May 20, 2021

AI Platform Provider ASAPP Raises $120m in Series C funding

AI
customerexperience
ML
Analytics
2 min
ASAPP’s technology responds to customer interactions and offers suggested responses in real-time to call agents

ASAPP, a provider of artificial intelligence-enabled customer experience tools used in call centers, has announced it raised $120 million in Series C financing. This brings ASAPP's total funding to $400 million and doubles the company's valuation to $1.6 billion from its Series B financing a year ago. 

New investors included Fidelity Management & Research Company LLC and Dragoneer along with existing investors John Doerr, March Capital, Emergence Capital, Euclidean Capital, HOF Capital, Telstra Ventures and 40 North Ventures. 

AI is continuing to be adopted by organisations, and according to a poll, enterprise executives cite customer experience as their number one reason for investing in AI. AI-enabled conversational agents are expected to handle 20% of all customer service requests by 2022, a report suggests. 

Asapp is one of the few companies advancing research and development in AI and its application for customer experience, founder and CEO Gustavo Sapoznik explains"In an environment where customer expectations are rising, ASAPP is helping large enterprises advance digital engagement, real-time voice transcription, speech analytics, and live agent coaching and analytics," 

"The Customer Experience (CX) industry is at a crossroads. After years of interactive voice response systems (IVR) and bot investments, customer satisfaction is down, and costs have increased. We apply our AI research to make people in contact centers wildly more productive because existing rules-based technology and architectures limit companies to small improvements that can't bridge the digital transformation opportunity that AI is enabling and delivering." Sapoznik added. 

Improving customer experience

The New York based company aims to increase agent efficiency with AI-driven suggestions of what to say and do to resolve issues quickly. ML identifies opportunities for automation before, during, and after agent engagement, as well as flexibly setting agent capacity based on intent, the complexity of conversations, customer responsiveness, agent experience, and more.

"This Series C financing will enable ASAPP to increase investment in ASAPP's AI Native, Customer Experience Performance (CXP) platform that helps global enterprise customers drive differentiated customer experiences, revenue, cost reductions and automation designed to support employees in customer service and sales," said Tim Stone, ASAPP's Chief Operating Officer, and Chief Financial Officer. 

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Jun 23, 2021

Google launches Visual Inspection AI tool for manufacturers

AI
Google
Manufacturing
ML
3 min
Google has launched Visual Inspection AI, a new Google Cloud Platform solution designed to help reduce defects during the manufacturing process

Google Cloud has launched Visual Inspection AI, a new tool to help manufacturers identify defects in products before they're shipped. 

Poor production quality control often leads to significant operational and financial costs. The American Society for Quality estimates that for many organisations this cost of quality is as high as 15-20% of annual sales revenue, or billions of dollars annually for larger manufacturers. Google Cloud’s new Visual Inspection AI solution has been purpose-built for the industry to solve this problem at production scale. 

How does it work? 

The Google Cloud Visual Inspection AI solution automates visual inspection tasks using a set of AI and computer vision technologies that enable manufacturers to transform quality control processes by automatically detecting product defects.

Google built Visual Inspection AI to meet the needs of quality, test, manufacturing, and process engineers who are experts in their domain, but not in AI. 

  • Run autonomously on-premises: Manufacturers can run inspection models at the network edge or on-premises. The inspection can run either in Google Cloud or fully autonomous on your factory shop floor. 
  • Short time-to-value: Customers can deploy in weeks, not the months typical of traditional machine learning (ML) solutions. Built for process and quality engineers, no computer vision or ML experience required. An interactive user interface guides users through all the steps. 
  • Superior computer vision and AI technology: In production trials, Visual Inspection AI customers improved accuracy by up to 10x compared with general-purpose ML approaches, according to benchmarks from several Google Cloud customers. 
  • Get started quickly, with little effort: Visual Inspection AI can build accurate models with up to 300x fewer human-labeled images than general-purpose ML platforms, based on pilots run by several Google Cloud customers.
  • Highly scalable deployment: Manufacturers can flexibly deploy and manage the lifecycle of ML models, scaling the solution across production lines and factories.

Industry use cases

The demo video shows how Visual Inspection AI addresses use cases to solve specific quality control problems in industries such as automotive manufacturing, semiconductor manufacturing, electronics manufacturing and general-purpose manufacturing. 

Kyocera Communications Systems, a manufacturer of mobile phones for wireless service providers, has been able to scale its AI and ML expertise through the use of the solution. “With the shortage of AI engineers, Visual Inspection AI is an innovative service that can be used by non-AI engineers,” said Masaharu Akieda, Division Manager, Digital Solution Division, KYOCERA Communication Systems. “We have found that we are able to create highly accurate models with as few as 10-20 defective images with Visual Inspection AI. We will continue to strengthen our partnership with Google to develop solutions that will lead our customers' digital transformation projects to success.”

Visual Inspection AI has fully integrated with Google Cloud's portfolio of analytics and ML/AI solutions, giving manufacturers the ability to combine its insights with other data sources. The tool integrates with existing products from Google Cloud partners, including SOTEC, Siemens, GFT, QuantiPhi, Kyocer and Accenture. 

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