Amazon Web Services Inc. today provided a rare glimpse into the growth of its artificial intelligence business by sharing some figures for the ML Solutions Lab, the in-house AI consultancy it set up in 2017.

Michelle Lee, the vice president who leads the ML Solutions Lab, disclosed in a blog post that the group has completed projects for 175 customers since launching a little over two years ago. Those customers include organizations in retail, healthcare, energy, the public sector and sports among others.

The executive detailed that the group has boosted its capacity by more than five times since its formation partly by adding more offices. The ML Solutions Lab, which started out as a North American operation, now has branches in Asia, Europe and Australia as well thanks to the expansion. 

Lee also shared details about her group’s role in some of the high-profile enterprise deals that AWS has announced recently. The ML Solutions Labs is helping the National Football League, which said it would expand its AWS use in December, with its effort to build a system for simulating player injuries. Cerner Inc., a healthcare technology firm that recently named the Amazon.com Inc. subsidiary as its preferred cloud provider, has tapped the consulting group to build an AI engine for predicting heart failure.

NASA’s Heliophysics Lab is also among the AI Solutions Lab’s 175-plus customers. “We brought together the expert scientists at NASA with the machine learning experts in the ML Solutions Lab and the AWS Professional Services organizations to improve the ability to predict and categorize solar super storms,” Lee wrote.

The ML Solutions Lab’s strong growth  reflects how consulting solutions are an increasingly important part of the provider’s strategy for winning business from enterprises. Consulting has a particularly big role to play in AI projects since many traditional companies face a shortage of relevant expertise. Moreover, even organizations already using AWS may not necessarily be familiar with SageMaker and its other AI offerings.

The Amazon subsidiary has been scaling its consulting offerings in a bid to address this need. The ML Solutions Lab added an AI training program for enterprises in December and AWS offers machine learning certifications to consulting partners.

By offering professional services that lower the entry barrier to AI, AWS is ultimately making its cloud-based AI tools accessible to more enterprises. That, in turn, broadens its addressable market. International Data Corp. projects that enterprises will be spending close to $100 billion on AI solutions annually by 2023.

Photo: AWS