IT solution firm Xavient Information Systems has launched AMPLIFY, an artificial intelligence-powered analytics platform. Company informed that AMPLIFY converts customer interactions aggregated from various channels including speech to text, into intelligent patterns, issues and recommended actions.
The benefits include increased productivity in call centres and proactive outreach to dissatisfied customers thereby reducing churn, also identification of personalised upsell opportunities, decrease in misdiagnosed issues, and ultimately more satisfied customers, said Xavient Information Systems.
Company informed that AMPLIFY will be offered as a cloud- based service in three levels, along with Xavient’s other predictive analytic services:
The Gold level service will include voice-to-data, sentiment analysis and integration to drive next-best action, care prioritisation and omnichannel.
The Silver level service will offer sentiment analysis in near real time in addition to the basic voice-to-data service.
The Bronze level service will include basic voice-to-data transcription in batch mode.
Xavient’s AMPLIFY was developed in the company’s AI Lab and is based on Large Vocabulary Continuous Speech Recognition (LVCSR) technology. The product features the ability to interpret a diverse vocabulary, and is more human-like in its ability to understand and interpret data.
Xavient’s Analytics Engine was designed to aggregate countless threads of customer interactions – be it chat, tweet, email, voice mails, voice transcripts, payment habits or logs and social feeds – into a single, all-encompassing data stream on which companies can mine information to better serve customers.
“The top priority for all enterprises in the digital economy is to innovate and enhance the ‘Customer Experience Architecture’, and Xavient Labs’ innovation with AMPLIFY underlines our alignment with that goal,” said Rajeev Tandon, CEO of Xavient Information Systems.
Hosted on Amazon Web Services‘ cloud, AMPLIFY is architected on Open Source technologies.
