Algorithmia, a leader in ML Operations & Management, announces a series of upgrades to its Enterprise product. The platform changes are highlighted by advanced security options that enable customers to operate Algorithmia in highly controlled and restrictive environments, including AWS C2S and AWS GovCloud. The new version of Algorithmia Enterprise also includes support for the latest AWS and Azure GPU hardware, user local debugging improvements, and integration to PyCharm.
Machine learning has the most impact on a company’s core applications, which live behind a firewall in regulated industries like financial services, insurance, healthcare and laboratory sciences. For ML systems to serve those industries, integration to core security systems and compliance with policies and processes is a requirement. Algorithmia’s updated Enterprise product addresses this with support for air-gapped deployment, C2S, GovCloud and VMWare, authenticated proxies, customer-provided and hardened OS images, private Docker hub, private dependency mirrors, and private certificate authorities.
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“Large enterprises in regulated industries have stringent requirements around all aspects of their software development lifecycles,” said Diego Oppenheimer, CEO at Algorithmia. “Many of these companies want to leverage machine learning and artificial intelligence to improve business outcomes, but current MLOps platforms don’t offer the features and integrations to support these requirements. Algorithmia Enterprise allows customers to control the provenance of all components of ML operations, including certificate authorities, operating system, container images, code, dependencies and ML models used in their ML enabled applications.”
“Deploying machine learning models in production applications is no small task, and it’s further complicated for organizations, like ours, that operate in highly regulated industries,” said Shane Zabel, PhD, Artificial Intelligence Technology Director at Raytheon Intelligence & Space. “Algorithmia has helped by combining technology and expertise that allows us to deploy ML-based applications quickly and easily while prioritizing security and compliance with government standards.”
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The updated version of Algorithmia Enterprise also includes support for the latest GPU hardware. “Organizations today are utilizing advanced ML models that require more memory and GPU performance, while driving down costs, and new hardware is being created specifically to meet the needs of these models,” says Oppenheimer. “This update addresses our ability to support the latest hardware per our customers’ requirements.”
Finally, Algorithmia extends the benefits of modern software development lifecycle practices, and by enabling local debugging in the developers desktop tools they use to develop in today. By extending this experience locally, Algorithmia will enable users to write and run local tests for algorithms, pass local data files as input to their algorithms, and integrate with leading development environments like PyCharm. Integration to tools like PyCharm allows developers and data scientists to use tools of their choice, develop faster with fewer defects. Algorithmia integrates with various developer tools already such as Jupyter Notebooks, R Shiny, Android, IOS, Cloudinary, Datarobot and H2O.AI.
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