MLOps Platform
for AI Teams

Turn any infrastructure into an AI Cloud

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A New Kind of ML Platform

AI Operating System

  • Turn any infrastructure into your own private AI cloud.
  • Easily deploy popular open-source systems and compose them into end-to-end AI applications.
  • Increase observability and remove management bottlenecks in your AI software stack.

Large Models

  • Serve massive models on your own infra efficiently using model parallelism.
  • Customize to target use cases with fine-tuning and prompt engineering.
  • Automate pre/post processing for safe and reliable outcomes.

CASL Opensource Ecosystem

  • Compose a fully interoperable MLOps and Large Models platform.
  • Automate expertise in infrastructure and ML to tune and train your models.
  • Scale large models across your entire enterprise.

Empower Your
Entire ML Team

Separate your concerns and workflows for a more efficient, productive, and collaborative team.

MLOps Engineer

  • Manage production releases

  • Scale, secure, & optimize cost of infrastructure

  • Monitor ML deployment

ML Engineer

  • Build training pipelines

  • Build model serving APIs

  • Scale training & serving

  • Optimize performance

Data Scientist

  • Select models & features

  • Train & test models

  • Tune hyperparameters

  • Experiment & compare models

Data Engineer

  • Aggregate Data Sources

  • Extract & transform data

  • Feature engineering

  • Manage training data

The Petuum Platform

The Platform to
compose your
own Platform.

The Petuum Platform is made up of 3 central components: the Al Operating System (AIOS), Universal Pipelines, and the CASL Opensource Ecosystem.

Click through to discover more about each tool in our stack.

1. AI Operating System

At the core of the Petuum Platform is the Al Operating System: a control plane extending Kubernetes that allows users to compose, orchestrate and manage custom infrastructure that spans multiple systems on a single pane of glass.

AlOS is interoperable with any tooling simplifies the user's glue code between services. It is fully functional via CLI and GUI.

2. Universal Pipelines

Universal Pipelines enables model builders to develop locally with zero glue code and seamlessly scale to the cloud via our unified DataPacks and auto-containerization tool.

This allows for the separation of concerns between the team members focused on ML pipelines and those focused on production deployments and infrastructure.

3. CASL Opensource

CASL provides an open, unified toolkit for composable, automatic, and scalable machine learning systems.

Built to support machine learning in the real world, the CASL ecosystem includes distributed training, resource-adaptive scheduling, hyperparameter tuning, and compositional model construction.

Explore our Research

Powered by the cutting edge MLOps thought leadership from our award-winning Petuum team.