Overview of Protegrity AI Team Edition on

Architecture and Design Principles

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Protegrity AI Team Edition delivers core Protegrity capabilities. This includes governance, discovery, protection, privacy, and semantic controls. It is provided in a lightweight, containerized form factor that emphasizes fast deployment, simplified operations, and consistent enforcement of data security policies across environments. It is designed around five engineering goals: ease of deployment, high availability, scalability, extensibility, and maintainability.

Goal	Implementation Details
Ease of Deployment	- OpenTofu templates provision a Kubernetes environment (EKS) with minimal manual intervention. - Helm Charts deploy and configure all components for consistent, reproducible setups. - Because each component runs as a container image, upgrades and patches follow standard CI/CD workflows.
High Availability	- Kubernetes manages service health and redundancy automatically. - No Trusted Appliance Cluster (TAC) required. - No external load balancers required. - No manual replication required.
Scalability	- The system scales horizontally and vertically through Kubernetes-native scale-up and scale-down mechanisms. - Administrators can adjust resources dynamically as workloads grow or shrink without redeployment.
Extensibility	- New capabilities are introduced by adding new container images and Helm configurations. - Allows incremental feature expansion without redesign.
Maintainability	- Kubernetes simplifies lifecycle management. - Updating a container image replaces an older version automatically, avoiding downtime and manual patching.

Protegrity Common Services

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All deployments include a standardized set of common services delivered by a microservices architecture provide routing, security, and audit capabilities for all features and protectors.

Service	Description
Authentication and Authorization	Provides user and service credential validation with role-based access enforcement.
Backup and Restore	Creates periodic backup of the cluster and indexes for restoration during Disaster Management.
Certificate Management	Manages and validates TLS certificates for inbound and inter-service communication.
Common Ingress Controller	The main entry point for all API and service traffic to the cluster.
Insight	Provides logging and auditing capabilities using OpenSearch for event storage and Insight Dashboard for visualization and reporting.

Compatible Features

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The various features compatible with Protegrity AI Team Edition are provided here.

* - Available for purchase as an add-on. Can be installed as an individual product.

Feature	Description
Anonymization	Apply statistical privacy models such as k-anonymity, l-diversity, and t-closeness to sensitive datasets.
Data Discovery	Automatically identify structured and unstructured sensitive data through pattern matching and machine learning classification.
Policy Manager	Define and manage data protection policies that govern tokenization, masking, and anonymization.
Protegrity Agent	Intelligent assistant for automated policy creation, data classification recommendations, and guided configuration of protection workflows.
Semantic Guardrails	Apply contextual and runtime safeguards to AI and analytics workflows to prevent data leakage or misuse.
Synthetic Data	Generate tabular synthetic datasets for development, testing, and AI model validation without exposing real sensitive data.

Protegrity Protectors

Protegrity AI Team Edition protectors enable organizations to embed data protection directly where data is processed, inside applications, analytics engines, or cloud-native data systems. The protectors use the Workbench for obtaining the policy for processing. The Protegrity Agent is available for creating and working with policies in the Workbench.