.

 

From Wall Street to the Warehouse

Stefan’s background spans more than two decades in machine learning and big data. His teams previously built risk models that powered “80% of all North American financial transactions” and supported algorithmic trading systems making multi-billion-dollar decisions.

“A lot of the things we did to make multi-billion dollar decisions in the stock market actually really perfectly apply to supply chain,” he said. If financial markets can compute uncertainty in real time, supply networks can as well.

 

2026: The Era of Compounding Uncertainty

When asked about dominant themes shaping 2026, Stefan was direct: “The big theme that everybody has to solve for is uncertainty. And the uncertainties will only increase.”

Geopolitical realignment, shifting trade blocs, labor shortages, and accelerating technological change are redrawing supply networks. But Stefan cautioned that AI is not just a technology challenge. “AI is more a human adoption problem. Change management is the top problem.”

He also pointed to the rise of physical AI, such as robotics and automation, as essential in a world where reshoring meets workforce constraints. “You don’t want to be at the same spot in five years… as you are right now with ‘all my data is dirty and I’m trying to get AI to work.’”

 

Seeing the Supply Chain as an Organism

Centrum AI’s broader ambition is to help leaders see beyond surface-level metrics. Stefan described a foundational model that understands the global flow of materials and how it truly represents a living, breathing “organism.”

By analyzing upstream signals, the system can anticipate downstream demand shifts. The platform can run “tens of thousands of simulations on a daily basis,” consuming “20 billion supply chain records globally.”

The outcome is precise inventory optimization. Rather than spreading “15% safety stock like a peanut butter spread on everything,” companies can reduce stock for low-risk SKUs while increasing it for high-risk ones, freeing working capital while maintaining service.

As Scott confirmed, the immense value is to help leaders “see far deeper, far further, and around corners” – – and enable them to make the best decisions possible.

 

A Can-Do Industry

Reflecting on Manifest 2026, Stefan expressed optimism. “People are excited to solve some of these problems,” he said. “I’ve seen a very positive ‘can-do, will-do, we need to figure this out now’ attitude.”

In an era defined by volatility, that mindset, combined with uncertainty-first, probabilistic technology, may be the defining advantage for the next generation of supply chain leaders.

 

Where to Learn More

Connect with Stefan Groschupf on LinkedIn here; and be sure to follow Centrum AI on LinkedIn here. For more information, check out the company website here: https://www.centrum-ai.com/

More Blogs

global supply chain
Blogs
February 3, 2026

The Value of a Data-Driven Approach to Demand Sensing and Forecasting

Special Guest Blog Post written by Chris Cunnane with InterSystems   Demand sensing and demand forecasting are both crucial aspects of optimizing supply chains, but they do have slightly different functions in their approach and focus. Demand sensing uses real-time data and analytics to identify and respond to immediate demand fluctuations, while demand forecasting uses historical data to predict future demand over a longer period (months or years). Different methods, such as statistical modeling and machine learning, are used to enhance the accuracy and adaptability of these processes. Both areas are crucial for companies when it comes to projecting sales, managing inventory, and coordinating replenishment. In the end, the goal is to accurately predict customer demand by using predictive models to forecast future demand. InterSystems surveyed 450 senior supply chain practitioners and stakeholders to examine key supply chain technology challenges, trends, and decision-making strategies across five key use cases: fulfillment optimization; demand sensing and forecasting; supply chain orchestration; production planning optimization; and environmental, social, and governance (ESG). This blog focuses on demand sensing and forecasting.   Current State of Demand Sensing and Forecasting According to the survey results, when asked how they currently forecast demand, 36% of respondents indicated that…
driver safety
Blogs
June 5, 2026

When Safety Technologies Backfire and How Managers Can Prevent It

Brought to you in partnership with the Journal of Business Logistics   Companies are investing heavily in safety technology. Trucking fleets now rely on cameras, collision warnings, lane alerts, adaptive cruise control, and automated braking to reduce crashes and protect drivers. That investment assumes a straightforward outcome. More technology should lead to safer behavior. It does not always work that way. Research in the Journal of Business Logistics shows that the same technologies designed to improve safety can also undermine it. The difference comes down to how drivers experience the tools and how managers use them. The problem is not the system. It is the interaction around it.   How safety technology fails in practice The study points to two common patterns that show up across fleets. The first is avoidance. Some drivers ignore or disable alerts. They cover inward-facing cameras or override automated features. This behavior shows up when the system feels intrusive or disconnected from real driving conditions. Frequent warnings and false alarms create frustration. Experienced drivers, in particular, may feel the technology challenges their judgment rather than supports it. When that happens, drivers do not adapt to the system. They route around it. The second pattern is…