Ideation sessions help you “work backwards” from business challenges to identify and prioritize your organization’s top ML use cases based on business value, data availability and quality, and level of effort.

Experts guide your team through the process of developing ML solutions for a targeted set of use cases.

To cap off the engagement, our experts can assist with the deployment of ML capabilities to production.

Leveraging our diverse experience helping organizations find value with ML, the ML Solutions Lab will guide your organization through the process of identifying concrete use cases that are important to the organization and addressable with ML.

Our data scientists design and develop advanced ML models in areas such as computer vision, speech processing, and natural language processing to solve customer’s problems.

Our team of experts apply best practices to build ML production pipelines for data management as well as model training, tuning, and deployment to allow our customers to scale new or existing ML models on AWS.

An overarching goal of the ML Solutions Lab is to “teach the customer to fish.” Our ML experts will work hand-in-hand with your team throughout the project, so your developers and data scientists can use the experience to identify, build and deploy additional ML capabilities if you wish.

Applying expertise in anomaly detection, forecasting, and more, the ML Solutions Lab helps manufacturing companies improve their core production, maintenance, safety, and quality, as well as R&D and supply chain functions. For example, the ML Solutions Lab helped Formosa Plastics to apply ML to more accurately detect defects and reduce employee time spent doing manual inspection in half.

The ML Solutions Lab works with financial institutions such as banks, investment organizations, insurance companies, and mortgage firms to improve forecasting, enable surveillance systems to flag new or emerging threats, generate personalized recommendations for financial products, automate document processing, and improve the customer experience with chatbots and conversational interfaces.

The ML Solutions Lab has extensive experience working with sports organizations like Formula 1, the National Football League, and the Seattle Seahawks, to improve the fan experience and quality of the game. In AWS’s partnership with the NFL, the ML Solutions Lab identified and built an entirely new way for fans to engage with the sport through Next Gen Stats and is currently applying ML to support the NFL’s player health and safety initiatives.

The ML Solutions Lab has worked hand-in-hand to tackle some of the world’s biggest challenges from human trafficking to famine to better understanding our universe using machine learning. For example, the ML Solutions Lab worked with Maxar to more effectively analyze satellite data with machine learning – enabling organizations to move faster to react to disasters, like wildfires, and deliver vaccines to villages in Africa.

In the automotive industry, the ML Solutions Lab has worked with customers in areas including supply chain optimization, in-car entertainment experiences, and autonomous driving. This includes improving the safety of drivers and pedestrians with accurate road scene perception and advanced analytics.