Migrating to AI Team Edition

Switch from the AI Developer Edition to AI Team Edition.

1: Migrating Python Modules
2: Migrating Java Libraries

In AI Developer Edition, data requiring encryption is processed through the Protegrity server. This is suitable for development and testing but lacks the scalability and centralized management needed for production environments. To meet enterprise requirements such as robust logging, advanced security, and modular feature deployment, upgrade to AI Team Edition. The AI Team Edition leverages NFA (New Foundational Architecture) which is a Kubernetes-based, cloud-native framework that enables secure, scalable operations and policy enforcement. Unlike traditional setups that rely on ESA (Enterprise Security Appliance), AI Team Edition simplifies architecture by using NFA for collaborative, high-performance environments without the complexity of appliance clusters.

For more information about the AI Team Edition, refer to the AI Team Edition documentation.

Policy migration is not supported. Data protected in AI Developer Edition cannot be unprotected with the policy in AI Team Edition.

Key Advantages of AI Team Edition Over AI Developer Edition

Deployment and Architecture
Team Edition is container-based and built on a microservices architecture, enabling fast deployment, simplified operations, and native integration with CI/CD pipelines. This aligns with modern DevOps practices and scales easily across environments.
Developer Edition, by contrast, is primarily API-focused and intended for prototyping and development, not production. It uses a protector model and cannot go into production environments.
Feature Set
AI Team Edition includes advanced capabilities such as:
- Data Discovery and Classification for sensitive data (PII, PCI, PHI, IP).
- Semantic Guardrails to enforce safe AI interactions.
- On-demand Anonymization and Privacy-Safe Synthetic Data generation.
- Integrated policy management and governance for compliance.
Developer Edition offers the basic features of these for developers to experiment. It lacks enterprise-grade security and compliance features.
Use Case and Audience
Team Edition is designed for small to mid-sized teams or departmental deployments that need production-ready data protection for AI and analytics workflows. It supports multiple protectors, enabling broader use cases beyond development.
Developer Edition is strictly for initial development and prototyping; it cannot be scaled for production workloads.
Security and Compliance
Team Edition embeds security directly into AI workflows, ensuring compliance without slowing innovation. It uses unique key material per customer, supports External Initialization Vectors (EIV), and enforces policy encryption over TLS.
Developer Edition uses shared key material and mock protectors, making it unsuitable for production-grade security.
Cost and Scalability
Team Edition offers a lower total cost of ownership for departmental deployments and can scale into Enterprise Edition later.
Developer Edition is free for experimentation but has no upgrade path for assets created during development; moving to Team or Enterprise requires reconfiguration.

1 - Migrating Python Modules

Steps for updating the Python modules.

Note: When the policy is set up on the AI Team Edition, ensure that the same data elements added for the AI Developer Edition are used. For more information about the data elements policy, refer to Policy Definition.
If you use different data elements while creating the policy, then modify the data elements used in the AI Developer Edition accordingly before running the modules.

Install and set up the New Foundational Architecture (NFA) and AI Team Edition using the steps from the NFA documentation and the respective feature documentation.
Select the venv where protegrity-developer-python is installed.
Install Application Protector Python using the steps from the Application Protector Python documentation.
Note:
When prompted for the ESA IP address, enter the IP address of the NFA ESA. Similarly, when prompted for the ESA listening port number, enter 25400. This IP address and the port number enables the protector to integrate with the NFA ESA.
After installation, the AP Python module of AI Developer Edition is replaced with the AP Python module of AI Team Edition.
Run the samples.

2 - Migrating Java Libraries

Steps for updating the Java libraries.

Note: When the policy is set up on the AI Team Edition, ensure that the same data elements added for the AI Developer Edition are used. For more information about the data elements policy, refer to Policy Definition.
If you use different data elements while creating the policy, then modify the data elements used in the AI Developer Edition accordingly before running the modules.

Install and set up the New Foundational Architecture (NFA) and AI Team Edition using the steps from the NFA documentation and the respective feature documentation.
Install Application Protector Java libraries using the steps from the Application Protector Java documentation.
Note: When prompted for the ESA IP address, enter the IP address of the NFA ESA. Similarly, when prompted for the ESA listening port number, enter 25400. This IP address and the port number enables the protector to integrate with the NFA ESA.
Include the ApplicationProtectorJava.jar in the classpath of your applications.
Navigate to the location where the AI Developer Edition is cloned.
Go to the protegrity-developer-edition/samples/java directory.
a. Update the pom.xml and the application-protector-java dependency.
```
```
<dependency>
    <groupId>com.protegrity</groupId>
    <artifactId>application-protector-java</artifactId>
    <version>1.0.1</version>
    <scope>system</scope>
    <systemPath>/opt/protegrity/sdk/java/lib/ApplicationProtectorJava.jar</systemPath>
</dependency>
```
```
Note: The AP Java libraries are expected to be in the default path /opt/protegrity/sdk/java/lib/. If the installation uses a different directory, update the environment or configuration so the system can locate the correct JAR files.
b. Run the following command.
```
```
./mvnw clean package
```
```
c. Update the sample shell script to include ApplicationProtectorJava.jar in the classpath.
d. Run the samples.