How we helped an Engineering Firm get a grip on Shadow AI — before it became a problem

This Engineering firm is a Singapore-based precision parts manufacturer supplying components to the aerospace and industrial equipment sectors. With around 120 staff across production, engineering, sales, and admin, they're a tight operation — everyone wears multiple hats, and moving quickly is part of how they stay competitive.

In mid-2024, the Managing Director noticed something: staff were openly using ChatGPT and other AI tools to draft quotes, summarise supplier emails, and write technical documents. No policy covered it. IT had no visibility into it. And some of what was being shared — client specs, pricing models, proprietary process details — wasn't meant to leave the building.

Nobody was being reckless. They were just getting things done. But the exposure was real, and their leadership knew it needed to be addressed before something went wrong.

When Uxible was brought in, we started with a one-week discovery phase — talking to the MD, the ops lead, the sales team, and several engineers. What we found was a pattern common in growing SMEs: AI had crept in organically because it was useful, and nobody had yet built a framework around it.

There was no malice and no major incident — yet. But the risk was real and accumulating quietly. The challenge wasn't to shut AI use down; it was to channel it into something the business could actually stand behind.

Our core design principle was the same as always: the sanctioned tool had to be genuinely more useful than the unsanctioned ones. A clunky internal system would be bypassed within a week. Something that made people's jobs easier — while keeping data safe — would stick.

For an SME like them, we also knew that simplicity mattered. There was no large IT team to manage a complex platform. Whatever we built had to be lightweight enough for the MD to understand and maintain going forward.

We designed and built AideBridge: a lightweight, private AI workspace deployed within their own cloud environment. Staff get access to the AI tools they actually need — quoting, technical writing, supplier research — without any of their data touching a public AI service.

The MD can see who's using it, what for, and flag anything that looks out of place. There's no IT team required to keep it running. And because it's built around their real workflows, staff actually prefer it to the tools they were using before.

AideBridge launched to their full team in Q4 2024. Within four weeks of rollout, the results were clear — both on the risk side and in day-to-day productivity. Staff adopted it readily because it was genuinely useful, not because they were told to.

SMEs face the same risks as large enterprises — with less buffer. A data incident or client complaint about mishandled information hits a 120-person business harder than it hits a multinational. The risk isn't smaller; the margin for error is.

Shadow AI in SMEs is more visible — and more fixable. In a smaller business, the MD often already has a sense of what's happening. The gap isn't awareness; it's having a practical solution that fits the scale and budget of the business. That's where Uxible comes in.

Staff don't resist governance — they resist friction. Every staff member at their organization was happy to switch to AideBridge once it proved more useful than what they were using before. The key was building around their real tasks, not around an IT policy document.

Lightweight doesn't mean less secure. We didn't need to overbuild. A well-architected, right-sized solution — private deployment, simple access controls, clear logging — delivered everything they needed without unnecessary complexity or ongoing cost.