By Mark Tullis | Posted - Feb 20th, 2024





Anagram Raises $1.2 Million Pre-Seed Investment from Nextview and Kickstart to Build Simple AI For Complicated Products

Anagram, an AI-powered product data platform for brands, announces its $1.2 million pre-seed financing led by Kickstart Fund (Salt Lake City) and NextView Ventures (San Francisco, Boston, New York).

Anagram’s mission is to make “simple AI for complicated products,” said Anagram Co-Founder Austin Winfield, an ecommerce veteran and BYU graduate who worked at Mercato Partners and then joined one of their portfolio companies, a sock supplier called Stance. Winfield observed several pain points around product data during his time at Stance and while running his own consumer products company, Period Correct, a supplier of nostalgic automotive merchandise for brands like McLaren Automotive, Lexus, Hot Wheels, and IWC Schaffhausen.

We sat down with two of Anagram’s co-founders, Austin Winfield (President, above center, and based in Salt Lake City) and Bryce DeFigueiredo (CEO, above left, and based in the Bay Area), to learn more about Anagram, what it does, and what led to its founding.  

Winfield said during his time working for socks and underwear e-commerce companies he started to see a common pain point around getting simple answers to different questions about different types of consumer products.

“You would be surprised at how hard it is to get accurate answers to product-related questions even internally at most brands said Winfield. 

He continued, “Product data for brands is still fragmented and overlooked, but brands are sitting on a data goldmine that we can help them uncover with AI. We founded Anagram to enable brands to find new meaning in their product data.”

Winfield teamed up with co-founders Bryce DeFigueiredo and Jeremy Fischer (CTO, above right, and based in Portland, OR), alumni of Utah’s Lucid Software, to pursue the dream of bringing simplicity to the world of product data. Winfield and DeFigueiredo met each other in Cambridge, MA while playing 6:00am basketball at the Harvard Business School gym. DeFigueiredo was attending HBS working on an MBA at the time, as was Winfield’s wife.

At the time it seemed everyone in business school was obsessed with cryptocurrency, recalls Winfield. “While everyone at HBS was talking about crypto, Bryce, instead, was focused on AI and large language models, having gotten early access to OpenAI’s API before it was generally noticed by most people. I had a lot of data from running consumer products companies. Bryce knew a lot about large language models, so we started putting the data to work with some of these large language models to see what we could do. We quickly figured out there was a lot of powerful stuff we could do with consumer product data. It is highly fragmented and disorganized. And it is missing a lot of important information that brands need, most of it very obvious and simple things like compatibility with other products and applicability for certain types of weather.”

DeFigueiredo led a team at Lucid that built the company’s first AI personalization recommendation engine. At Lucid he connected with Jeremy Fischer who also worked on Lucid’s early AI large language model features. Together, the three co-founders created Anagram, a startup that helps brands easily aggregate their product data from both obvious and overlooked data sources. Anagram’s dream customers are consumer product companies selling “high consideration products, i.e. products like snowboards or ebikes that may or may not be very expensive, but typically involve considerable research by the potential buyer. Using the latest LLM technology, Anagram allows both internal users and online shoppers to get instant answers and hyper-personalized product recommendations.

Winfield said “We believe in giving merchants the power to create the exact experience they want to give to their customers, using the merchant’s own documentation and regardless of the customer’s location, age, sex, or other attributes. A customer in Dallas will probably have very different questions than that of the customer in LA. We’re really dialing in that brand voice and giving merchants a persona of each customer.”

DeFigueiredo said “the latest wave of generative AI is opening a whole new world of opportunity for consumer products companies. Early on, we asked ourselves, what if we could help brands develop better products, increase shopper engagement, or even reduce customer support tickets? With Anagram we’re finding the combination of product data and AI can do all of this and more.”

He continued, “It's pretty transparent and obvious to the users that they're talking to an AI; we’re not trying to make them think they're talking to a human being. But we also want to make it fun and engaging.”

The company has already onboarded over a dozen brands to its platform including St. George, Utah-based electric bike supplier, Amped Bikes. Amped’s head of ecommerce, Jeff Rogan said, “We sell technical products and want to make sure our customers get exactly what they are looking for. Anagram helps us get them answers and gives us insight into the kind of info they are searching for. It’s becoming an important piece of our customer journey.”

NextView’s David Beisel knows this world well, having invested in a variety of successful commerce companies, including hyper-personalized SMS and email company, Attentive (San Francisco, New York, London and Sydney). He understood the opportunity instantly while chatting with Austin and Bryce. 

“At NextView, we are convinced that generative AI represents a pivotal shift in the way brands can develop products, go to market, and engage with customers. This transformative journey is deeply rooted in data, and we find Anagram's innovative approach to leveraging it is particularly compelling."

Anagram’s customers are seeing several benefits from integrating Anagram’s AI into their product pages, according to Winfield. “Our merchants are seeing higher engagement on their product description page, which means people are spending more time on the product description page. And they're not leaving to go ask Google the answer to the question they couldn’t find on the product page. They're staying on the page.” 

He added, “Merchants are seeing fewer support tickets because shoppers are getting the answer they are asking. But ultimately, merchants are reporting better conversion rates because their buyers know they're getting the product they're actually looking for. Buyers feel more confident in making the purchase decision because they have gotten answers to all of their questions before making the purchase.”

To learn more visit the company's website

Mark Tullis
About the Author

Mark Tullis - Mark is Co-founder and Editor of TechBuzz News. Born and raised in Ogden, Utah, Mark attended Weber State, Brigham Young, and Tufts Universities. He has been involved in tech, media, publishing and education since the 1980s. He enjoys spending time with his family, hiking, and playing the saxophone.



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