“Headquartered in Charlotte, NC, USA, Fuzzy Logix is a leading predictive analytics software and services company that provides analytics tools for big data.”
As organizations increasingly rely on data analytics to make better, more informed decisions, you need tools that give you a competitive edge. With in-database analytics solutions provided by Fuzzy Logix, the constraints of traditional analytics no longer exist. By eliminating the need for data extraction, middle-tier analytics servers and redundant data storage, the company’s products allow customers to process their analytics within the database and make massive time, cost and resource savings.
Fuzzy Logix started its operations in 2007 by forming a partnership with Netezza. Its first customers were on the Netezza platform. The need to go multi-platform prompted the company to port its models to run on nine database platforms including Teradata and SQL Server. The code base is now over 700 models for data mining and machine learning.
Achieving Unprecedented Performance Gains
Almost all other analytics products in the market have speed and scalability constraints because either they require data to be moved from the data warehouse to their server for processing or they didn’t code their models for parallel processing so performance is not optimized. Adopting the solutions of Fuzzy Logix has resulted in performance improvements of 10X to 100X. The ability to embed its products into existing applications and reporting tools means that the learning curve for users is fast and companies can deploy analytics operationally. The company also doesn’t charge a seat license. It does this in order to make it possible to roll out analytics across the business at very low cost.
A new generation of In-Database Analytic Solutions
The company’s solutions have been proven to help firms make smarter decisions, increase effectiveness and improve performance. Fuzzy Logix’s main product, DB Lytix is a collection of over 600 analytics models that cover everything from forecasting and segmentation to data mining and machine learning. It installs DB Lytix into a traditional data warehouse or Hadoop in about 15 minutes and turns that environment into a high performance analytics engine. The speed and scalability are fantastic.
For calculation intensive problems, it installs models in GPUs and can run billions of iterations in milliseconds. To complete the solution stack, Fuzzy Logix also offers consulting. This can range from helping a company develop and deploy their analytics strategy to custom model development.
The customers of Fuzzy Logix are in diverse sectors including banking and finance, insurance, retail, manufacturing, marketing services, and healthcare. Its customers are generally large companies with enormous amounts of data who are already doing analytics such as Tesco, Raymond James, 3 of the top 5 healthcare organizations in the US and 2 of the 5 largest financial institutions in the US. The company also works with smaller and highly innovative companies who are trying to deploy analytics and create competitive advantage.
It also has a second set of clients that include partners with whom products are jointly engineered. These include Teradata, Dell and Actian. In this case, the companies either resell or embed its product into theirs as an OEM solution.
A large pharmaceutical company wanted to improve the way drug trial simulations were performed. They logically had a way to improve accuracy and safety, but couldn’t find a technical solution that could perform the calculations. Fuzzy Logix worked with them to engineer a custom solution that now runs in hours instead of days. The solution has now been submitted to the FDA and should be approved as the new standard of performance in drug trial simulation.
The company has a global presence with emphasis on countries such as USA & Canada, UK, Germany and Western Europe as well as India.
Future Road Map
Fuzzy Logix is currently working to add functionality to its product and build it into new platforms including Aster Data and Hadoop. It is also moving up the solution stack by building not just models, but solutions to address common problems such as churn management, warranty reserve holding calculations, cash flow forecasting and retail inventory management analytics. Finally, the company is working with clients to bring solutions to market in the form of joint ventures. These solutions will combine the company’s analytics expertise with its domain experience to create market specific high value solutions.
Meet the Leadership Team
Partha Sen, Chief Executive Officer
Before founding Fuzzy Logix, Partha held senior management positions for Bank of America, including the commercial and investment bank, portfolio strategies group and also managed the Quantitative Management Associate Program. He has a Bachelor of Engineering from the Indian Institute of Technology and a MBA from Wake Forrest. Partha has a passion for solving complex business problems using quantitative methods, data mining and pattern recognition to create the ground-breaking products that Fuzzy Logix is renowned for delivering.
Michael Upchurch, Chief Operating Officer
Prior to Fuzzy Logix, Michael worked at Bank of America, where he developed the strategic and operational plan for their $11B telephone based mortgage and home equity sales group and grew it to $22B. Later he joined the Consumer Innovation Team in Global Portfolio Strategies in the Global Corporate and Investment Bank. Next, Michael worked in the Global Bank Debt organization to develop sales strategy and product innovation. In his final role, he worked to identify innovative solutions to treasury and debt management challenges for global companies. He has a degree in Finance and minor in Psychology from East Carolina University. Mike is passionate about helping companies leverage analytics to create value. He works with clients to identify solutions that align analytics projects with corporate goals and to ensure the delivery of these solutions.
“We make analytics easy, pervasive and available real-time.”
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