You’ve likely never heard of a take like Kim Vu’s on secondhand clothes: They can help create identity and belonging.
It’s a perspective she gained as a child sorting through church-donated bags of used clothing her mom, an ESL teacher, brought back home for the community.
“I learned the value of secondhand clothes really early on,” said Vu, the daughter of Vietnam War refugees who immigrated to Amarillo, Texas in the 1970s.
She went on to scale financial companies, including as former Seattle market president of Bank of America and ESG leader at Remitly. Still, the love for stylish, gently-used clothing remained.
Four decades later, she parlayed it into founding StyleOrigin, an AI-powered company for vintage, thrift and consignment shops.
The technology aims to solve a problem that’s long plagued the secondhand clothing market: The time and labor-intensive process of listing a garment that’s often one of a kind.
She kept encountering the issue while selling vintage clothes through a friend’s resale shop, after leaving Remitly at the end of 2023.
It takes an average of 45 minutes per secondhand garment to figure out how to price, write a product description and list it, said Vu. That’s a significant barrier for any small business. Most have between 2,000 to over 5,000 items to process, she said, which can make it almost cost prohibitive.
Vu also saw a sustainability opportunity. Speeding up listings would save more garments from prematurely contributing to the 92 million tons of clothing that ends up in the landfill every year.
Problem identified, now it was time to build a solution.
Seeing AI used for other pattern-recognition tasks, she became curious about how to use it to build her resale clothing technology database. The only problem? She had never coded before.
It didn’t deter her.
In the fall of 2025, she began “vibe-coding” her model, or using large language models to code her technology, without needing to write her own. What began as “tinkering and learning on Youtube university,” started shaping up as a viable prototype within a few months.
Vu built in analog, in tandem. She traveled extensively around the country to meet and talk to resellers — potential customers — all of which informed the offering and generated interest.
“AI has leveled the playing field for non-technical founders and made it much easier to test an idea without making a huge financial investment upfront,” she said. She urges more women considering entrepreneurship to be open to iterating and testing an idea to get to a minimum viable product. All while talking to customers simultaneously.
How it works: Snap a photo of the garment and upload to StyleOrigin’s platform. It identifies the brand, time period, fabric and condition, while pulling real price comparisons and writing a ready-to-post listing. What took 45 minutes now takes under 30 seconds.
Vu is now actively fundraising a pre-seed round. She’s already got nine vintage thrift and consignment stores signed up as pilot customers and 70 more businesses waitlisted.
Her advice to other middle-aged — her words, not mine — founders on fundraising?
“Leverage everything you have learned, every relationship that you've built, all of that is gold to build your credibility.”
Vu’s entrepreneurial story might be uniquely her own. But here’s a data point on her side: A 50-year-old startup founder is 1.8 to 2 times more likely to build a top-growth or successful exit company than a 30-year-old founder.
