Algorithmia named a leader in GigaOm Radar for Evaluating Machine Learning Operations
Here at Algorithmia, we know that the key to unlocking the value in your AI and machine learning is machine learning operations (MLOps). No matter how many data scientists you’ve hired or how many ML models you’ve built, you won’t get any value from your machine learning until it’s put into production—and MLOps is how you do that.
MLOps can help you put more models into production, faster, and iterate on them quickly as the market inevitably changes. MLOps is your key to staying ahead of your competition in a landscape of rapid digital transformation.
And we’re happy to share that Algorithmia’s enterprise MLOps platform has been recognized as a leader in GigaOm’s Radar for Evaluating Machine Learning Operations (MLOps).
In its first year, the report evaluated the offerings of 14 vendors in the MLOps space. The report emphasizes the vital importance of MLOps for operationalizing your machine learning efforts, and positioned Algorithmia as both a leader and a fast mover in the space.
According to GigaOm, “The time for performing production machine learning (ML) on an ad hoc basis is over. The management of experimentation, deployment, and monitoring of ML models in a formalized, consistent, governable, and rigorous manner is now essential.” The report noted Algorithmia’s strengths as an MLOps platform supporting robust enterprise IT needs.
As the enterprise MLOps platform, Algorithmia manages all stages of the production ML lifecycle within existing operational processes, so you can put models into production quickly, securely, and cost-effectively. Unlike inefficient and expensive do-it-yourself MLOps management solutions that lock users into specific technology stacks, Algorithmia automates ML deployment, optimizes collaboration between operations and development, leverages existing SDLC and CI/CD systems, and provides advanced security and governance.
Over 130,000 engineers and data scientists have used Algorithmia’s platform to date, including the United Nations, government intelligence agencies, and Fortune 500 companies.
We’re excited to receive this recognition from GigaOm, and look forward to seeing more organizations unlock the value in their machine learning through MLOps.