Both Lance Riedel and Nigel Daley spent many years discovering search engines, but it wasn’t until they worked at Pinterest to launch Pinterest Shopping that they began to know how search engines could perform personalized searches when shopping online.
Most people expect online shopping to be a matter of entering a keyword and then expecting a search engine like Google to do its job and return a rating result.
But the biggest magic they learned on Pinterest was using large language models and artificial intelligence to discover images to reverse the script to tailor results not only to a keyword but also to a person’s previous actions, Riedel told TechCrunch.
The more often a person interacts with one of these search engine, the higher he gets to know his preferences, the higher his shopping results.
They left Pinterest and began Vantage’s discovery in 2023, offering this search engine to brands that do not have the resources or expertise to pursue LLM and other types of AI on their very own.
For example, a buyer who has had exposure to BoHo clothing in the past will get a very different result than a buyer who has had exposure to streetwear in the past when searching for something like “a dress for a fun night out.”
But Vantage goes a step further with image recognition. The buyer can even use their search engine and ask: show me more products like this to point out the consumer related products. The search engine can even use a person’s Pinterest profile to generate personalized shopping recommendations based on the items pinned on their board.
“At the core of our engine is a custom vector database where we combine both a semantic understanding of the user’s query and a semantic understanding of the user’s personal style to produce the most personalized and targeted results in milliseconds for millions of items,” Riedel said.
As with most commerce-focused search engines, the rating of results will be controlled by Vantage’s customer, which is the retailer or brand. “We can also re-rank results based on a custom model tailored to optimize our clients’ business metrics.”
The startup was founded in early 2024 and works with clients including Cooklist, Koodos, West.co and Bookopolis. Daley declined to offer exact revenue numbers, but said the company generates revenue and also “partners with one of the largest retailers in the world.”
Vantage Discovery has caught the attention of Twitter co-founder Biz Stone, who is participating in a recent $16 million Series A round. And now he is a member of the board. This follows an unannounced $4 million seed fund the company raised last 12 months from Stone and Evan Sharp, co-founders of Pinterest.
“One of his other investments required an intelligence platform that would support RAG, search and novel discovery capabilities,” Riedel said. RAG is search augmented generation, a natural language processing technique that mixes search and generative artificial intelligence models. “Biz was so impressed that they invested in our seed round.”
The financing round was led by Lobby Capital and also included participation from LoveFrom’s Jony Ive, former Apple chief design officer, in addition to Sharp, The Hive, Future Positive and Common Metal. In addition to Stone, David Hornik of Lobby Capital, who has invested in corporations similar to Gitlab, Bill.com and Evite, will join Vantage Discovery’s board.
Meanwhile, Riedel and Daley said they are also interested in delving deeper into what they call “commodity tools,” which is how online stores or search engines rank results. They need to add a touch of artificial intelligence to it.
“It’s a space that’s been around for a long time, with marketers putting their thumb on the search scale and influencing it in a certain way,” Riedel said. “It’s important and necessary for retailers, but we think we can eliminate some of that hard work.”