Lynx Analytics, a leader in artificial intelligence and data science solutions, announces the open source release of its Complete Graph Data Science Platform, LynxKite 4.0, after years of development and successful deployments with customers.
With rapidly growing availability of network and relationship data as well as new graph deep learning technologies, Graph AI is the next frontier of machine learning as advocated by leading machine learning experts. By integrating relationship information into machine learning models, graphs are a crucial component in numerous AI applications: network based attribute prediction, fraud detection, product recommendation, infrastructure and operations optimization, drug discovery, etc.
Up until today, building Graph AI solutions has been a highly technical process that involved numerous skills, tools and coding efforts. This has created a high barrier to entry and slow adoption of Graph Analytics. As a “one stop shop” graph data science platform, LynxKite removes these obstacles and makes Graph AI more accessible to enterprises and citizen data scientists.
“After having been conceived and developed by professors from prestigious US, European and Asian universities, and a top-notch engineering team, LynxKite has already been deployed at a number of our enterprise customers and across many industries. It’s also been tested and used extensively by our data scientist team.” says Gyorgy Lajtai, Lynx Analytics’ CEO. “With increasing requests from our clients and users, we are pleased to open source LynxKite to benefit the larger data science community.” he added.
All interested users can download LynxKite from lynxkite.com and access the source code on GitHub under the GNU Affero General Public License v3.0. Alternatively, they can also evaluate the tool through a Cloud Demo. Detailed documentation and usage examples are available online as well.