New platform makes getting data-driven faster and easier than ever
SAN FRANCISCO, Calif., September 18, 2014 – Lucidworks, the chosen search platform for the world’s most important companies and brands, today launched “Fusion,” a new version of its platform, which gives companies the ability to translate massive pools of data into actionable insights faster than ever. Providing advanced machine learning and signal processing capabilities, Fusion brings a consumer-like search experience to the enterprise. Additional upgrades and new features make it easier for companies to design, develop and implement intelligent search apps at any scale. Built on the global search standard Apache Solr, Lucidworks Fusion dramatically increases businesses’ ability to deliver personalized and contextual search results against a wide variety of data sources.
Lucidworks Fusion helps companies work smarter by delivering the tools required to transform enormous repositories of data into critical and personalized decisions every day. The launch of Fusion delivers numerous new features, such as:
- Modular Integration: allows current Solr users to overlay Lucidworks search and discovery on their existing Solr configuration.
- Big Data Discovery Engine: actively prepares and enriches data, adding features such as language identification and analysis, geospatial processing and synonym identification.
- Connector Framework: provides the ability to import and use data from many external sources and database types.
- Intelligent Search Services: provides developers with the ability to incorporate Lucidworks advanced search features into their applications, providing real-time results that are personalized, relevant and context-aware.
- Signal Processing: harnesses machine learning to transform clicks, social, device, geo and other signals into a contextually-relevant data experience.
- Advanced Analytics: deeply integrated analytics and dashboards make understanding and modifying users’ search experience intuitive and flexible.
- Natural Language Search: delivers full text search that simplifies discovery for users at any level of an organization.
Companies like Sears, Verizon, ADP, Raytheon, Qualcomm, Ford, MapR, eHarmony and Cisco, among others, rely on Lucidworks to power search inside their organizations.
In addition to today’s product launch, Lucidworks announced new leaders at the helm of the organization. Will Hayes, previously Director of Business Development at Splunk, has been named CEO and Keith Messick, who has past experience at SuccessFactors, Get Satisfaction and Topsy (acquired by Apple), has joined as Chief Marketing Officer.
“The launch of Fusion highlights the momentum and direction of Lucidworks,” Hayes said. “The ability to search and retrieve data is the most important action for realizing the promise of Big Data, and Lucidworks is the platform that companies all over the world rely on for their search needs.”
Fusion is available starting today. For more information, visit lucidworks.com.
Lucidworks is the commercial arm of Lucene/Solr, one of the largest open source projects in the world, employing over 80 active Solr committers helping to improve and shape the direction of the most popular search software solution.
Follow @LuceneSolrRev to find session content and get updates on our next event, or visit http://lucenerevolution.org/
Join our conversations on Twitter @Lucidworks and Facebook
Lucidworks builds enterprise search solutions for some of the world’s largest brands. Fusion, Lucidworks’ advanced search platform, provides provides the enterprise-grade capabilities needed to design, develop and deploy intelligent search apps — at any scale. Companies across all industries – from consumer retail and healthcare to insurance and financial services – rely on Lucidworks every day to power their consumer-facing and enterprise search apps. Lucidworks’ investors include Shasta Ventures, Granite Ventures, Walden International, and In-Q-Tel. Learn more at lucidworks.com.
LaunchSquad for Lucidworks
lucidworks [at] launchsquad [dot] com