The platform, called Algorithmia AI Layer, is designed for companies building AI/ML algorithm portfolios. It allows data scientists to automate the DevOps – the combination of software development (Dev) and operation (Ops) – and deployment of AI/ML models in the language of their choice with a simple API in a matter of minutes.
Organizing and implementing AI/ML models is a manual and expensive process requiring years of development time, and requires keeping the layer up-to-date with the latest AI/ML technologies. The lack of AI infrastructure has become a “last mile” problem for companies, says the company, 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 versions: The Serverless AI Layer version allows an engineer or data scientist to create an account on Algorithmia, add AI/ML models in their language of choice, and use the API provided by Algorithmia to host the models on Algorithmia’s cloud; an Enterprise AI Layer version deploys the software to any public or private cloud.
Once deployed, data scientists can use Git to add models, and engineers in the organization can discover and utilize the models with an API call. Authorization and permissioning can be customized to work with any organizational structure, the company says, and DevOps is fully automated.
“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.”
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