Logi Analytics Leverages Future Insights with Predictive Tool

Share this:

With the understanding that applications are more valuable when they show future outcomes, as opposed to past results, the embedded analytics provider Logi Analytics is launching a product today that will allow users to access and leverage future insights, enabled by machine learning, directly from their existing applications.

Logi says its new predictive analytics tool, dubbed Logi Predict, is an industry-first solution that takes the questions answered by business intelligence tools already on the market—for example, “What’s most likely to happen, and what can I do to change those outcomes?”—and goes one step further, offering a way for product teams to embed predictive insights into the applications they’re already using.

The solution is meant to take the complexity out of the analytical process, giving business administrators a more streamlined way to utilize key data points without relying on outside teams of data scientists.

“Currently, to achieve meaningful predictive insights, an organization needs to have a highly advanced data scientist with R/python skills. Even with that skillset, key insights can be difficult to translate to a wider audience within an organization, which makes it difficult to provide direction,” says Sriram Parthasarathy, senior director of predictive analytics at Logi.

Logi’s new solution, on the other hand, was designed to be easy enough for developers to use as they embed, scale, and maintain predictive analytics on their own. That sort of do-it-yourself approach to predictive analytics is something Parthasarathy and his team are seeing a greater demand for among their developer clients.

In fact, Parthasarathy says the decision to create this new product stemmed directly from customer demand. Logi interviewed more than 100 existing customers as part of its product discovery process and also gathered insights from recent research reports before deciding to create Logi Predict.

“Customers want to treat their business data as a financial asset and are demanding foresight into future business outcomes,” Parthasarathy says.

Also at play is a growing interest among developers who want solutions that will help their own applications stand out from the competition. Parthasarathy says customers are searching for new ways to add context to sensitive, advanced analytics within their applications.

Given that most of the embedded applications that exist today focus primarily on data from the past, Parthasarathy explains that his team wanted to go in the opposite direction, looking forward rather than backward.

Today’s product launch is a long time coming for Logi. The company’s most recent update, prior to today’s, was back in 2017. But Parthasarathy sees Logi Predict as a natural addition to the company’s existing platform, cementing Logi’s position as a leader in embedded analytics.

“The new predictive capabilities open new possibilities going forward for product teams, such as analyzing users’ behavior so they can understand how to improve an application’s experience; creating template applications to predict popular business needs like machine failure, so product teams can more quickly incorporate those insights into their applications; and analyzing unstructured data such as text, audio, images, and video—using deep learning algorithms—to add more context to understand business performance,” Parthasarathy says.

Stephanie Miles is a senior editor at Street Fight.

Stephanie Miles is a journalist who covers personal finance, technology, and real estate. As Street Fight’s senior editor, she is particularly interested in how local merchants and national brands are utilizing hyperlocal technology to reach consumers. She has written for FHM, the Daily News, Working World, Gawker, Cityfile, and Recessionwire.