DataRobot Adds to its AI Toolbox
DataRobot, the automated machine learning software vendor, continued its string of acquisitions this week with a deal to buy Boston Consulting Group’s AI technology platform. The companies also announced a strategic partnership that would combine consulting services with DataRobot’s intellectual property.
The AI acquisition and partnership seek to address the growing number of unsuccessful enterprise AI deployments. Missing is the ability to build, deploy and monitor machine learning models that produce actual results and return on investment.
Hence, the partners said Tuesday (June 9) they will collaborate to help customers build “industrial-grade” AI platforms. To that end, high-flying DataRobot will acquire the business consultant’s Source AI technology. The platform is designed to free data scientists to write restriction-free code used that combines human and technical expertise.
For example, the Source platform was recently used to build a decision support and scenario planning tool to gauge the impact of COVID-19 on customer demand. The Lighthouse tool combines real-time data, analytics and human expertise to come up with business intelligence on how the pandemic is affecting consumer demand and supply chains.
Boston Consulting touts its approach as filling in blind spots such as lag time and lack of granularity often associated with sales data. Hence, the platform’s “intelligence layer” incorporates demand signals such as “footfall” and web traffic. Among the insights gleaned from this granular approach is that online demand for goods and services often represents a leading indicator of actual sales transactions.
DataRobot said the new functionality would allow data scientists to use its enterprise AI platform for “model experimentation and training as well as production model management and deployment.”
The partners also said they would collaborate on “industry-specific applications” that would ease the adoption of AI technology at scale. DataRobot specializes in data science automation to accelerate deployment and management of machine learning models. The Boston-based company announced a $206 million funding round last September, bringing its investment total through seven rounds to nearly $431 million.