Big Squid Releases Ultra-Fast Prediction API Enabling Real-Time Business Decisions

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Early customers empowered to make critical decisions on leads within 30 seconds, saving millions in costs, and achieving exceptional ROI.

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“We realized that a data-literate organization isn’t going to settle for a few teams or individuals leveraging machine learning, but would want to extend those capabilities to as many people as possible,” says Brian Shindurling, VP of Marketing at Big Squid.

Big Squid is pleased to announce its new ultra-fast Kraken Prediction API, providing decision makers and business analysts with real-time predictions that are immediately actionable.

As a testament to the power of the Kraken Prediction API, one early adopter in the financial services industry connected the Kraken Prediction API with their Lending Management System to make real-time lead-buying decisions. With as little as 30-seconds to make a buying decision, the API helps quickly identify at-risk borrowers that may default on the loan or won’t get funded before they are acquired, reducing lost income and cutting expenses. “Using Kraken’s API, we have been able to make decisions on inbound leads within 30 seconds. In the span of one month, this has enabled us to save $34k and has the potential to save us hundreds of thousands of dollars per year,” states this confidential Big Squid customer.

The API makes deploying analyses and taking prescriptive action easier than ever through real-time and row-level predictions integrated directly into Business Intelligence tools, data warehouses, business rules engines, CRM systems, or other software solutions. Matt Belkin, Big Squid’s President, explains, “The API is just one more way we are working to democratize data across an entire organization, independent of role or experience with machine learning.” He continues, “We have many customers and partners seeking to incorporate machine learning into their product and service offerings. Unfortunately they lack the resources and know-how to make that happen. The Prediction API changes this entirely, allowing them to incorporate real-time predictions into their custom offerings, how and when they need it."

Enterprises that already use automated machine learning to empower analysts and decision makers are beginning to scale those insights across multiple departments and applications. “We realized that a data-literate organization isn’t going to settle for a few teams or individuals leveraging machine learning, but would want to extend those capabilities to as many people as possible,” says Brian Shindurling, VP of Marketing at Big Squid. “We wanted to give our customers the means to be as creative as possible and we are blown away at what we are seeing. The Prediction API is another example of the work Big Squid is doing to define how machine learning is applied in business.”

Big Squid notes that Kraken already gives analysts the ability to create predictive machine-learning models without necessarily needing a data scientist. The Prediction API extends the power of those models to multiple end-users by integrating data-driven, prescriptive, action directly into their day-to-day work. It is flexible enough that it can be deployed in a variety of different ways and allows for the creation of customizable applications that best fit almost any use case.

Big Squid’s release of the Kraken Prediction API comes on the heels of other customer-centric features, namely the CSV upload, on-premises deployment capability, and Snowflake integration.

About Big Squid:
Machine Learning is helping companies become data-driven faster than ever before. Big Squid empowers businesses to understand their data and to take action on it in ways that traditional business intelligence and analytics tools are not yet able to do. Our AutoML platform, Kraken, was designed to augment your existing analytics capabilities. Kraken quickly surfaces true statistical insights and diagnostic analytics and empowers business analysts to deliver predictive and prescriptive analytics solutions all within your existing data and analytics infrastructure.

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Carly Ray
@Big_Squid
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Big Squid, Inc.

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