Coveo Lauds Itself for Growth, Innovation, and Industry Awards
February 16, 2016
The article on EIN News titled Coveo Achieves Another Record-Breaking Quarter and Calendar Year of Rapid Growth discusses the search companies growth and recognition in a nakedly self-congratulating post. In 2015, Coveo released both Coveo Cloud, a streamlined search-as-a-service, and Coveo Reveal, a self-learning search service aimed at understanding intent to ensure improved accuracy and relevance in search results. The article states,
“The company expanded its SI ecosystem with several leading CRM and Customer Community system integrators, including Appirio, Bluewolf, Cloud Sherpas, Etherios, NTT Data Cloud Services and Vertiba. Exiting 2015, Coveo had in excess of 100 certified SI partners… Coveo for Sitecore was named as a 2015 CUSTOMER Magazine Product of the Year Award winner, marking the fourth consecutive year that Coveo has won this award (In January of 2015 Coveo received its fifth consecutive CUSTOMER Magazine product of the year award…)”
So just how big was that fish Coveo caught? The private company reports a “record breaking quarter” lists any number of current projects and industry recognitions. According to the article, the company now has a total amount of financing of $75 million. 2015 was clearly a very good year, particularly in the financial services market. What company can resist patting itself on the back?
Chelsea Kerwin, February 16, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
It Is Not a Bird in the Law Firm
November 3, 2015
In science-fiction, artificial intelligence is mostly toyed around with in robots and androids. Machines that bear artificial intelligence either try to destroy humanity for their imperfection or coexist with humanity in a manner that results in comedic situations. In reality, artificial intelligence exists in most everyday objects from a mobile phone to a children’s toy. Artificial intelligence is a much more common occurrence than we give our scientists credit for and it has more practical applications than we could imagine. According to PR Newswire one of the top artificial intelligence developers has made a new deal for their popular product, “RAVN Systems’ Artificial Intelligence Platform Is Deployed At Berwin Leighton Paisner.”
RAVN Systems is known for their top of line software in enterprise search, unstructured big data analytics, knowledge management, and, of course, artificial intelligence. The international law firm Berwin Leighton Paisner recently deployed RAVN Systems’s RAVN Applied Cognitive Engine (RAVN ACE). RAVN ACE will work in the law firm’s real estate practice, not as a realtor, but as the UK’s first contract robot. It will use cutting-edge AI to read and interpret information from documents, converting unstructured data into structured output. RAVN ACE will free up attorneys to complete more complex, less menial tasks.
“Matthew Whalley, Head of Legal Risk Consultancy at BLP commented, ‘The robot has fast become a key member of the team. It delivers perfect results every time we use it. Team morale and productivity has benefited hugely, and I expect us to create a cadre of contract robots throughout the firm. If the reaction to our first application is any indication, we will be leading the implementation of AI in the Law for some time to come.’ ”
RAVN ACE has more applications than writing real estate contracts. It can be deployed for financial services, media, telecommunications, and more. Taking over the menial tasks will save on time , allowing organizations to reinvest time into other projects.
Whitney Grace, November 3, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Coveo: A Real Life Search Implementation Success
September 11, 2015
If we detect some serious Coveo cheerleading in this recent article found on RT Insights, that might be because the story originated at that company. Still, “How Real-Time Enterprise Search Helps Seal Financial Deals” does illustrate the advantages of consolidating data resources into a more easily-used system.
The write-up describes challenges faced by London investment firm 3i Group. The global company had been collecting an abundance of data about its clients’ deals, but was spending many worker hours retrieving that information from scattered repositories. Coveo Enterprise Search to the rescue! The platform implementation included a user-friendly UI, actionable analytics, and security measures. The article continues:
“As a result of the implementation, 3i Group reports 90 percent faster access to deal-related intelligence as well as a 20 percent reduction in staff and resources required to respond to compliance requests. 3i Group’s staff members use the platform to search across 3.66 million file share documents, 6.39 million Exchange emails, 897,000 SharePoint documents, and 107 million Enterprise Vault records. For the first time, 3i Group staff members are able to perform a single search across all of the company’s knowledge repositories by using either a browser-based interface or an integrated search interface within SharePoint. 3i Group’s compliance team was provided with a dashboard that enabled them to search and correlate content from across 3i Group’s entire data set, and quickly evaluate permissions and user access rights for every 3i Group record or knowledge asset.”
Founded in 2005, Coveo maintains offices in California and the Netherlands, with its R&D headquarters in Quebec. (The company is also hiring as of this writing.)There is no doubt that being able to reach and analyze all data from one dashboard can be a huge time-saver, especially for a large organization. Just remember that Coveo is but one of several strong options; some are even open source.
Cynthia Murrell, September 11, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
How to Use Watson
August 7, 2015
While there are many possibilities for cognitive computing, what makes an idea a reality is its feasibility and real life application. The Platform explores “The Real Trouble With Cognitive Computing” and the troubles IBM had (has) trying to figure out what they are going to do with the supercomputer they made. The article explains that before Watson became a Jeopardy celebrity, the IBM folks came up 8,000 potential experiments for Watson to do, but only 20 percent of them.
The range is small due to many factors, including bug testing, gauging progress with fuzzy outputs, playing around with algorithmic interactions, testing in isolation, and more. This leads to the “messy” way to develop the experiments. Ideally, developers would have a big knowledge model and be able to query it, but that option does not exist. The messy way involves keeping data sources intact, natural language processing, machine learning, and knowledge representation, and then distributed on an infrastructure.
Here is another key point that makes clear sense:
“The big issue with the Watson development cycle too is that teams are not just solving problems for one particular area. Rather, they have to create generalizable applications, which means what might be good for healthcare, for instance, might not be a good fit—and in fact even be damaging to—an area like financial services. The push and pull and tradeoff of the development cycle is therefore always hindered by this—and is the key barrier for companies any smaller than an IBM, Google, Microsoft, and other giants.”
This is exactly correct! Engineering is not the same as healthcare and it not all computer algorithms transfer over to different industries. One thing to keep in mind is that you can apply different methods from other industries and come up with new methods or solutions.
Whitney Grace, August 7, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
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