Concentrix Wins UK National 2019 Innovation Award

Innovations in Blending Human and Artificial Intelligence

The National Innovation Awards (the Nationals) recognize business technology innovations and their impact on customer experience, employee engagement, operations performance, product creation and profitable growth. Concentrix has been recognized for disruption and innovation by being awarded Winner for “Innovations in Blending Human and Artificial Intelligence” in partnership with Unbabel, a strategic engagement that has established a bold and creative industry-disrupting hybrid multi language solution.

Through their strategic partnership, Concentrix and Unbabel continue to digitally transform traditional multi-lingual customer management solutions by removing the barriers of language and leveraging a unique combination of advanced machine learning, AI and highly-proficient crowdsourcing.

The collaboration of human and artificial intelligence has empowered the creation of highly skilled multi-lingual hubs in low-cost, language-agnostic locations, capable of any-time support in 29 languages. A blueprint for being Different By Design, this innovation is unique in that it allows global organisations to be truly CX-centric for every customer, to shift from a focus of language skills and the many cost and sourcing challenges that can encounter, to a focus that that places their multi lingual support back into the core of a digital first agenda, with greater focus on cross-skilled, digital savvy problem solvers who can offer non-English speaking customers the same levels of high service at the same times as everyone else.

Unbabel helps Concentrix deliver human-quality translations at massive scale, their combined innovation disrupts traditional geo-based solutions and places them not only as the authority of multi lingual innovation, but pioneers of inclusive innovation.

This innovation, which requires less than four weeks to implement, removes the barriers of language and requires minimal up-training, has disrupted traditional multi-lingual

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