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Uniphore Conversational AI recognised by Everest Group as Major Contender

05/10/2022 04:34 PM

KUALA LUMPUR, Oct 5 (Bernama) -- Uniphore, the leader in Conversational Automation has announced that Everest Group, a leading strategic research and analyst firm, has recognised its conversational AI and automation platform as a Major Contender in its 2022 “Conversational AI – Technology Vendor Landscape with Products PEAK Matrix® Assessment.”

Uniphore’s flagship conversational AI and automation platform is the industry’s only platform that delivers a complete analysis of intent, sentiment, emotion and tone for every contact centre conversation. With these robust capabilities, enterprises can transform the complete customer and agent experience.

Uniphore’s platform combines AI, Machine Learning, RPA, Natural Language Processing (NLP), Knowledge AI and more to drive new experiences and maximise the efficiency and cost savings for its customers.

“We’re honoured to be recognised by Everest Group as a Major Contender in the Conversational AI industry. At Uniphore, we’ve always been focused on the importance and the value of conversations in their entirety, and that shines through in this report,” said Umesh Sachdev, CEO and Co-founder at Uniphore in a statement.

“Our platform approach answers the natural evolution of the Conversational AI market, which has for a long time focused solely on self-service offerings opposed to the full spectrum that benefits both customer and agent.”

Meanwhile, Sharang Sharma, Practice Director, Everest Group said: “Uniphore is positioned as a Major Contender in Everest Group's Conversational AI PEAK Matrix®. Uniphore offers a detailed conversational AI solution that utilises advanced capabilities such as sentiment analysis, knowledge AI, RPA integrations, and a low-code/no-code platform.”

“Uniphore’s built-in reports and dashboards analyse conversational data to help with strategic planning. It drives real-time contextualised engagement with customers to improve closure rates and operational efficiency.”


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