Wednesday , September 1 2021

Level AI lands $13M Series A to build conversational intelligence for customer service

Level AI, an early-stage startup from a former member of the Alexa product team, wants to help companies process customer service calls faster by understanding the interactions they’re having with customers in real time.

Today the company launched publicly, while announcing a $13 million Series A led by Battery Ventures, with help from seed investors Eniac and Village Global as well as some unnamed angels. Battery’s Neeraj Agrawal will be joining the startup’s board under the terms of the agreement. The company reports it has now raised $15 million, including an earlier $2 million seed.

Company founder Ashish Nagar helped run product for the Amazon Alexa team, working on an experimental project to get Alexa to have an extended human conversation. While they didn’t achieve that, as the technology is just not there yet, it did help him build his understanding of conversational AI, and in 2019 he launched Level AI to bring that knowledge to customer service.

“Our product helps agents in real time to perform better, resolve customer queries faster and make them clear faster. Then after the call, it helps the auditor, the folks who are doing quality assurance and training audits for those calls, do their jobs five to 10 times faster,” Nagar explained.

He says that the Level AI solution involves several activities. The first is understanding the nature of the conversation in real time by breaking it down into meaningful chunks that the technology can understand. Once they do that, they take that information and run it against workflows running in the background to deliver helpful resources, and finally use all that conversational data they are collecting to help companies learn from all this activity.

“We now have all this call data, email data, chat data, and we can look at it through a new lens to train agents better and provide insights to other aspects of the business like product managers and so on,” Nagar said.

He makes clear that this isn’t looking at sentiment or using keyword analysis to drive actions and understanding. He says that it is truly trying to understand the language in the interaction, and deliver the right kind of information to the agent to help the customer resolve the problem. That involves modeling intent, memory and understanding multiple things at the same time, which as he says, is how humans interact, and what conversational AI is trying to mimic.

While it’s not completely there yet, they are working at solving each of these problems as the technology advancements allow.

The company launched in 2018, and the first idea was to build voice assistants for front-line workers, but after talking to customers, Nagar learned there wasn’t a real demand for this, but there was for using conversational AI to help augment human workers, especially in customer service.

He decided to build that instead, and launched the first version of the product in March 2020. Today the company has 27 employees spread out in the U.S. and India, and Nagar believes that by being remote and hiring anywhere, he can hire the best people, while driving diversity.

Agrawal, who is lead investor for the round, sees a company solving a fundamental problem of delivering the right information to an agent in real time. “What ​​he’s built has real time in mind. And that’s kind of the holy grail of helping the customer service agents. You can provide information after the call ends, and that’s […] helpful, but […] you get the real value [by delivering information] during the call and that’s where real business value is,” he said.

Nagar acknowledges this technology could extend to other parts of the business like sales, but he intends to keep his focus on customer service for the time being.

This Article was first published on https://techcrunch.com/

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