A London tech startup has launched a free platform that combines AI and neuroscience with an emotion-led approach to streaming categorisation., which goes live in 118 countries today, aims to enable users to match a movie to their mood across 516 streaming platforms mere days after Netflix cracked down on users in secondary households. Users describe their desired emotional state using emotive words or emojis. 

Recommendations can then be further filtered based on ratings, release date, what can be watched for free, or what can be watched with any existing paid streaming subscription.

With the global competition for subscribers, the amount of available video content has jumped 18% in the last three years. Paradoxically, this makes finding something relevant to watch harder. 

In December 2022, an annual global study of 6,000 streaming consumers by Accenture found a staggering 72% get frustrated trying to find something to watch, up 9% year on year. More than one-quarter (26%) say it can take them more than 10 minutes to choose something, up 53% year on year. And more than one-third (35%) unsubscribed from at least one of the top five streaming video-on-demand services in the last 12 months.

Existing streaming platforms typically rely on two main recommendation systems – content-based and collaborative filtering – which both date back to the 1990s and fail to take into account the emotions that influence nearly every decision people make. 

How is Near-Life making training simulations accessible?

“Watching movies is an emotional experience,” said founder and CEO Ben Polkinghorne (below). “Discovering them should be too. 

“Existing streaming platforms are infuriating their customers with arguably ancient, flawed and unsophisticated recommendations that often fail to connect people to the content they crave.”

Ben Polkinghorne,

Funded by a grant from Innovate UK, the startup undertook research with leading neuroscientists Dr Kathrin Kadosh and Dr Philip Dean at the University of Surrey. The company was then able to develop a pioneering emotion-led algorithm that has now analysed 676,906 films.

Dr Dean explains: “By measuring brain activity as people watch movies, we begin to understand the neural signatures of emotional processing. This raw emotional data can then feed an algorithm to automatically predict how a movie will make someone feel.”’s free platform also promises greater visibility and discovery of exciting content from independent and foreign filmmakers that often don’t surface on traditional platforms, where recommendations tend to favour popular hits. is free to users and has plans to engage with content platforms to licence its patent-pending technology while continuing to develop its public service.

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