DataRobot announced the release of DataRobot AI Platform 9.0, along with deeper partner integrations, AI Accelerators, and redesigned service offerings, all centered on helping organizations derive measurable value from their AI investments.
“AI has the potential to enhance every aspect of business transactions and human interactions to improve how we live and work,” said Debanjan Saha, CEO of DataRobot. “Since our founding, we have been 100% focused on helping enterprises realize measurable value from AI by offering an AI lifecycle platform designed to solve business problems, and the applied AI expertise to help customers envision what’s possible – and achieve it.”
The DataRobot AI Platform allows customers to leverage Value-Driven AI, a unique and collaborative approach that improves how organizations run, grow and optimize their business. With the new and expanded platform capabilities announced today, DataRobot is enhancing the key features and functionalities trusted by global organizations and relied on by nearly half of the Fortune 50.
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“DataRobot’s rich machine learning blueprints, feature engineering methods and explainability features amongst others make it a cornerstone in BMW Group’s AI Platform to scale AI adoption,” said Marc Neumann, Head of AI Platform BMW Group. “We use DataRobot for rapid exploration and development of AI models while adhering to the code of ethics for safe and trustworthy AI.”
The breakthrough innovations inside the DataRobot AI Platform include capabilities that facilitate:
- Rapid experimentation and value identification using Workbench, DataRobot’s brand new collaborative experimentation experience. Workbench, equipped with integrated managed Notebooks, supports users with both code-first and no-code approaches and the full spectrum of data science capabilities.
- Reduced enterprise risk and barriers to production through well-architected guard rails — from bias mitigation, centralized model monitoring, to automated model compliance documentation of both DataRobot and non-DataRobot models.
“Before DataRobot, our process was very manual – we had success in pockets but our scale was limited,” said Luke Bunge, Data Science Project Manager at Polaris Inc. “Polaris is growing rapidly, and DataRobot is key to allowing us to scale and expand ML across business units, making our existing team much more productive and driving the most possible value with AI.
SOURCE: Businesswire