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Skymind Secures $11.5 Million in Series a Funding to Bring AI to the Enterprise

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Skymind Builds High-Performance AI Stacks; Helps Companies Automate Business Processes and Employ Predictive Analytics

Skymind, the leading open-core data science company, has secured $11.5 million dollars in Series A financing. TransLink Capital, a Silicon Valley venture capital firm that helps entrepreneurs develop customer connections and partnerships in Asia, led the round with participation from ServiceNow, Sumitomo’s Presidio Ventures, UpHonest Capital, and DCode with GovTech Fund. Early investors Y Combinator, Tencent, Mandra Capital, Hemi Ventures, and GMO Ventures, also joined the round. To date, Skymind has raised $17.9 million in funding.

“AI and machine learning are no longer on the enterprise wish list, they are a ‘must have’ as successful companies embrace the automation, predictive analytics and efficiency that AI provides”

Skymind’s technology enables enterprises to build high-performance, predictive AI stacks. Specifically, the Skymind Intelligence Layer (SKIL) brings machine learning to a company’s big data stack and computing resources, whether that data and computing power is on-premise, in the cloud, or in a hybrid environment or on edge devices like mobile phones, drones, autonomous vehicles and healthcare sensors.

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“AI and machine learning are no longer on the enterprise wish list, they are a ‘must have’ as successful companies embrace the automation, predictive analytics and efficiency that AI provides,” said Chris Nicholson, Skymind’s founding CEO. “From the beginning, we have focused on creating an AI framework that will sustain companies for years to come, covering everything from data pipelines to algorithm training to model lifecycle management. Today’s financing is a validation of our approach and technology.”

Skymind will use its Series A funds to fuel customer acquisition, building out its sales teams in North America and Asia. Skymind currently has more than 40 employees and more than 20 enterprise customers, including Softbank and France Telecom’s Orange. As part of the new financing, Toshiya Otani, co-founder and managing director of TransLink Capital, will join the Skymind board of directors.

“AI is an $11 billion-dollar market set to double in a few years, and Skymind, as one of the original leaders in open-source AI technology, is well positioned to capture a significant share of the market, particularly as more and more enterprises seek to integrate AI into their core business,” said Toshiya Otani, co-founder and managing director, TransLink Capital. “We have confirmed that there is a significant market opportunity in Asia for Skymind’s technology.”

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With state-of-the-art language models and natural-language processing pipelines, Skymind helps enterprise create more intelligent products as well as automate business processes.

“Applying machine learning and AI to IT operations can help IT teams scale to meet the digital needs of their business,” said Pat Casey, ServiceNow’s Senior Vice President of Platform. “We’ve leveraged Skymind’s technology in our Now Platform Madrid Release to power deep learning solutions across digital workflows. We look forward to our continued work with Skymind as we find new ways to incorporate AI technologies in our platform to drive great customer experiences.”

Skymind’s platform is designed to help companies train machine learning models on a cluster and deploy them anywhere, notably on edge devices.

“We see a lot of potential in bringing machine learning to mobile and other edge devices,” said Ted Tatsumi, president and CEO of Sumitomo’s Presidio Ventures. “The same is true for machine learning applications in the enterprise, and for businesses that seek to bring AI out into the real world.”

Prior to launching SKIL, Skymind created the most widely used open-source AI tool for the Java programming language, Eclipse Deeplearning4j, and is one of the largest contributors to the popular Python deep learning framework, Keras.

Read More: The Artificial Intelligence Week

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