Saleor's Founders

Open source 'headless commerce' builder Saleor closes $8M round led by Target Global and Zalando

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Saleor's Founders

Image Credits: Saleor

Saleor — a Poland- and U.S.-based startup that develops an open source headless e-commerce platform used to build online shops — has pulled in an $8 million seed-extension round led by Target Global (the investors that have previously backed the likes of Revolut and Auto1) and e-commerce giant Zalando. Also participating were SNR VC Kevin Mahaffey, Cherry Ventures, and TQ Ventures.

Saleor’s API for e-commerce does the back-end heavy lifting for online shopping while developers produce a bespoke front end.

We last covered Saleor when it had raised $2.5 million in seed funding from Berlin’s Cherry Ventures, with participation from various angels.

The seed-extension round is noteworthy, as it’s clear open source is gaining traction in e-commerce where normally proprietary solutions abound. Saleor competes against other more traditional e-commerce tools such as CommerceTools and legacy vendors such as Salesforce.

In a statement, Lina Chong, partner at Target Global, said the firm was attracted to “Saleor’s thriving open source community” and “robust SaaS offering.”

Founded in 2020 but existing as a project since 2013, Saleor is an open source, headless, composable e-commerce platform. It was originally started by the web agency of founders Mirek Mencel and Patryk Zawadzki, who then spun it out as its own startup. Today, the platform is used by such brands as Lush and Breitling.

Zalando, a leading European e-commerce destination for fashion and lifestyle, said that it invested “based on Saleor’s traction with global brands.”

Jan Bartels, SVP B2B at Zalando, said in a statement: “We see a great fit with Saleor’s vision, offering, and expertise, which can also help us to further expand our capabilities.”

I spoke to co-founder Mirek Mencel, who said: “Everybody has to optimize for the experience they provide to their customers. And this is nontrivial in today’s world where expectations are growing, so Saleor is enabling that.”

He described how open source had gained traction in the e-commerce world: “When Patrick and I met as open source developers, we told ourselves we are not going to work with e-commerce because we hated this as developers.”

“We saw this as inefficient and programmatic and brands were asking for things the software was unable to do in 2009. After doing a couple of big projects together we realized this is a big niche. We released the platform as open source and decided to see if there was a possible business afterward. In 2020 we realized this was going to be an amazing business as well, because brands also want communities around the products, in the same way the open source community functions,” he added.

With Vertex AI Agent Builder, Google Cloud aims to simplify agent creation

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Google Vertex AI Agent Builder presentation at Google Cloud Next

Image Credits: Frederic Lardinois/TechCrunch

AI agents are the new hot craze in generative AI. Unlike the previous generation of chatbots, these agents can do more than simply answer questions. They can take actions based on the conversation, and even interact with back-end transactional systems to take actions in an automated manner.

On Tuesday at Google Cloud Next, the company introduced a new tool to help companies build AI agents.

“Vertex AI Agent Builder allows people to very easily and quickly build conversational agents,” Google Cloud CEO Thomas Kurian said. “You can build and deploy production-ready, generative AI-powered conversational agents and instruct and guide them the same way that you do humans to improve the quality and correctness of answers from models.”

The no-code product builds upon Google’s Vertex AI Search and Conversation product released previously. It’s also built on top of the company’s latest Gemini large language models and relies both on RAG APIs and vector search, two popular methods used industry-wide to reduce hallucinations, where models make up incorrect answers when they can’t find an accurate response.

Are AI models doomed to always hallucinate?

Part of the way the company is improving the quality of the answers is through a process called “grounding,” where the answers are tied to something considered to be a reliable source. In this case, it’s relying on Google Search (which in reality could or could not be accurate).

“We’re now bringing you grounding in Google Search, bringing the power of the world’s knowledge that Google Search offers through our grounding service to models. In addition, we also support the ability to ground against enterprise data sources,” Kurian said. The latter might be more suitable for enterprise customers.

Image Credits: Frederic Lardinois/TechCrunch

In a demo, the company used this capability to create an agent that analyzes previous marketing campaigns to understand a company’s brand style, and then apply that knowledge to help generate new ideas that are consistent with that style. The demo analyzed over 3,000 brand images, descriptions, videos and documents related to this fictional company’s products stored on Google Drive. It then helped generate pictures, captions and other content based on its understanding of the fictional company’s style.

Although you can build any type of agent, this particular example would put Google directly in competition with Adobe, which released its creative generative AI tool Firefly last year and GenStudio last month to help build content that doesn’t stray from the company’s style. The flexibility is there to build anything, but the question is whether you want to buy something off the shelf instead if it exists.

The new capabilities are already available, according to Google. It supports multiple languages and offers country-based API endpoints in the U.S. and EU.

https://techcrunch.com/2024/04/09/google-cloud-next-2024-everything-you-need-to-know/