raises $17 million to give e-commerce sites Amazon-level product recommendation muscle – TechCrunch

Amazon rules the roost in e-commerce, not only because of its size, but also because of the way it uses it to amass vast amounts of information which it in turn uses to continue to power the machine with sophisticated product recommendations, relevant advertisements, and more. for people to find things to buy and buy them. Today, a Stockholm-based startup called that has also built a product recommendation tool — which it says can help any retailer sell like Amazon — is announcing $17 million in funding to power its own growth in the United States and Europe, having chosen up to 60 customers, including Office Depot and Staples.

Series A is led by Tiger Global, along with Initialized Capital, EQT Ventures, Y Combinator and a long list of top angels. It follows a $2.8 million seed funding round the company raised last year from Initialized, EQT Ventures, Northzone and Y Combinator, where was part of the first cohort to follow the program during a Covid-19 lockdown.

As CEO Oliver Edholm (who co-founded the company with CTO Anton Osika) describes, the basic premise of is that Amazon’s algorithms work so well because they have so much data on their platform. shape what you and people like you are buying. On a platform with millions of products, this gives Amazon the power to determine what to show you, as well as what to stock and expand as product categories, and how to price these products. It’s a paradigm most other retailers have embraced as well, he said.

“It’s the same system that everyone has adopted, but they usually only look at their own historical data,” said Endholm, who will never be as extensive as the data set Amazon has, and does not provide no more asset information. purchases.’s solution was to amass a much larger trove of information by aggregating data from the internet; build its own deep learning-based platform to “read” it in a relevant way (e.g. in a search for recommendations after someone searches for a dress, identifying data that relates to other dresses, rather than models that resemble the model in a customer’s initial search); then ordering it according to the research carried out on the sites of its customers, to produce relevant recommendations.

It amasses the data initially by scraping a wide range of sites on the web, Edholm tells me. Scraping has had its share of controversy – a number of sites go to great lengths to make it difficult or ban it outright, and some have gone so far as to take legal action against those who scrape – but Edholm notes that it’s not is not illegal and is in fact a fairly common practice in the trading world.

“We train on loads of data pulled from the web, but a lot of models do that,” he said. “You can learn very good abstractions.”

And, in any case, scrapes such a wide range of sites that even if one or two or 10 blocked it, there would still be a huge treasure to be mined, and has already amassed a huge amount of data . .

“We don’t rely on any specific site like LInkedIn or Craigslist,” he said, referring to two platforms that have largely been taken down over the years for primary data that is repurposed by others. “We usually want to find a lot of information about e-commerce products and there are lots of ways to do that, so I don’t worry about blockages. dataset if we need it.”

The recommendation engine can then be integrated into the backends of its customers via an API. He claims his technology can increase customers’ e-commerce revenue by 4% to 6% “without needing any sales data at all.”

Catch Edholm if you can

Edholm’s ingenuity and willingness to quickly change the means of achieving Depict’s goals is a trait that is actually an integral part of the person himself.

A computer whiz, Edholm is a self-taught programmer who first got interested in coding after creating custom Minecraft experiences when he was 12 years old. He then moved on to creating mobile apps after realizing that they also used Java, like Minecraft.

After finishing middle school, Edholm quit formal education and turned to home schooling (he credited his parents many times for being “super open-minded” during our interview; my boy , are they). He first came up with the idea for while working as a data scientist at Klarna, the Buy Now, Pay Later e-commerce powerhouse, also based in Stockholm, where he started working there. that he was only 15 years old. (Klarna had to pull a lot of strings to get him working there, he said, and he describes his work there possibly because of that as “consulting.”)

There, he became obsessed with artificial intelligence.

“What was very clear is that modern machine learning needs tons of data to work well,” he said. “When you think you’ve had enough, even more is better. That’s how modern machine learning works. But in e-commerce, Amazon has a monopoly on data. e-commerce doesn’t have the same alternatives, they lack the amount of data of an Amazon.

But between noticing and understanding (using AI) how to bridge that gap between Amazon and the rest of the commerce world when it comes to product data, and actually starting to make it a business, Edholm took another detour.

When he was 16, he had saved enough money from his job at Klarna and selling apps in the App Store, and he got up and bought a ticket to Singapore, where he decided he had to live to create a different startup: an AI-based startup. accessibility platform for the web, to help people with visual impairments to discover the Internet.

Singapore was in his sights, he said, because he had read some accessibility research papers published by academics in the country on the subject, so he thought it would be best to be on the land there to build his ideas.

“I was very naive. I was inspired by the movie Catch Me If You Can,” he said. “I understand it was dramatic for my parents. I guess I’m used to booking spontaneous flights. (In fact, my interview with him was conducted when he was not in Stockholm, but in Antwerp, Belgium – where he had spontaneously flown off that morning to try and woo a potential recruit he really wanted to join the team.)

He stayed in Singapore for six months on a short-term visa to work on the idea, funding his time there by doing more consultancy work. Eventually he realized that it would be a huge challenge to grow this as a business. (Indeed, I think these products probably have value, but perhaps more as a platform than as accessibility as a service for end users.)

So, for a plan B, he also applied to join Y Combinator, now to work on, which had not yet launched. By the time he got a slot for an interview, he had returned to Stockholm, but hadn’t told YC about it, so he actually had to fly back to Asia, to Bangalore, for the in-person meeting before he was finally accepted, only to follow the program remotely because of Covid-19.

Since the start of, Edholm’s own star as an individual and founder of fame has only gone up: no surprise here, but he’s also now a Thiel Fellow.

Edholm is now only 19, and reading what he’s done so far, it’s hard to imagine him sitting still for too long, but with still under construction, there’s still a lot potential to exploit. For starters, it can attract more customers. It can also diversify the use of its data, both to serve e-commerce businesses, but also by applying this same framework to other verticals.

In that regard, it’s interesting to see an investor like Tiger leading this round. VC is increasingly appearing in smaller, earlier stages of funding – unlike its early and perhaps most high-profile investments where it sinks hundreds of millions into already large-scale ventures. The idea here is that Tiger himself learns more and wants to enter the field to get better returns on bets he thinks are good. In this case, this could just as well apply to support for as support for Edholm itself.

“’s AI-powered product recommendation platform is completely new as it does not require historical sales data, enables online retailers of any size to provide high-quality recommendations, a key driver of revenue growth,” John Curtius, partner, Tiger Global, said in a statement. “We believe’s technology is poised to become a leader in this space, and we are excited to partner with Oliver and his team as they continue to expand into new markets.”

“At EQT Ventures, we typically see two trends in e-commerce innovation. Entrepreneurs build tools to “arm the rebels” or create services for incumbents to keep up with the speed of more nimble players. When we met with Oliver and his team, we immediately bought into his vision of providing leading product recommendations for the masses. Several members of our team have experienced the problem first hand as founders, technology is both a direct catalyst for revenue growth and a time saver from a development capability perspective. We are excited to continue supporting them on their journey from seed to Series A and beyond as they build one of the future giants of the e-commerce infrastructure space,” added Rania Belkahia. , partner at EQT Ventures.

(The list of angels includes Fredrik Hjelm, CEO and co-founder of Voi, Johannes Schildt, CEO and co-founder of Kry, Carl Rivera, CEO and co-founder of Tictail, Erik Bernhardsson, creator of the recommendation engine Spotify, Northzone , Nicolas Dessaigne, CEO and co-founder of Algolia, Vidit Aatrey, CEO and co-founder of Meesho, Joshua Browder, CEO and founder of DoNotPay, Finbarr Taylor, CEO and co-founder of Shogun.)

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