Tupl scores customer win in T-Mobile deployment

T-Mobile has deployed Tupl’s Automated Customer Care Resolution (ACCR) tool, which is billed as a way for customer service reps to better serve customers while freeing up engineering resources.

It marks the first wireless carrier customer win for this product for Tupl, a startup based in Bellevue, Washington, which happens to be T-Mobile’s home turf. The vendor also has offices in Atlanta, Dallas and Malaga, Spain.

“At T-Mobile, we’re obsessed with the customer experience, and Tupl’s tool has enabled us to respond to our customers much faster on technical issues,” said Brian King, T-Mobile’s SVP of Technology Service Delivery & Operations, in a prepared statement. “Solutions like this help make T-Mobile #1 in customer satisfaction in US wireless.”

Tupl says its platform uses Artificial Intelligence (AI) to resolve technically complex and time-consuming issues. In fact, the company says the ACCR tool is 100 times faster and up to four times more accurate than legacy resolution methodologies.

“Our ACCR tool has enabled T-Mobile US to tackle the most complex technical issues through automation by AI,” said Tupl CEO and former Nokia executive Petri Hautakangas in the press release. “Benefits include a very high automation level, 100 times faster speed to response, and improved accuracy. Additionally, the results are 100% consistent, which would be otherwise impossible to achieve without our ACCR solution. Working with T-Mobile US has been a privilege, and we look forward to providing additional AI-based solutions that simplify the operations of the T-Mobile network.”

AI is expected to be a hot topic once again at this year’s Mobile World Congress, to be held in Barcelona Feb. 26-March 1.

Analysts at CCS Insight have said they expect to see a much broader set of uses of artificial intelligence by network operators and network equipment providers come to the fore, ranging from network resource allocation and optimization through detection of fraud and security problems to services based on the huge amount of data available from the network, in addition to processing of the massive quantities of data generated by IoT.