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DeepLearni.ng Receives $9 Million to Put AI to Work In Enterprise
[September 13, 2017]

DeepLearni.ng Receives $9 Million to Put AI to Work In Enterprise


TORONTO, Sept. 13, 2017 (GLOBE NEWSWIRE) -- DeepLearni.ng, a Toronto-based company that designs, builds and deploys applied AI systems for enterprises, announced today $9 million in Series A funding from mutual funds managed by Fidelity Investments Canada (“Fidelity”), a leading investment management firm. In a blog post today, DeepLearni.ng’s co-founders detailed how the investment could impact the company’s future.

Founded in winter 2016, DeepLearni.ng views this investment as a critical step in its multi-yearplan to become the leader in transforming businesses with AI. The timing of the funding also coincides with the company’s plan to scale development of their machine learning platform Frontiers, DeepLearni.ng’s comprehensive machine learning platform built for rapid AI deployment in enterprises. A portion of the funding will also go towards expanding the company’s footprint internationally, in both financial services and other strategic industries.

DeepLearni.ng will immediately begin growing their team, which is currently at 23 people. Headquartered in Toronto, home to The Vector Institute and Geoff Hinton’s pioneering lab at the University of Toronto, the company has a distinct advantage to attract and retain the world’s top talent.

DeepLearni.ng will continue its mission to help enterprises grow their AI capabilities by building sustainable solutions with measurable business impact.     


About DeepLearni.ng
DeepLearni.ng elevates enterprises by building and deploying applied AI systems. The company provides enterprise teams with the knowledge and tools needed to optimize the AI’s potential for business. DeepLearni.ng was founded in 2016 and is headquartered in Toronto. Learn more about how DeepLearni.ng works at www.deeplearni.ng.

CONTACT INFORMATION: For more information, please contact: Alyssa Kuhnert, Communications Director at ak@deeplearni.ng

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