Making the Complex, Simple: Sunny Han on ERP, AI, and the Human Side of Manufacturing

At FABTECH 2025, David Lechleitner of LevelUp Consulting invited Fulcrum CEO Sunny Han to join as a guest speaker during his talk: “Making the Complex, Simple: The Impact of ERP UI, UX, and AI on Your Employees' Work Satisfaction.” The session quickly turned into an open Q&A that revealed how Fulcrum is rethinking the role of ERP in manufacturing.

The questions circled around a few major themes that manufacturers everywhere are wrestling with: where to invest in AI, how to design software people actually want to use, and how to bridge generational differences on the shop floor. Sunny’s answers reflected Fulcrum’s philosophy: focus on what truly drives throughput, even if it isn’t flashy.

Throughput as the North Star

Fulcrum’s guiding principle is simple: help manufacturers make more with the same people and machines. As Sunny put it, “your machines are the mechanical muscles of your shop, and Fulcrum is the mechanical mind.”

That mindset drives how Fulcrum decides where to invest. The priority isn’t on eye-catching features that look good in a demo but don’t change much on the floor. Instead, the focus is on deceptively simple tools that eliminate bottlenecks. 

For example, Fulcrum is working on tools that automatically scan emails for order details and feed them into the system, making information instantly available to the rest of the shop. The same principle applies to document automation in development — first article inspections, certificates of conformance, and reports can all be generated instantly from customer templates.

“These things don’t sound super cool,” Sunny noted, “but they free people from the low-value work that eats up hours every week. That’s what drives throughput.”

On average, shops running Fulcrum see a 35-40% increase in throughput after implementation — same machines, same people, just better coordination and less time spent on paperwork, double-checking, or chasing information across multiple systems.

Design That Earns Engagement

ERP adoption lives or dies by user experience. Sunny shared how his early career implementing legacy systems revealed a troubling trend: as interfaces became harder to use, operators entered less data, and ERP systems wasted away as silos. Fulcrum’s counter-approach has been to invest 4x more in design than the industry norm, ensuring operators gain immediate value each time they enter data.

One example: when an operator enters a checkpoint in Fulcrum’s Job Tracker, the system immediately flags if it’s out of tolerance and (soon) will highlight it on the drawing. Instead of a note disappearing into a stack of paper, the operator gets instant feedback. Interactions like these build trust and keep data flowing into the system instead of spreadsheets or side notes. That usability keeps data density high, enabling advanced AI, automation, and reporting.

Bridging Generations on the Shop Floor

The Q&A also highlighted the challenge of serving a multigenerational workforce. Sunny described it as a kind of social contract. For veteran machinists, Fulcrum promises to capture their knowledge and reduce paperwork so they can focus on their craft. For younger employees, the priority is intuitive, real-time tools that feel familiar — simple search bars, mobile-friendly screens, and live updates.

The balance, Sunny noted, is less about age and more about shop culture: successful adoption happens where companies see employees as assets to be empowered, not just resources to be managed.

Unlocking AI in Manufacturing

While Fulcrum processes billions in orders annually, Sunny pointed out that the industry is still scratching the surface: “We estimate we only have about 8% of the necessary data to do the really cool stuff.” 

Data Density

Each year, an estimated 1.9 billion drawings are created, revised, and reproduced. Yet only 0.000001% of them are public and available to train AI models — nowhere near enough to build reliable systems. Without access to real data, models hallucinate. And training on drawings alone doesn’t work. Shops uniquely know how to make parts, whether that means a job goes flawlessly or ends up as scrap. Both outcomes are essential for training useful AI.

Even more knowledge is buried in spreadsheets, Word docs, and years of email threads between customers and engineers. As Sunny noted, simple small details — like how a bend line gets discussed with a customer — often carry decades of hard-earned tribal knowledge. This type of unstructured data is not only missed by ERP systems, but is a complete blind spot for today’s models relying on publicly available data.

“As we increase that density,” Sunny explained, “we can do cool AI stuff, we can do cool reporting stuff, we can do cool automation.”

The Danger of Customization

Most ERP systems compound the problem. Heavy customization leaves datasets inconsistent and scattered across custom fields and siloed modules. Adoption is often so low that critical information dies on paper or lives in isolated spreadsheets, inaccessible to any model.

Customization may let a manufacturer mold ERP to its process, but the trade-off is an island of data with no harmony — no patterns of actions, reactions, iterations, or decisions for AI to learn from. For AI to work in manufacturing, data structure harmony is essential.

What Comes Next

The next leap requires anonymized proprietary data — CAD models, work instructions, production results — combined with AI to deliver breakthroughs in scheduling, supply chain, and design efficiency.

That’s why Fulcrum is focused on making data entry easy, consistent, and cleanly structured today. It’s the foundation for what will become Fulcrum Intelligence tomorrow.