We made an open-source personalization engine
Hey, HN! You probably know that the ordering of products on Amazon, posts in FB, and search results in Google is personalized for each visitor, as it directly affects conversion, click rate and engagement. But not everyone can afford to hire an army of PhDs to squeeze every penny out of the ranking, and not everyone agrees on the current (im)balance between privacy and profits. So we built Metarank, an open-source and privacy-focused personalization engine. It can rerank in real-time any type of content, using only the data you allow, and optimize metrics you define. We made a lot of…
In plain words
Metarank is an open-source personalization engine that reranks content in real-time to optimize metrics like conversion and engagement. Built for companies that want to personalize product ordering, feed ranking, or search results without relying on proprietary services or sacrificing user privacy, it lets teams implement personalization using only the data they approve. The tool is designed for developers and businesses seeking an alternative to expensive, complex ranking solutions.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hey, HN! You probably know that the ordering of products on Amazon, posts in FB, and search results in Google is personalized for each visitor, as it directly affects conversion, click rate and engagement. But not everyone can afford to hire an army of PhDs to squeeze every penny out of the ranking, and not everyone agrees on the current (im)balance between privacy and profits. So we built Metarank, an open-source and privacy-focused personalization engine. It can rerank in real-time any type of content, using only the data you allow, and optimize metrics you define. We made a lot of proprietary DIY services for personalization in e-commerce in our past careers and heard so many complaints from other companies also struggling to implement personalization. It’s often considered "too risky" to spend 6+ months on an in-house moonshot project to reinvent the wheel without an experienced team and no existing open-source tools. Like other people in the industry, we were tired of building everything from the bottom up each time we approached personalization - it should be easy not only for Amazon to do such magical ML tricks, but for everyone else. A small demo of the tool with personalized recommendations: https://demo.metarank.ai A blog post on how this demo was made: https://medium.com/metarank/personalizing-recommendations-wi... The project itself: https://github.com/metarank/metarank
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