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CallMiner Announces Multi-Language Support PDF Print E-mail
Thursday, 17 August 2017
CallMiner, the leading platform provider of award-winning speech and customer engagement analytics, announced today the company has greatly expanded its language and sensitive data protection capabilities. The company’s industry-leading platforms are now available in nearly 30 different languages and dialects, with multiple languages certified with full PCI-compliant redaction that removes sensitive information such as addresses and ID numbers.

The company’s list of currently certified languages and dialects includes:

English (AU, CA, UK, US, ZA)
French (CA, EU)
Spanish (US, AR, CL, CO, GT, MX, ES)
Portuguese (BR)
German
Mandarin

Additional available languages include Cantonese, Catalan, Dutch, Arabic, Hebrew, Hindi, Indian English, Italian, Japanese, Korean, Malay, Mandarin Taiwanese, Norwegian, Polish, Russian, Swedish, Thai, Turkish, and Wu Chinese. As CallMiner customer requests are received for these available languages, CallMiner will conduct the complete redaction certification for that language.

“Certified” languages and dialects have undergone CallMiner’s strict PCI-compliant full redaction processes. This redaction removes sensitive language identified in the Payment Card Industry Data Security Standard (PCI DSS) from the conversation recording and transcript. The result is powerful analytics data that does not expose sensitive PCI-compliance information, giving clients needed insights while eliminating a security risk.

“Companies must compete in a globally-connected and multilingual world, and we’re offering a wide range of languages to support our growing base of worldwide clients,” said CallMiner Founder and CTO, Jeff Gallino. “Unlike other competitive offerings, we certify languages to ensure they are adequate for use in speech analytics and include native capabilities such as PCI redaction, allowing us to deliver a global, secure speech analytics offering.”

CallMiner’s Eureka platform combines multiple sources of client-to-customer interactions, including phone calls, email conversations, real-time chat, and social media content. This data is transcribed into searchable text so clients can categorise, tag, and score it. This allows clients to gauge agent performance and offers insight into customer satisfaction metrics.
 
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