June 22, 2024
Apparel, Fashion, Retail

Navan Unveils Fashiontech Platform Using Power Of Generative AI

Navan AI, a generative AI and computer vision solutions company has launched its FashionTech platform niia.ai, after a successful months-long trial run with a selection of fashion brands in Singapore and India.

Using the power of generative AI, niia.ai delivers significant time and cost savings to apparel designers, while complementing their creativity and enabling them to explore and experiment with various options.

“A typical 10-step process from ideation to market that can take weeks can now be executed in half the number of steps in a matter of hours,” the Singapore headquartered company said in a press release.

With niia.ai, designers will be able to create design variations or entirely new designs by simply describing their ideas.

The visualisation feature lets them get a 360® view of the product and generate photo shoot-quality images.

Eliminating the need to sample a design by actually printing it on a piece of fabric not only saves money, but also more importantly cuts waste and makes apparel design more sustainable.

“We are excited to roll out niia.ai for anyone involved in apparel and fashion design, from individual and boutique designers to large apparel brands,” Navan AI CEO Santosh Rout said.

“No longer do designers have to feel constrained by time and money to see their design ideas take shape,” Rout added.

“With our low-cost SaaS-model pricing, niia.ai is transformative and democratises apparel design, empowering fashion designers to give flight to their creativity with speed and efficiency,” he stated.

A couple of years ago, the Singapore Fashion Council had envisioned Singapore as a hub for the Asian fashion industry.

The emphasis was on technological innovation and sustainability, thereby differentiating itself from other cities renowned as ‘fashion centres’.

“I am optimistic and confident that niia.ai can play an important role in placing Singapore on the global fashion design map,” Rout observed

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