Make recommendations that feel tasteful and informed, not robotic.

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The first computer system that understands taste.

While researchers have experimented with increasingly complex mathematical models and “big data” techniques, the underlying frameworks of recommendation technology haven’t changed much since the late 1990s.

Engie takes a new approach to recommendations. Instead of focusing on traditional probability calculations based on user ratings, Engie weaves a holistic prediction algorithm together with systems that more deeply understand culture and taste. It's uncannily accurate, insanely fast, massively scalable, and works on all kinds of content.

Our goal is extraordinary: to change the way people discover the world’s content. So our engine is, too.

A new standard in recommendation quality.

Let's say you like some books...

Engie’s new approach to recommendations means...

25X More Hits
10X Fewer Misses
40X Faster

Upload your dataset, press train, and then use our simple API to get recommendations in real time. Engie's API is as succinct and powerful as the engine it interfaces with – so you can get setup in days, not months. Find our libraries on GitHub.

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Engie Silk is our large scale application built for platforms with hundreds of thousands to tens of billions of user accounts and items. Request a trial and see what the next generation of recommendation technology can do for your business.

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