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Picture this: You upload an image of a T-shirt to a software program, and within seconds it generates a detailed product description covering the size, brand, materials, condition and other key features – and uses search engine optimization (SEO) to help get that T-shirt into an online shopping cart.

That’s what Athiya Rastogi has built with that uses AI to generate product descriptions from images, helping second-hand clothing stores make a name for themselves in the online marketplace.

“As long as the human eye can see a product’s feature, the AI can see it. Doesn’t matter if it’s a low-quality photo or there’s a busy background,” says Rastogi, who graduated from the ���߲ݴ�ý Scarborough with an honours bachelor of science in statistics.

Rastogi built the AI technology with her brother and co-founder Aryaman after taking courses in machine learning. She initially grew the startup out of .

SnapWrite has since enjoyed success in pitch competitions including at The Hub and , another campus-linked accelerator of U of T Scarborough, winning around $40,000 in funding without having to give up equity. The startup has also attracted funding from big-league investors including FounderFuel, Inovia Capital and Panache Ventures.

Rastogi says the idea for SnapWrite emerged from a business she operated when she was a student. “While in school, I ran my own resale store and met a woman who ran a pre-loved clothing store,” she says. “When I looked her up on Instagram, there was this endless feed of other accounts that were doing the same thing. This is a market with challenges that have not been fully addressed yet.”

Rastogi explains that demand for second-hand clothing is exploding, but because each pre-owned product is unique, online postings made to sell them must be too – which poses a challenge for businesses trying to keep up with growing inventory.

SnapWrite helps these businesses save on time and labour by enabling them to upload hundreds of photos at once, with the platform giving each item a detailed digital identity in about 15 seconds – a task Rastogi says would take a human worker five to 15 minutes.

What’s more, SnapWrite also integrates with major web platforms such as Shopify, Wix and Magento to automatically sync clothes’ attributes with websites, so that garments can be posted automatically and appear in the right place when shoppers are suggested similar products.

These features have earned SnapWrite a client base of around 50 resellers and counting, including one that has more than 35 stores. The software has digitized 25,000 items and generated more than 700,000 product attributes, saving its users upwards of 6,000 hours, according to the company. 

The startup has also managed to rope clothing brands into the second-hand cycle through an initiative in which partner brands ask customers to bring used products back to their stores. These items are then run through the AI and offered to second-hand stores to resell. This model has already saved 25,000 pieces of clothing from ending up in landfills, says Rastogi.

SnapWrite’s AI generates a unique inventory number, which Rastogi envisions could enable a digital passport system of sorts for used clothing. For example, a T-shirt may get digitized by SnapWrite, sold by a thrift store, and then re-donated months later to another second-hand store that also uses SnapWrite – or uploaded to the startup's consignment platform. Even more time would be saved should the AI recognize the shirt and be able to pull up its data.

Having identified a need in the clothing market, Rastogi says she and her brother are now focused on keeping SnapWrite's momentum going. “There’s no software in the Canadian market solving this problem in the resale market right now, so we decided to do it.”