Installation

Private AI is primarily designed to be self-hosted by the user via a container, to provide users with the best possible experience in terms of latency and security. It would be counter-productive to send sensitive data across the Internet to a 3rd party system for the purpose of preserving privacy. It also ensures that Private AI never sees or handles customer data, unlike cloud APIs which usually retain a right to use any data passed through the system for service improvements and ML model development.

Instead of running the container locally, it is also possible to use a cloud version of the API, hosted at the following endpoint: https://api.private-ai.com/deid/

Custom integrations that do not rely on Docker can also be delivered upon request.

Installation is organized as follows:

• Prerequisites and System Requirements details the minimum and recommended hardware to run the container on.
• Grabbing the Image describes how to load the Private AI image.
• Running the Container covers how to create and run the container on your local machine.
• Environment Variables provides a comprehensive list of supported envrionment variables that you can configure.
• Deploying into Production describes how to run the container in production with orchestrators such as AWS ECS.
• Kubernetes Setup Guide is a self-contained guide on how to run the container using Kubernetes.
• Benchmarks provides some performance numbers on the CPU and GPU containers.
• Concurrency talks about recommended concurrency settings.
• Security notes about security considerations taken by the Private AI team.