Deploy and Manage ML Models the Smart Way

Automate DevOps

Automate DevOps for ML

Deploy any model in minutes
Advanced Monitoring
Autoscale to match any demand
Accelerate Your Team

Accelerate Your Team

Empower your data scientists
Collaborate Across Org
Zero-lag model iteration
Optimize Hardware

Optimize Hardware

Serverless Microservices
Optimized GPU usage
Advanced Scheduling

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.

New Algorithm Options

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.

Sentiment Analysis Algorithm Summary

AI Marketplace

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
Algorithm Tags and Categories
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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.

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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.

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Advanced Monitoring

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 Sources

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.

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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.

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Tech Stack

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

Anna Patterson
VP of Engineering, Artificial Intelligence at Google

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.

Google
Katie Gray
Partner at In-Q-Tel

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.

In-Q-Tel
Mark Cuban
Chillest Shark on Shark Tank

Algorithmia: Google Sheets + AI

Great introduction to playing with AI
WORTH THE TIME

Via Twitter
Prashant Sharma
Senior Program Manager at Microsoft

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.

Microsoft

Ready to make your entire team more effective?