Innography Named One of “10 to Watch” by Leading Analyst Firm
Innography, the innovative software provider of better intellectual property answers for improved business results, announces that it has been named one of “10 to Watch” by Outsell, Inc. in its report “The Evolving Patent Information Landscape.” Innography was selected because, according to Outsell analyst Hugh Logue, “Innography has earned the reputation of being one of the most innovative players in the patent information market.”
“With our recent Spring 2014 Release, we have already extended our product and service capabilities beyond the report’s complimentary description to add even more value for clients.”
With patents and patent information becoming increasingly critical to business performance, the report provides an overview of the vendor solution landscape and types of user professionals at each stage of the patent lifecycle. Outsell’s Hugh Logue says, "Innography is a relatively new player that has managed to disrupt the patent information market by successively leveraging predictive analytics and big data technology. It is strong in business-facing solutions and is popular with executives because of its advanced visualization tools and its integration of patent information with related data such as financial, litigation and other key information."
“With almost 50 new clients so far this year, many in the market are realizing the advantages of the highly capable and innovative Innography platform,” said John F. Martin, CEO and chairman, Innography. “With our recent Spring 2014 Release, we have already extended our product and service capabilities beyond the report’s complimentary description to add even more value for clients.”
Innography has achieved record growth so far in 2014, and was named the winner of two content CODiE awards for Best Legal Information Solution and Best Service Using Aggregated Content. In April 2014, Innography was listed in the Open Data 500, a comprehensive study of U.S.-based companies that leverage open government data and extrapolate value commercially.