BACK TO NEWS

Protegrity AI Team Edition: Foundation for Zero Model Exposure

By Protegrity
Apr 16, 2026

Summary

5 min
  • Protegrity introduced AI Team Edition to help organizations secure inferencing with zero model exposure:
    The announcement positions the new offering as a way to embed protection directly into AI architecture, helping organizations reduce risk, protect data and knowledge, and move faster with AI at a lower cost.

  • The platform is designed to bring enforceable controls to AI systems from policy creation through deployment:
    Core capabilities highlighted in the post include protection for contextual and operational data, natural-language-driven policy creation, enforcement across pipelines and inference workflows, auditable interactions, and scalable deployment through a Kubernetes-based architecture.

Built from the ground up, Protegrity AI Team Edition secures data and knowledge with semantic encryption  

Menlo Park, CA — Protegrity, a global leader in data and knowledge security, today announced its AI Team Edition, a new paradigm for zero model exposure with secure inferencing that rebalances cybersecurity, especially against Mythos and other leading foundation models, and their ability to upend existing perimeter-based security methods.

Data and knowledge are now “Darwinian principles” in the AI era. If they are not secured or shared properly, they are open to theft and malicious distortion, paving the way for corporate marginalization, perhaps even extinction.

“Knowledge is what forms when facts and transactions meet context,” said Michael Howard, CEO, Protegrity. “It is when repetitive failure informs judgement, when intent guides interpretation. It is inferential, and lives between systems. Protegrity AI Team Edition is effectively a new type of data and knowledge firewall, a product that has the capabilities required to enable the leading organizations of the world to achieve actual AI success.”

Protegrity AI Team Edition addresses the gap between data utility and risk within AI by embedding protection directly into companies’ new AI architecture. Zero model exposure enables faster time-to-value at a fraction of the cost of AI projects. The technology that makes that possible is Protegrity’s semantic preserving encryption which protects the meaning and relationships that power AI systems across knowledge graphs and AI workflows.

Core capabilities include:

  • Data to Knowledge:
    Protection extends beyond traditional categories to include operational, behavioral and contextual data used in AI systems
  • Prompt to Policy:
    Policies can be created from natural language inputs and applied automatically, reducing manual effort and accelerating deployment
  • Upstream to Downstream Enforcement:
    Controls operate directly in data pipelines, analytics engines and inference workflows, adapting to context and role
  • Server to Datacenter:
    Inference securely everywhere via its Kubernetes-based architecture with CI/CD integration enables rapid rollout, updates and scale
  • Developer to Department to Enterprise with Attestation:
    All interactions are validated, logged and auditable across systems
  • Priced to Scale:
    Priced to bring enterprise-grade AI security to organizations of all sizes, starting at a fraction of typical AI infrastructure costs

“Securing AI has become the responsibility of the entire organization, not just security or IT professionals,” said Grace Trinidad, Research Director, Future of Trust, IDC. “Protegrity is providing the tools that enable AI security in a way that makes sense no matter where you are or who you are in the organization.”

Protegrity AI Team Edition is available now.