As the very definition of IT broadened over the last few years, data has become too vast for humans to manage manually, let alone analyze and act upon in real time. Organizations are increasingly applying Machine Learning to address the expectation gaps that were born out of this mega trend. But, while most of the dirty work is now being done by computers, it still takes an army of data scientists—and a lot of physical infrastructure—to uncover actionable insights at the enterprise level.

Wise.io wants to change that with a cloud-based, predictive analytics platform that allows customers to hit the ground running. The platform allows them to scale their algorithms as needed, without large upfront capital expenditures on data center equipment.

The startup, a graduate of both the Alchemist Accelerator and the prestigious Citrix Startup Incubator, promises to not only take the hassle out of deployment but also let CIOs make “true machine intelligence” accessible to the non-technical users who drive the bottom line.

Wise.io‘s razor-sharp focus on simplicity mirrors the earlier work of cofounders Damian Eads and Joshua Bloom, professors of astronomy at UC Berkeley who helped develop automated, machine-learning frameworks for analyzing rare cosmic phenomena such as black holes and exploding white dwarfs.

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Wise.io announces funding, new CEO

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Marking the latest milestone in its quest to democratize predictive analytics, Wise.io disclosed today that it has raised $2.5 million in Series A financing from Voyager Capital, an early and growth stage VC notable for its investments in global search marketing agency Covario and other successful Big Data firms. The funding round, which brings Wise.io’s total funding to $5.1 million, was announced in conjunction with the appointment of Jeff Erhardt as CEO.

Erhardt, the former chief operating officer of R distributor Revolution Analytics, is taking over the reins from Bloom, who will continue to direct product development as CTO. These kinds of shuffles are common in startups where the technically-minded founders, who ended up in the driver’s seat, often pass their management responsibilities to more experienced business leaders at the first opportunity.

Wise.io plans to spend the $2.5 million in Series A funding in part on “growing our sales and marketing teams,” Erhardt told siliconANGLE, “and continuing to invest in the productization of our technology by integrating with additional leading SaaS business applications.” The company already has more than a dozen production customers, including Fortune 500 enterprises and startups (such as infographic marketplace operator Visual.ly).

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Machine learning: predictive analytics on steroids

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What exactly is Machine Learning? According to Erhardt, it is an advanced form of computational and statistical techniques used to find subtle patterns in data and make highly accurate predictions based on those patterns. “Its power lies both in the ability to find the proverbial ‘golden needle in the haystack’ and to actually self-improve over time,” Erhardt explained. “While not a new concept, Machine Learning has recently garnered widespread acclaim as being the next generation of Predictive Analytics. It has already become integral to our lives in the form of intelligent spam detection, personalized product recommendations, and adaptive search.”

“Machine learning as a service” refers to Wise.io’s method of their solution’s delivery, according to Erhardt. “We offer a cloud-based application that delivers our solution on-demand,” he said, “either directly via our own platform or integrated with another SaaS application like Zendesk or Salesforce.”

Machine Learning very well may be the future of advanced analytics for the enterprise. “You can think of Machine Learning as ‘predictive analytics on steroids’,” Erhardt said. “Whereas predictive analytics has historically relied on restrictive, so-called parametric models (such as linear regression and logistic regression), Machine Learning employs truly data-driven models that can extract more knowledge from your data.”

As a result, Erhardt said Machine Learning is typically more accurate than classical predictive analytics, especially for large and heterogeneous data sets. “Moreover, because the models themselves are data-driven, they are not limited by the ability of a human to presuppose the factors which will drive the outcomes,” he explained. “Finally, the world does not stand still, and neither should predictive models. Machine Learning-based models have the ability to self-improve over time.”

Wise.io CEO Jeff Erhardt

Customer-facing business processes and tools need to become more data-driven today because, as Erhardt explained, companies that don’t embrace a data-driven approach will be at a distinct competitive disadvantage. “Like with the life experiences of people, machines learn more and find deeper insights with more historical data available,” he explained. “The application of the learning process to make predictions as new data arrives is where the real power lies: what good is the acquisition of data if it is not made actionable?

“Machine learning is already pervasive our lives: being used to detect email spam, make informed product and movie recommendations, and [monitor] financial transactions for signs of fraud. Companies must continue to innovate and optimize their processes. Business intuition and domain knowledge have been useful to make companies more competitive to date.”

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The future of advanced analytics

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The next wave of efficiency will be driven by companies that mine the patterns hidden in their customer data and adopt practices to leverage the insights, Erhardt predicts. Over the next five years, he said advanced analytics will increasingly help enterprises become more efficient and serve their customers better. “Enterprises are sitting on larger and larger data stores but they’re still struggling with what to do with all that data,” he explained.

“Advanced analytics solutions, like ours, will help enterprises draw actionable insights from their data stores. Machine Learning applications will allow workers to focus on creative thinking tasks by automating rote tasks that are better accomplished by machines.”

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photo credit: mansikka via photopin cc

photo credit: Pensiero via photopin cc

photo credit: kevin dooley via photopin cc

Jeff Erhardt’s photo courtesy of Wise.io

Maria Deutscher contributed to this story. Written by Suzanne Kattau