Fill out this short form to request access for free

Data Scientists will get free compute capacity on AWS to train, package, and deploy machine learning models to showcase the simplicity and speed of A360.AI

Free Compute Capacity Data Scientists can train, package, and deploy ML models for free
Deploy Models FAST

Increase speed to deploy an AI model by 500% - Read our Blog...

Increase Job Satisfaction Increase Data Scientists job satisfaction by 100%

“I tested out the data drift, which actually works great for tabular kinds of problems or in a tabular data.”
Data Scientist


“The whole experimenting feature, all of that worked great. It saves us the effort of doing all the logging, it handles all of that for us. So that worked perfectly. Then you know, the connection to the Jupyter Notebooks, access to the models, the way the models were displayed through the UI, all of that was perfect.”​
Data Scientist


“I thought experiments were great. It really makes it easier for us. So, we don't have to keep track, it keeps track of everything. And it kind of puts everything in its own bucket, so you can easily find it later.”​
Data Science Team Lead


“I really liked how the software is laid out. It's just very easy to navigate through. And the whole thing, it's very aesthetic, which is awesome.” ​
Data Analyst


“The whole data saving feature, like upload the CSV, and then create your parquets. And then stores it, that was also done really well."
Data Science Team Lead

Use this form to request access to A360 AI Community Edition that will enable a data scientist to build/import models, package and deploy models, and monitor models for development environments.

For the A360 AI free trial, we limit the total cloud resources used to less than 1GB.

The following data types are natively supported by A360 AI for experiments, packaging and data drift monitoring. Tabular, Time Series, Text Data 

Other types can be used for training and deployment with additional custom development. 

A360 AI provides a full stable, native and customizable Jupyter Lab environment hosted on the cloud for your ML development needs. 

Python and R programming languages are fully supported for model training and inferencing. 

Our current packaging process uses a GitHub repo to host the deployment script.

Note that we design our ML deployment process to be fast and easy, you will be able to deploy your ML model as endpoint within 10 minutes, we also provide code examples on how to use the endpoint to make real-time model inference. 

1. Please indicate the AI Frameworks you typically use for ML Model development.(Required)
Note that A360 has native support for these frameworks, but you are free to use any other frameworks but may require additional setup.
2. Do you currently package and deploy models to production environments?(Required)
3. Is the data that you would use for training already available or can be uploaded to Snowflake or AWS S3?(Required)
4. Please enter your name(Required)
7. How did you learn about

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