Protegrity AI Team Edition

Govern Agents.
Secure Compute.

Protegrity AI Team Edition brings bring(s) zero-trust data protection to departmental data and AI workflows. Empower teams with the highest-precision data, enable high trust AI, and secure compute engines–the analytical workloads of choice.

Proven at Global Scale

Our customers choose Protegrity to give every team safe access to high-precision data, trusted model outputs, and streamlined compliance.

Secure Agentic AI, Models & Tooling

Embedded and
Semantic Controls
for High Precision Data

Protegrity AI Team Edition enables trustworthy agentic
workflows – agnostic to frameworks, vendors, and hyperscalers–with centralized policy and distributed, inline enforcement.

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Data Discovery & Classification

Identify, tag, and classify sensitive data – including PII, PCI, PHI, & IP – in structured and unstructured formats in the flow of data before it’s used in models or analysis.

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Centralized Policy, Distributed Enforcement

Define once, secure everywhere with protection that adapts based on data purpose and context –tokens for referential integrity, masked data for least-privilege consumption.

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Semantic Runtime

Guardrails judge accuracy and evaluate interactions between users, data, and AI based on risk thresholds – blocking unsafe content and preventing information leakage.

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Semantic Anonymization

Transform datasets and generalize identifiers to anonymize sensitive information for privacy-enforced analytics and AI workflows.

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Privacy-Enabled Synthetic Data

Generate realistic datasets by modeling production data to create non-sensitive datasets that mirror statistical properties for use in model training and test data.

Features are deployable via container and API, supporting seamless integration into notebooks, AI pipelines, and agentic workflows.

Start with one project, expand when ready

Developer-Friendly. Team-Scoped. Enterprise-Ready.

Protegrity AI Team Edition delivers a unified set of controls designed for real-time data protection in AI and analytics environments.

Protegrity

AI Team Edition

Govern agents and secure departmental workloads with data-level protection and simple policy controls. Teams innovate faster with trustworthy inputs and auditable outputs. Work with complete, context-rich data while enforcing consistent controls—so teams deliver accurate results, share safely, and lower risk.

Protegrity

AI Enterprise Edition

Enterprise-wide control for AI and analytics. Standardize protection, visibility, and compliance across hybrid environments—so you can unlock sensitive data at scale without compromising trust. Centralize data-centric security across clouds, platforms, and business units. One place to define and prove policy, scale safely, and meet regulatory obligations while enabling AI everywhere.

Embedded and semantic controls ensure AI-ready data that knows its own security and purpose

AI IS OUTPACING TRADITIONAL
SECURITY APPROACHES

Agents don’t follow application, infrastructure or network boundaries. They follow data and intent with runtime context that mixes sensitive and public data. But data leakage, exfiltration, and injection fears delay launches and limit success because a lack of adaptive enforcement and scalable governance leads to higher complexity.

Secure GenAI Without Blocking Innovation

Runtime protection across prompts, AI processing, and outputs

Protegrity AI Team Edition intercepts model input/output to enforce policies—detecting PII, blocking unsafe completions, and preserving security without breaking workflows. Tokenization protects data sent to vector stores or LLMs.

Integrate Protection at Every Layer

SDKs, APIs, and native protectors for analytics and AI stacks

Protegrity AI Team Edition integrates directly into your analytics and AI stack. REST APIs and a Python SDK connect to pipelines and services. Application Protectors support Java, .NET, and Python environments. Big Data connectors work with Databricks, EMR, and CDP, while cloud data protectors secure Snowflake, Redshift, and Athena—all without requiring ETL rewrites or architectural changes.

Track, Prove, and Report What’s Protected

Built-in visibility without custom wiring

Every action—tokenization, classification, policy enforcement—is logged to OpenSearch and visualized in OpenDashboards. Teams get immediate visibility into what’s protected, how it was accessed, and when—making audit prep and security reviews straightforward.

Containerized deployment with minimal overhead

Kubernetes-Native, CI/CD-Ready

  • Infrastructure Setup

    Terraform

  • Provision AWS Environment

  • AWS VPC

  • EKS/ECS/Docker Compose

  • IAM Roles/Permissions

  • Platform Install

    Helm

  • Install AI Team Edition Services

  • Ingress Controller

  • TLS Cert Manager

  • Policy Manager

  • Protection Services

  • Audit Logging

  • Deployment Result
  • Running Cluster

  • Tokenization, Guardrails, Discovery Line

  • Routing Layer

  • All Services Containerized

  • Updates Via Container Image Refresh

No patching or appliance updates required

Runs fully within your AWS account

CI/CD-ready, container-native deployment

Deploy Protegrity AI Team Edition using infrastructure-as-code templates—Terraform provisions your AWS environment and Kubernetes cluster (EKS, ECS, or Docker Compose), while Helm Charts configure and install the platform’s microservices. Ingress, TLS management, routing, and audit logging are built in. Updates are applied by refreshing container images—no patching or appliance maintenance required.

VISIBILITY & CONTROL

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