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    Coveo Launches Intelligent Cloud-Based Search Platform

    Written by

    Nathan Eddy
    Published June 16, 2015
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      Intelligent search and business processes specialist Coveo announced the launch of Coveo Cloud, an end-to-end, intelligent search cloud platform delivering unified search as a service.

      Coveo Cloud, which is scheduled for release in September, is designed to accelerate and simplify search deployments and user adoption by securely unifying data from disparate sources across the IT ecosystem, both in the cloud and on-premises, and creates ubiquitous search experiences where people work.

      The platform also recommends the most relevant insights from everywhere directly into the contexts that customers and employees need.

      “Search is becoming the key to enabling the digitalized workplace. It allows the next generation of digitally literate workers and consumers to access the most contextually relevant information from the IT ecosystem of cloud and on-premises systems and data sources at [the] moment of need,” Diane Berry, senior vice president of market strategy at Coveo, told eWEEK. “By delivering search as a service, organizations will be able to simplify the deployment and expansion of search throughout the enterprise by making it easier to index a wide range of on-premises and cloud-based data sources and systems.”

      The platform’s components include a cloud-based index that unifies cloud and on-premises content, data enrichment that includes text analytics and auto-tagging, and a security framework including encryption at rest.

      “Our goal was to leverage the flexibility and elasticity of cloud computing environments to make enterprise search applications that are simple to deploy and offer secure indexing across both newer cloud-based applications and legacy, on-premises systems,” thereby allowing organizations to accelerate user adoption and reduce time to value, Berry explained.

      In addition, the solution provides broad connectivity to a range of cloud and enterprise systems; a tunable relevance engine, by department, workgroup and user context; a JavaScript interface editor to configure and embed intuitive search experiences; and usage analytics for crowd-sourced content curation and relevance, including machine learning to automatically optimize result relevance.

      As Berry pointed out at Salesforce, where Coveo delivers proactive insights to 900 service agents and all of the customers in its success community, case deflection has increased significantly, and search relevance for support agents has also grown by 85 percent on deployment.

      Coveo for Salesforce Service Cloud and Communities Cloud editions securely bring relevant information from across the IT ecosystem into the context of customers and support agents, often without an explicit query being conducted.

      “The next step in search applications will be the ability to proactively provide users with the most contextually relevant information without the user actually conducting a search,” Berry said. “Machine learning will be combined with usage analytics to allow a search application to provide the most contextually relevant information, at the moment of need, before the user conducts the search.”

      She explained that users—their dynamic profile, including history of searches, interactions across various channels, data accessed and type of work they’re conducting—will become the search, while search applications, ubiquitously embedded in the flow of work, will become the interface to deliver it to the next generation of digitalized workers.

      Nathan Eddy
      Nathan Eddy
      A graduate of Northwestern University's Medill School of Journalism, Nathan was perviously the editor of gaming industry newsletter FierceGameBiz and has written for various consumer and tech publications including Popular Mechanics, Popular Science, CRN, and The Times of London. Currently based in Berlin, he released his first documentary film, The Absent Column, in 2013.

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