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In our latest guest blog post from Upscale programme partners Amazon Web Services, we explore the current transformation of media analysis at the hands of AI company Signal Media.

In the last few years there’s been a lot of hype around artificial intelligence and machine learning. But there are far fewer stories about how these transformative technologies factor in big business in a real-world context. So we sat down with media monitoring startup Signal Media, to find out how they’re leveraging machine learning technology to shape business knowledge around the world.

A better way to digest information

The way we consume media is messy. When busy C-suite executives need to analyse stories in popular publications, they usually ask a group of analysts and assistants to read and find relevant articles from magazines, news articles, and broadcasts, to understand what’s happening in their world. Research is often ad hoc and unstructured, which impacts how the information is interpreted and deployed.

For David Benigson and Dr Miguel Martinez, co-founders of Signal, the need for a better solution was impossible to ignore: business leaders should be able to filter relevant news from an unlimited number of sources and get reliable, actionable insights on demand.

Partnering with academics from leading institutions across Europe, the team developed proprietary AI and machine learning principles to sift through media content in real-time, delivering relevant information to businesses.

For example, let’s say you want to keep track of Apple, but you don’t want any news about the fruit, or The Beatles’ publishing company. Signal contextualises the news around the word, so only news about Macs and iPhones is seen, rather than the apple harvest in Herefordshire or Hey Jude. And when it delivers results, it shows you the sources it’s used, so you can assess the relevance, context and trustworthiness of the content.

Today, the technology can scan linguistic quality to weigh in on journalistic style, and translate content automatically across 70 languages. The result – it’s users make smarter, faster decisions based on actionable, contextual insights.

Building a platform

The team began as a handful of data science researchers and developers crammed into a windowless North London garage. Their vision was clear, but with pressure to develop technology that could solve such a complicated challenge, ahead of competitors, the road ahead was long.

Yet today, Signal’s grown into a successful business with a team of more than 50, airy offices in Aldgate, and plans for global expansion.

The transformation took less than four years, and was driven by cloud technology. The team built its infrastructure on Amazon Web Services (AWS) which provided freedom to scale without limits, and grounds to test systems without making commitments. It was able to cluster large volumes of data and process more than 30,000 documents in a day – a figure which has now ballooned to over 3 million.

By using AWS, server growing pains were reduced to a simple, automated formality. They’d turned the unmanageable global data firehouse into a contextual knowledge base for businesses around the world.

Research-led innovation

Academia has been at the heart of Signal from the very beginning. They’ve worked with young, smart researchers from institutions worldwide to create an adaptable network of talent that inspires a culture of innovation. Each year they host a number of top researchers in the AI and machine learning space who develop their MSc thesis, PhD or Postdoc through collaboration with the company.

Community culture

An important practice for growth is to maintain connections with other businesses, creating a strong network that facilitates idea generation and development.

“That’s why initiatives like Tech City UK’s Upscale programme are so important,” according to Miguel. “They connect startups with leaders who’ve made huge wins from humble beginnings.”

And Upscale doesn’t just cater for CEOs. It attracts big players across a range of departments from marketing to product development, so deeper discussions about tech and problem-solving can be had. They’re also a great place to source researchers. And for those just wanting to learn, there’s an extensive programme of interesting, intimate talks, like how to function in a niche market or utilise a particular kind of tech.

A global vision

Today the team are using Series A funding to refine technology, hire more developer talent, and expand into the US.

The next move is to expand the AI to sift through multiple data sets, from legislation and research papers to compliance and risk documents.

The future’s bright for Signal, and for other AI companies trying to make a real impact.

Grow your startup

AWS is a Upscale programme partner that’s helped a number of startups to innovate and disrupt, from Airbnb and Netflix to Slack and Spotify. Check out the latest successes features on AWS Startup Stories.

And to learn more about Signal, check out, or their research initiative at




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