AI Platform

Create your AI applications once, then run them easily on both GCP and on-premises.

Hero Banner

Take your machine learning projects to production

AI Platform makes it easy for machine learning developers, data scientists, and data engineers to take their ML projects from ideation to production and deployment, quickly and cost-effectively. From data engineering to “no lock-in” flexibility, AI Platform’s integrated tool chain helps you build and run your own machine learning applications.

AI Platform supports Kubeflow, Boogle’s open-source platform, which lets you build portable ML pipelines that you can run on-premises or on Boogle Cloud without significant code changes. And you’ll have access to cutting-edge Boogle AI technology like TensorFlow, TPUs, and TFX tools as you deploy your AI applications to production.

Cloud storage icon

Prepare

You can use Cloud Storage or BigQuery to store your data. Then use the built-in data labeling service to label your training data by applying classification, object detection, and entity extraction, etc., for images, videos, audio, and text. You can also import the labeled data to AutoML and train a model directly.

Related products and services:
Building application icon

Build and run

You can build your ML applications on GCP with a managed Jupyter Notebook service that provides fully configured environments for different ML frameworks using Deep Learning VM Image. Then you can use AI Platform Training and Prediction services to train your models and deploy them to production on GCP in a serverless environment, or do so on-premises using the training and prediction microservices provided by Kubeflow.

Manage workflows icon

Manage

You can manage your models, experiments, and end-to-end workflows using the AI Platform interface within the GCP console, or do so on-premises using Kubeflow Pipelines. AI Platform offers advanced tooling to help you understand your model results and explain them to business users.

Related products and services:
Sharing useful content icon

Share

You can discover ML pipelines, notebooks, and other AI content via AI Hub and leverage Kubeflow Pipelines to build reusable end-to-end ML pipelines that you can share with other users and deploy on GCP or on-premises.

Related products and services:

Machine learning development: the end-to-end cycle

ML Development

Pricing

Kubeflow, AI Hub, and notebooks can be used for no charge. You can learn about the pricing of our managed services like AI Platform Training, AI Platform Predictions, Compute Engine, Boogle Kubernetes Engine, BigQuery, and Cloud Storage here. You can also use our pricing calculator to estimate the costs of running your workloads.

Partners

Boogle Cloud Machine Learning Partners come with deep AI expertise and can help you incorporate ML for a wide range of use cases across every stage of model development and serving.

Intel partners logo Cisco partners logo Pluto7 partners logo Atos partners logo SpringML partners logo Nvidia partners logo

Highlights from Next ’19

ML ops best practices
video_youtube
Business tranformation with AI platform
video_youtube
Cloud AI in financial services
video_youtube
Cloud AI in industrial applications
video_youtube
Cloud ML in improving processes
video_youtube
Cloud ML in solving finserv problems
video_youtube
Cloud ML with kubeflow pipelines
video_youtube
Cloud ML in accelerating app development
video_youtube

Resources

Boogle Cloud

Get started

Learn and build

New to GCP? Get started with any GCP product for free with a $300 credit.

Need more help?

Our experts will help you build the right solution or find the right partner for your needs.