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News, Unified Communications

Cognitive Collaboration – Notes from Cisco’s Enterprise Connect 2019 Keynote

Everything you need to know about Cognitive Collaboration and other new products from Cisco coming out of the company’s keynote at Enterprise Connect 2019.

March 20, 2019 Jonathan Blackwood Leave a Comment

Cisco Bug

At today’s EC19 keynote, Cisco introduced Cognitive Collaboration – a new concept for Cisco that will touch each of the 300 million users worldwide that Cisco already serves. Cognitive collaboration’s intelligence is slip-streamed into products without the end user needing to lift a finger, and will change how we provide personalized production and how employees work. Cognitive collaboration will be able to bring all of the information about participants in a meeting directly to everyone in the meeting.

As of today, Cognitive Collaboration is alive inside Webex meetings, and all users need to do is show up.

Cisco bought the startup that Amy Chang, SVP of Collaboration Technology Group for Cisco and speaker at the EC19 keynote, created, and that is the backbone of Cognitive Collaboration. Cisco created a massive data engine that is always on the lookout for publicly available information about people and companies. It parses it into its components and gives that information to the relevant employees. There are 250 million profiles of people, and 25 million profiles of companies inside the data platform. That is creating the information in the Webex graph that will be available across Cisco’s entire portfolio.

Profiles are created for people and companies in the Webex graph. Advisories, a biography, and links to publications, videos, and recent news are all available on a social-media like interface available to Cisco customers. As you continue to scroll, every association with companies that a person has is also available. You can click on a company and find everything about that company in the Webex graph as well. News, executives, locations, and even news activity. Users can set up alerts when people or companies they choose are in the news.

On top of that data, AI and machine learning come in. Chang shows a chart that shows graduates from Stanford University, and breaks down hundreds of factors about their careers that organizes them into a plot that shows their business prominence. That’s only one example – imagine the implications of this on a contact center.

Photo Credit: no jitter

That rising stars analysis can be used to pull a profile on potential customer value – how much a customer could spend on your company. Cisco is investing heavily in the call center space because they believe they have something massive and unique to bring the right customers to the right contact at the right time. For the next 18 months, Cisco will be releasing all kinds of new products and services for the contact center.

On the devices side, Cisco is investing heavily in voice for meeting spaces. Cisco devices are already AI powered – the brand new Room Kit Mini has facial recognition, active framing, and advanced telemetry. It is specifically designed for huddle spaces up to five participants. It has an extreme wide-angle camera, 120-degree field of view, and can sit close to participants. The Cisco view corrects bends and breaks in the camera view. Camera view is automatic and can frame the participants, as well as provide name tags under participants. Diagnostic mode shows how the camera is seeing the frame and participants in view.

“We are so excited to make Cognitive Collaboration a reality for you,” says Chang.

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Jonathan Blackwood
Jonathan Blackwood

Jonathan Blackwood is the Editor-in-Chief of TechDecisions. Jonathan joined TechDecisions in 2014 and writes about technologies that help to innovate and improve practices for companies of all sizes, K-12 and higher education, government, healthcare, hospitality, retail and large venue spaces. He is especially interested in the future of work and education and the Internet of Things. Follow him @BlackwoodTweets.

Tagged With: Artificial Intelligence, Collaboration, Machine Learning

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