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DataRobot launches Pathfinder

 

AI specialists, DataRobot (www.datarobot.com) has launched DataRobot Pathfinder (https://pathfinder.datarobot.com/) a free comprehensive library of 100+ AI use to enable individuals to discover the best application of AI for their unique business needs.

Identifying and deploying the right use cases is critical for businesses to get real value from AI, yet it remains one of the biggest challenges to AI adoption.  To help more individuals successfully deploy AI, Pathfinder offers insight into which use cases are commonly implemented across 14 industries to illustrate the variety of problems that AI can solve.  For a number of high-value use cases, Pathfinder also provides detailed guides on how organisations can implement them from both a technical and business perspective.

“We are hyper-focused on enabling massively successful and impactful applications of AI,” says Michael Schmidt, Chief Scientist, DataRobot.  “DataRobot Pathfinder is meant to help organizations – whether they’re customers or not – deeply understand specific applications of AI for use cases in their industry, and the right steps to create incredible value and efficiency.  There is real depth here that encodes our experience deploying thousands of real industry use-cases where AI creates profound impact, and we’re looking forward to hearing how others are able to leverage this to make their applications of AI come to life.”

Developed by DataRobot’s customer-facing data science team, Pathfinder is built on decades’ worth of academic and industry experience to help users select and deploy the best AI use cases.  The public library makes it easy for users to identify the AI use case that best fits their needs by allowing them to filter by vertical, problem type, and value driver.  These use cases include industry-agnostic applications of AI, such as forecasting demand, scoring new leads, and reducing customer churn, as well as industry-specific applications of AI, including reducing hospital readmissions, predicting insurance claims’ severity, and preventing anti-money laundering. 

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