“There has to be a better way.”

That was what Md Ridwan Hossain kept thinking after seeing the same scene repeated across garment factories: workers hunched over rolls of fabric, scanning for defects under harsh lights. A process that is slow, exhausting, and still misses most flaws in the fabrics.
threadBridge starts from that reality. It uses AI-powered smart glasses to help workers detect defects in real time, turning a manual process into one that is faster, data-driven, and less physically demanding.

The innovation is designed to work with people, not replace them, enhancing workers’ capabilities to improve both quality and working conditions.

Fabric inspection is one of the least visible steps in garment production, but its impact is significant. In many factories, only around a few percent of incoming fabric is checked manually. The rest moves directly into cutting and production.

When defects are discovered later, the damage is already done. Fabric cannot be uncut. The result is wasted material, lost value, and unnecessary environmental impact – all originating from a step that has remained largely unchanged.

For many, the obvious solution would be to rely on machine-driven automation.
threadBridge starts from a different premise: supporting workers rather than replacing them.

The innovation combines AI-powered smart glasses with a connected device to transform how fabric inspection works. The glasses, that are worn by quality control workers during inspection, detect flaws in real time and alert the wearer. In the meantime, the device measures each issue and generates a digital report automatically, turning what was once a manual check into a continuous stream of reliable data.

What changes is not just the process, but the experience of doing the job. Instead of straining to catch every defect, workers are supported in real time, making inspection more accurate and less physically demanding.

“I am from Bangladesh,” says Ridwan. “The textile industry is the backbone of our economy, it employs millions of people. When I was on those factory floors, I didn’t see an abstract business problem. I saw our industry being held back by a process that nobody had bothered to modernize. I saw workers straining their eyes for hours, doing a job that technology could make easier and better.”

In addition to supporting workers, there are also clear environmental gains. Every meter of fabric carries a cost – in water, energy, and resources. When defects are discovered too late, those resources are wasted.

By identifying issues before cutting, threadBridge prevents that waste at its source. Materials that would otherwise be lost can be removed earlier, reducing the amount of fabric that enters production with hidden flaws. The result is not only better quality, but less waste across the system.

For factory owners, this also means fewer losses, more consistent output, and better visibility over material quality before it reaches the cutting stage.

By starting with how people actually work – and building technology around that reality – threadBridge shows how innovation can begin to improve both systems and the way people work within them.

“This is personal to me because fixing this problem does not just save fabric, it strengthens the industry that supports my country,” says Ridwan. “I have the engineering skills to solve it, and I feel a responsibility to do so.”