Experiment Faster with Confidence

Deploy models when you want.  Release features when you're ready.

Eliminate risk and deliver value through continuous experiments with your machine learning pipelines.

Control your users' experience through custom targeting rules, shadow mode, and percentage-based rollouts.


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KubeFlow + Airflow + MLflow Workshop
on September 14, Online Global

Every Framework
Every Hardware
Every Cloud

Data Science Teams  

Central Visibility and Control

One dashboard to manage the lifecyle of your models from local development to live production.  Train and deploy your models when you want.  

Deploy Models When You Want

Empower your data science team to collaborate effectively, maintain stability, and delivery models faster. 

Product Teams  

Collect Feedback Faster

Use custom targeting rules, shadow mode, and percentage-based rollouts to safely test features in live production and collect valuable feedback.

Release Features When You're Ready

Product teams independently release features when they are ready.  Instantly rollback any feature with the click of a button.

Enterprises PipelineAI

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Apple PipelineAI Apple

Expedia PipelineAI

Walmart PipelineAI

Square PipelineAI

Hotels.com PipelineAI

U.S. Department of Defense PipelineAI US Dept of Defense

Disney PipelineAI

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Huawei and PipelineAI

Halliburton and PipelineAI

HomeAway PipelineAI

Warner Brothers and PipelineAI


PipelineAI In The News

August 2019
PipelineAI Announces KubeFlow Workshop
KubeFlow + TFX + Airflow

January 2019
PipelineAI Hosts AI Workshop
Deep Learning Summit in San Francisco

December 2018
PipelineAI Joins the Cloud Native Computing Foundation (CNCF)

August 2018
PipelineAI Announces Full KubeFlow & MLFlow Compatibility

May 2018
PipelineAI Launches Multi-Cloud Support @ DockerCon SF

October 2017
PipelineAI Wins O'Reilly Media AI Startup Competition


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