Aylien launches news analysis API powered by its deep learning tech

Text analysis startup Aylien, which uses deep learning and NLP algorithms to parse text and extract intel from documents for its customers, has launched a new tool specifically focused on analyzing written news content.

“The idea for the News API is to give access to the news content that is out there enriched and in real-time to developers and data scientists,” says co-founder Parsa Ghaffari. “It’s a very data and analytics centric approach to news.”

The Dublin-based startup says it’s utilizing core text analysis tech powering its existing text API product, which launched back in February 2014 — but this time it’s focusing exclusively on news content and also doing a little more of the analytical heavy lifting for its customers.

“We decided to simplify the use case a little bit by collecting and analyzing the news documents on our end, rather than giving them the tools to do that themselves. So this was born out of that,” says Ghaffari.

He adds that the text analysis API was already being used by news and media companies “to makes sense of news articles at scale” — so the team has now stepped in with a tailored product to better serve that demand.

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Ghaffari says they’re targeting the News API at developers, data scientists and “solution builders” in verticals such as publishing, PR, news aggregation, newsreader apps, hedge funds, media monitoring, and voice of the customer analysis solutions. So there will evidently be some overlap/cannibalization of existing Aylien users.

Its SaaS Text API product has nearly 20,000 subscribers at this point, with Ghaffari flagging up the likes of Sony, The World Economic Forum and Complex Media as “notable customers”.

While Ghaffari mentioned a plan to launch a news API all the way back in 2014, when TechCrunch last spoke to him, he says the idea then was to build a bare bones news ticker. Whereas the News API is a fully featured product in its own right — letting users perform granular search queries — such as, for example, asking for news stories written about Donald Trump that have a negative sentiment and were published by news outlets based in Wisconsin.

The product also serves up automated summaries of retrieved news article; points to related stories; profiles social media performance; charts the volume of stories on a particular topic over time; shows sentiment breakdown; and details article length.

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Users can search for news by byline to track particular journalists’ output — a useful feature for PRs wanting to intelligently target pitches. (Rather than, *hint-hint*, repeat copy-pasting ‘I read your story about X and thought you’d be interested in writing about Y’… )

I ask Ghaffari whether he used the news API tool to determine which TC journalist to send his pitch to — and he confirms he did (as you’d hope). So, in this one example at least, the tech’s targeting relevance was fair. (It did also suggest he approach my colleague Fred, who wrote the prior story on Aylien.;

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