Deploy and Manage ML Models the Smart Way
Automate DevOps for ML
Accelerate Your Team
Deploy Autoscaling ML Models using Serverless Microservices
Machine Learning utilization is often unpredictable, which makes scaling a nightmare. We deploy your algorithms as scalable microservices built on a serverless infrastructure: that means you get fast and reliable API access, only pay for what you use, and never worry about the hardware under the hood.
Catalog Your ML Portfolio
As your teams push more models into production, keeping track of them can become tedious. The AI Layer lets you tag, categorize, and search all of your models while keeping you on top of where and when they’re being used.
Want to find the right algorithm for your project? You’ve come to the right place. We don’t just host your models: we’ve got a marketplace of over 5,000 algorithms for you to utilize. They’re powered by a community of over 70,000 amazing developers from all over the globe.Explore the Marketplace
Use the Language of Your Choice
Data Scientists thrive in multiple languages, and their models are built accordingly. The AI Layer supports inputs and outputs in most major programming languages, which lets you focus on what matters: building the best models you can.
Model Pipelining built-in
Building sophisticated Machine Learning systems relies on layers of dependencies. The AI Layer makes it easy to pipeline multiple algorithms together seamlessly. You can even set chaining permissions when you create your models.
Resilient Machine Learning systems need to be lightning fast and fully reliable. The AI Layer offers sophisticated reporting and metrics that give you full visibility of your deployments at all times.
Compatible with your Workflow and Infrastructure
Work with any Popular Framework
We support almost anything you’d build a model with, like TensorFlow, Keras, Pytorch, and Scikit-Learn. It’s as simple as stating your package dependency and pushing your code.See all Frameworks
Write in Multiple Languages
Data Scientists write models in multiple languages, which can make things complicated. Are some of your models in R and others in Python? No problem. The AI Layer can run models, functions, and algorithms in most popular languages.See all Languages
Data is everywhere, and piping it all together for modeling is a challenge. The AI Layer supports connectors to S3 and Dropbox, as well as the Algorithmia Data Portal.Learn More
Private Clouds / On-Prem / Air Gapped
Multi-cloud and hybrid-cloud are cornerstones of many infrastructure strategies. We offer deployment across both AWS and Azure, as well as on premises options.Learn More
Our backend has taken years of development. It is built with the most cutting edge frameworks and utilizing the best possible hardware.
What people are saying about Algorithmia's AI Layer
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.
Algorithmia empowers U.S. Government agencies to rapidly deploy new capabilities to the AI layer. 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.