Algorithmia Launches AI Layer for the Enterprise

“Last mile” solution allows data scientists to deploy AI/ML models in minutes

Seattle, Washington, UNITED STATES

SEATTLE, Nov. 16, 2017 (GLOBE NEWSWIRE) -- Algorithmia announces the availability of the Algorithmia AI Layer, a software platform that dramatically accelerates the process by which companies can deploy Artificial Intelligence (AI) and Machine Learning (ML) models into applications. Designed for companies building AI/ML algorithm portfolios, Algorithmia AI Layer allows data scientists to automate the DevOps and deployment of AI/ML models in the language of their choice with a simple API in a matter of minutes.

Billions of dollars are spent annually by data scientists and the companies they work for developing AI/ML models, however, organizing and implementing these models is a manual and expensive process requiring years of highly experienced engineers’ development time, and requiring the team to keep the layer up-to-date with the latest AI/ML technologies. The lack of AI infrastructure has become a “last mile” problem for companies, which keeps most AI/ML investments from ever reaching production.

“Tensorflow is open-source, but scaling it is not,” says Kenny Daniel, co-founder and CTO of Algorithmia. “Almost all R&D has focused on collecting and cleaning data, and building models. Algorithmia has spent the last five years building the infrastructure that will put those models to work.”

The Algorithmia AI Layer comes in two flavors: Serverless and Enterprise. With the Serverless AI Layer, an engineer or data scientist can create an account on Algorithmia, add AI/ML models in the language of their choice, and use the API provided by Algorithmia to host the models on Algorithmia’s cloud. With the Enterprise AI Layer, Algorithmia’s team deploys the software to any public or private cloud. Once deployed, data scientists can use Git to add models, and engineers around the organization can discover and utilize the models with an API call. Authorization and permissioning can be customized to work with any organizational structure, and DevOps is fully automated.

“Algorithmia empowers U.S. Government agencies to rapidly deploy new capabilities to the AI layer,” says Katie Gray, Principal of Investments at In-Q-Tel. “The platform delivers security, scalability and discoverability so data scientists can focus on problem solving.”

“Today, most AI/ML models are still being deployed manually, which requires a lot of time, coordination, and engineering resources. We’re working with Algorithmia to help companies deploy, iterate, and scale faster on Azure with the Enterprise AI Layer,” says  Prashant Sharma, Senior Program Manager, Microsoft for Startups.

“As someone that has spent years designing and deploying Machine Learning systems, I'm impressed by Algorithmia's serverless microservice architecture – it's a great solution for organizations that want to deploy AI at any scale,” says Anna Patterson, VP of Engineering, Artificial Intelligence at Google.

“Every company with an AI strategy is going to need to build their own AI layer, which would take years and cost millions of dollars, or buy one,” says Diego Oppenheimer, co-founder and CEO at Algorithmia. “Our view is that companies would rather buy a platform that works today, is supported by some of the world’s leading tech companies and AI experts, and costs a fraction of what it would take to build their own solution. We already have several large enterprise companies using the Algorithmia AI Layer and look forward to partnering with all the major cloud providers to deliver the AI layer to their customers.”

About Algorithmia

Algorithmia started in 2014 as a marketplace for AI/ML models and has grown to support over 55,000 developers and 4,000 algorithms, functions, and models, making it the largest AI platform in the world. Today, algorithms and models on Algorithmia include research from MIT, University of Washington, Carnegie Mellon University, University of California Berkeley, Caltech, University of Texas at Austin, University of Tokyo, and University of Toronto. More information at

Media contact:
Kevin Wolf
(650) 327-1641