Quark.ai Brings Unsurpassed Accuracy, Speed and Scale To Enterprise Customer Responsiveness

Quark.ai Brings Unsurpassed Accuracy, Speed and Scale To Enterprise Customer Responsiveness

Quark.ai, a SaaS technology vanguard provider of Autonomous Customer Support, announced that the Quark.ai Autonomous Support Platform has been successfully deployed at Fortune 1000 companies in the High Tech sector and, through Quark.ai partner Quantum Ventura, at one of the US federal government’s most prominent medical services agencies.

The multi-channel Quark.ai platform combines Deep Learning, NLP and Computer Vision to interpret complex customer cases and automatically provide resolutions with high accuracy and speed, resulting in higher Customer Satisfaction (CSAT) and significantly lower support costs.  Quark.ai’s unique IP enables the platform to be deployed at High-Tech companies with no additional training for its Deep Learning models, enabling customers to realize ROI in a matter of months. Quark.ai resolutions eliminate hours of document reviews by support engineers and can also be used for “auto response.”  Auto-response is a process in which Quark.ai automatically responds to a case or takes corrective actions, for resolutions in which it has a very high confidence. Quark.ai can deliver an increase in support productivity of over 40%.

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“For the federal medical services agency project, we were looking for a fast NLP/ NLU engine able to train rapidly and provide accurate information,” said Srini Vasan, CEO of Quantum Ventura Inc. “Quark.ai’s technology was rapidly deployed with minimal effort for the complex domain using NLP, NLU, and Voice Recognition, and it was able to quickly interpret and cognitively understand highly sophisticated and complex sentences, even those spoken in five different ways.”

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“It is gratifying to see our unique platform delivering excellent ROI to customers in private and public sectors,” said Prosenjit Sen, Quark.ai’s Co-Founder and CEO.  “Quark.ai onboards customers rapidly requiring minimal training of our Deep Learning models, the result of the expertise and unique perspective of our CTO, Dr. Sanjeev Kumar, who has worked in this space for over 20 years.”

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