{"id":18236,"date":"2022-03-02T22:39:10","date_gmt":"2022-03-02T22:39:10","guid":{"rendered":"https:\/\/mailinvest.blog\/index.php\/2022\/03\/02\/level-ai-which-provides-call-center-automation-software-raises-20m\/"},"modified":"2022-03-02T22:39:10","modified_gmt":"2022-03-02T22:39:10","slug":"level-ai-which-provides-call-center-automation-software-raises-20m","status":"publish","type":"post","link":"https:\/\/mailinvest.blog\/index.php\/2022\/03\/02\/level-ai-which-provides-call-center-automation-software-raises-20m\/","title":{"rendered":"Level AI, which provides call center automation software, raises $20M"},"content":{"rendered":"

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Join today’s leading executives online at the Data Summit on March 9th. Register here<\/a>.<\/em><\/p>\n

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The shift to digital during the pandemic put pressure on customer service operations. A collection of recent reports \u2014 from\u00a0HubSpot<\/a>,\u00a0Salesforce<\/a>\u00a0and\u00a0Mic<\/a>rosoft<\/a>\u00a0\u2014 prove this out. Ninety-three percent of customer service teams believe that customer expectations are higher than before. On the customer side, 69% of people expect more personalized service from companies while getting products and apps. The stakes are high. Nearly 58% of consumers say that they\u2019ll end ties with a brand or business due to poor customer service.<\/p>\n

Automation technologies are one potential way to deliver improved customer experiences. In 2020, Salesforce found that 37% of customer service departments are seeing a higher return on investment from automation than any other department. But challenges stand in the way of adoption, including technical issues, a lack of vision or strategy, resistance to change, and implementation costs. <\/p>\n

Ashish Nagar, formerly a product manager at Amazon Alexa\u2019s conversational AI team, set out to solve these challenges by founding Level AI<\/a>. Based in Mountain View, California, 60-employee Level AI provides real-time conversation monitoring and assistance for contact center agents as well as search tools that enable agents to find information across their organization. <\/p>\n

Automating service tasks<\/h2>\n

At Amazon, Nagar worked on speech recognition and natural language understanding technologies across search-related Alexa services, with a focus on conversational speech understanding. With the learnings from his two years there, Nagar and a small team of engineers built Level AI\u2019s platform, which aims to blend human and machine intelligence to make customer call center service more efficient. <\/p>\n

\u201cThe idea first started with the use of voice assistants to help frontline workers like nurses, contact center workers, and technicians. We observed a pain point: for these frontline workers, phones and laptops are not a great way to access computing, as they work with their hands,\u201d Nagar told VentureBeat via email. \u201cWe focused on the customer service category after seeing the huge market, customer pain, and opportunity to impact the lives of 4 million to 5 million Americans.\u201d<\/p>\n

Nagar claims that Level AI can understand what customers are actually saying during a conversation and scour through different knowledge sources (e.g., Google Drive and Zendesk) to surface proactive hints. Agents can refine the platform\u2019s suggestions, he adds, by flagging hints that don\u2019t help with a customer\u2019s issue.<\/p>\n

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