Using artificial intelligence and big data, Tupl is helping CSPs strengthen their core business
For communications service providers (CSPs), 5G simultaneously presents an extraordinary opportunity and an extraordinary challenge. The opportunity is to enable the digitalization of industry at a scope never seen before. The challenge is to capture that opportunity while controlling operating costs and delivering new, differentiated service experiences.
In order to manage this increasing level of network complexity, operators around the world are turning to machine learning (ML), artificial intelligence (AI), and big data analytics in order to automate business-critical processes thereby saving time and money while driving quality of service and quality of experience.
Based on the maths term “tuple” which refers to a type of ordered list, Bellevue, Washington-based Tupl is working with CSPs around the world on complex automation use cases focused on reducing manual labor and delivering faster, more accurate process outcomes for both network engineering teams and for subscribers.
Tupl CEO Petri Hautakangas, speaking with RCR Wireless News during the recent Mobile World Congress Los Angeles, explained, “The role of automation is paramount. The complexity keeps increasing; it will not go down. In general, there is a huge amount of highly complex, repetitive, manual work that needs to be done by engineers. And the bigger the operator the bigger the problem. That’s what we set out to solve.”
Tupl counts Amdocs, Deloitte, Keysight Technologies, Softbank, Tech Mahindra, Telcel and T-Mobile US among its partners and customers. Discussing Tupl’s work with T-Mobile US, Hautakangas said the goal was to automate engineering decisions when there was a customer issue. In terms of outcome, “We got about 100x faster response to customer issues by using AI-based automation.” He said process efficiency gains were in the 90% range.
With T-Mobile US, Tupl used its AI Care solution which uses engineering, customer care and other data flows to quickly resolve problems, predict problems, and prevent them from occurring. “That creates a fantastic value on the Net Promoter Score,” Hautakangas said.
He said, prior to Tupl being brought on board, time to resolution was 10 hours. After Tupl was brought in, time to resolution went down to 1.5 hours. “This year we are bringing it to 50 seconds. You can run this immediately when someone calls or when someone walks into a retail store. We are really excited about the opportunities we’re bringing to the table as an enabler for our customers.”
