What is
Protect AI
?
Most platform initiatives fail the same way: they start too big, get funded like projects instead of products, build for too long without testing with users, and confuse renaming an infrastructure team with building a platform team. Instead, start small, learn fast and scale deliberately.
At a glance
Attribute | Value |
|---|---|
Primary use case | Discover, assess and secure AI agents, applications, models and data across the AI lifecycle |
Deployment type | Fully managed runtime security, container deployment profiles, and Linux/KVM cluster deployment |
Pricing model | Token-based API licensing; prices not specified |
API compatibility | OAuth 2.0 |
Supported integrations | Microsoft Foundry, Linux/KVM, next-generation firewalls |
Source type | Closed |
Cloud provider | Cloud Agnostic |
Ideal team size | Enterprise teams |
Onboarding time | Instant deployment claimed for Managed AI Runtime Security; overall onboarding time not specified |
AEP branch | Agent Infrastructure |
AEP category | Governance |
AEP subcategory | Agent Security |
AEP detail | Compliance & Posture |
Profile
Compliance & Posture is the most specific AEP level for Protect AI. The platform provides visibility into AI agents, applications, and models and how they connect across an environment. It supports ongoing assessment of AI applications and agents, permission controls, and real-time security-posture monitoring.
Protect AI also provides runtime safeguards for AI interactions, including controls intended to block prompt injections and data leaks. The platform's listed capabilities span AI Gateway, Agent Security, AI Red Teaming, AI Runtime Security, AI Model Security, and AI Posture Management. Deployments include managed runtime security, container deployment profiles, and Linux/KVM cluster deployment.
Focus
Protect AI is intended for enterprise teams seeking to discover, assess, and secure AI agents, applications, models, and data across the AI lifecycle. It addresses limited visibility into AI activity and risks by identifying AI assets and their connections, assessing application and agent security, and monitoring AI behavior during live interactions.
Background
The available company-background research does not establish the company's founding, funding history, or open-source contributions. The product website identifies Prisma AIRS as a Palo Alto Networks platform, but the supplied research provides no further verified company-history details.
Features
AI discovery
Discovering AI assets helps teams gain visibility into shadow AI and understand how agents, applications, and models connect across an environment. The platform describes discovery of AI agents, apps, and models.
AI posture management
Assessing AI components helps teams monitor security posture and access to deployed models. The platform provides visibility into AI data used for training or inference, the integrity of AI agents and applications, and access to deployed models.
Agent security
Verifying agent identities and enforcing real-time security helps prevent unauthorized actions as teams move agents from pilot to production. The platform lists agent identity verification and real-time security enforcement as Agent Security capabilities.
AI runtime security
Monitoring AI behavior helps prevent manipulation, data exposure, and unsafe actions during live interactions. Runtime security applies safeguards to AI interactions, including a fully managed firewall offering described as blocking prompt injections and data leaks.
AI red teaming
Simulating real-world attacks helps teams proactively identify and address security loopholes in AI agents and applications. The platform lists support for multi-turn attacks and testing autonomous and multi-agent systems.
AI model security
Scanning third-party models helps teams identify vulnerabilities before adoption. The platform names model tampering, malicious scripts, and deserialization attacks as examples of issues it scans for.
Toxicity reporting
Classifying toxicity gives teams categorized reporting on detected content. Reporting classifies toxicity into eight categories.
Pros and cons
Pros
Combines discovery, posture assessment, red teaming, model scanning, and runtime security capabilities across the AI lifecycle.
Includes protections for runtime threats such as prompt injection, data leaks, manipulation, data exposure, and unsafe actions.
Toxicity reporting classifies content into eight categories.
Offers a fully managed runtime security option, container deployment profiles, and Linux/KVM cluster deployment.
Cons
Token-based API licensing is listed, but prices are not specified in the available information, making costs difficult to assess from the supplied materials.
Instant deployment is claimed for Managed AI Runtime Security, but an overall onboarding time is not specified.
The available research does not establish the product's open-source contributions or provide product-specific independent user-review findings.
FAQs
Frequently asked questions
How does Protect AI work?
Protect AI discovers AI agents, applications and models, assesses security posture and permissions, and applies controls to AI interactions, including safeguards against prompt injections and data leaks.
Which integrations does Protect AI support?
Protect AI lists Microsoft Foundry, Linux/KVM, next-generation firewalls as supported integrations. Protect AI lists OAuth 2.0 as its API compatibility.
Which deployment options does Protect AI offer?
Protect AI supports Fully managed runtime security, container deployment profiles, and Linux/KVM cluster deployment.
What does Protect AI cost?
Protect AI uses Token-based API licensing; prices not specified.
How long does onboarding take for Protect AI?
Protect AI's onboarding time is listed as: Instant deployment claimed for Managed AI Runtime Security; overall onboarding time not specified.
