Now, Edgetier is excited to take this capability a step further with the launch of Spotlight Summaries - a feature release designed to give you a clearer picture of multiple customer interactions at once.

Increasing appetite for automation in contact centres is driving significant demand for new tech to step in. And with AI and machine learning being all over the place, it was a matter of time before customer service catch up.Irish company EdgeTier, which helps customer contact centres improve customer experience using AI, announces today that it has raised €6 million in Series A funding in a round led by Smedvig Capital, with participation from Episode 1 and Act Venture Capital.This funding will enable EdgeTier to meet the growing demand for its real-time AI analytics platform that helps companies deliver excellent customer experience using their conversational data.Dr. Shane Lynn, CEO and Co-founder of EdgeTier, comments: “Companies will simply not be able to compete without AI and machine learning augmenting their ability to understand and support their customers at scale. We want to help more contact centres and customer experience professionals recover the missed insights in their conversations, react faster to changes, and have the data they need at their fingertips to make decisions. Over the fundraise, we’ve been really impressed with the Smedvig team; Joe and Maeve are already bringing great value to the business and I’m really excited to partner with them now on the journey ahead.”EdgeTier’s AI platform ushers in a new era of customer experience management, giving unlimited access and real-time insights on customer conversational data to support a higher quality customer experience, and in turn drive customer acquisition and retention. This task is hugely difficult as existing toolsets are complex to operate, not real-time focussed, and have no machine learning capabilities to support advanced analysis.With EdgeTier, contact centres get a deep understanding of customer attitudes and can detect even subtle issues in real-time, which could otherwise have gone unrecognised and unaddressed