SFL Scientific today announced that it has been selected by the NVIDIA Partner Network (NPN) as the 2019 Service Delivery Partner of the Year 2019 for the Americas for the second year in a row.
The NPN selected SFL Scientific for its AI consulting and development services, helping clients and partners develop new AI tools, products, and solutions utilizing the power of NVIDIA GPUs to help accelerate and solve complex business challenges.
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“Receiving this honor and recognition from NVIDIA is the validation of our mission to be the leading data science and AI implementation partner, helping organizations solve unique challenges with deep learning and AI-based solutions,” said Dr. Michael Segala, CEO, SFL Scientific. “NVIDIA’s industry-leading GPU portfolio benefits not only our respective clients, but shapes how we create R&D, automation, and operational solutions across industries.”
“This award is a testament to SFL Scientific’s ability to lead clients and partners along their journey toward becoming AI-driven enterprises,” said Craig Weinstein, Vice President of the Americas Partner Organization at NVIDIA. “NVIDIA and SFL Scientific have worked together to add strategic services in solution development and enablement, as well as created opportunities for our clients to innovate.”
The NPN honors its top North American partners that have shown growth in their GPU business through their growth, leadership, and investments they have made throughout the year.
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As organizations capture valuable data across all business functions, a central understanding of how to fully leverage that information, operationalize outcomes, and plan where to best make Artificial Intelligence (AI) and machine learning (ML) investments is critical to building a future competitive advantage. SFL Scientific addresses these needs by deploying Ph.D. data scientists and engineers to use AI in solving data-intensive and complex R&D problems.
SFL Scientific’s data science consulting team has worked extensively to distinguish their capabilities beyond what is commercially available by developing novel AI solutions, working across data collection, DevOps & data management, hardware & cloud, computer vision, natural language processing (NLP), and time-series & IoT.
