Artificial Solutions Recognized as Business Disruptive Technology of the Year

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Artificial Solutions, the natural language interaction (NLI) specialist that enables users to have a meaningful, humanlike interaction with technology, announced today that Teneo has won Business Disruptive Technology of the Year in the 2015 Technology Innovator Awards. The awards highlight the pioneering work of the teams and individuals behind the ground-breaking developments.

Already recognised in the Nordics in the Disruptive Challenger awards, Teneo enables enterprises to rapidly build a range of artificially intelligent natural language applications from digital employees and mobile personal assistants, to wearables and IoT interfaces – all from a single platform. In addition, Teneo’s deep analytics provides the backbone to delivering true machine learning and implicit personalization by understanding more about an individual, their likes and preferences, through interaction only.

The 2015 Technology Innovator Awards shines a spotlight on those companies that develop the technology that fundamentally alters the business world for the better for many years to come. Through its rigorous awards process it considers an organizations commitment, experience and willingness to explore and take advantage of the opportunities presented.

Digital employees, the IoT and artificial intelligence all have the capacity to make or break enterprises within the next few years,” says Andy Peart, CMO or Artificial Solutions. “Our ethos behind making technology think has always focused on enabling enterprises to take advantage of this disruptive technology faster and easier than any other comparable product. We’re delighted to be recognised with this award.”

Teneo delivers artificial intelligence not just to the end user, but to the development of natural language applications too by reducing the reliance on highly technical skills such as computational linguists that other tools still require. Today, Teneo uses machine learning and auto-coding to learn, predict and proactively recommend improvements to an application. This enables organizations to quickly build and deploy highly effective NLI applications within very short timescales.

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