IBM is rolling out a cognitive tool powered by its Watson supercomputer that uses companies’ internal data to answer questions about performance and efficiency and predict outcomes.
IBM said the tool — the latest in a series of Watson products — will make more widely available data analytics capabilities long reserved for research scientists. The move is part of IBM’s effort to shift resources away from a slumping hardware sector into more profitable fields like cloud computing and analytics.
In August, IBM launched Watson Discovery adviser, a tool scientists can use to identify patterns in data. In July, engine maker Pratt and Whitney said it would use IBM’s data analytics to predict aircraft engine trouble.
Watson Analytics clients can upload their business’ data and ask the tool personalized questions like “Who are my most profitable customers?”
Watson, which uses artificial intelligence to quickly analyze huge amounts of data and can understand human language, may ask several follow-up questions to give clients the most accurate results possible.
The cloud-based tool will then analyze various data sets and provide answers and visualizations that predict future outcomes.
Watson can also create graphics and charts that allow clients to share the results of their inquiries and better implement solutions to their problems.
“When people have individual problems, they can get answers without having to call a data scientist or call IT, without having to become a data scientist themselves,” said Alistair Rennie, general manager of business analytics for IBM.
IBM will equip Watson with geographic, industry and economic data that customers can use in conjunction with their own data. The interactive tool also automatically prepares, refines and houses data.
The offering will be launched in beta-testing mode within the next month and will be available for all IBM business clients in November.
The basic service is available on a freemium basis, where basic features are free and customers can pay for a premium service that allows them to work with larger, more complex data sets from a wider array of sources.
“Essentially, we think freemium is important because this is the type of tool that hasn’t been accessible to a wide audience. We’re convinced once professionals get a taste for the base features, they’re going to love it and want to use more of the premium features,” said Rennie.
(Reporting by Marina Lopes; editing by Andrew Hay)
This article originally appeared on Recode.net.