Protect AI vs HiddenLayer
Both compete in Red-Teaming & AI Security. Protect AI positions itself as “End-to-end security for the AI and machine-learning supply chain”, while HiddenLayerleads with “AI detection and response plus red teaming to protect machine learning models and AI products”. The table below compares what each publishes.
Where Protect AI pulls ahead
Publishes support for NIST AI RMF, SOC 2, which HiddenLayer does not. Security and ML teams needing to scan and defend models, pipelines, and LLM apps across the AI lifecycle
Where HiddenLayer pulls ahead
Enterprises and regulated organizations needing runtime protection and detection for production ML models
| Positioning | End-to-end security for the AI and machine-learning supply chain | AI detection and response plus red teaming to protect machine learning models and AI products |
|---|---|---|
| Category | Red-Teaming & AI Security | Red-Teaming & AI Security |
| Frameworks | NIST AI RMF, SOC 2 | None published |
| Deployment | SaaS, On-prem, Open-source, API | SaaS, On-prem, API |
| Built for | Security, Data Science / ML, Risk | Security, Data Science / ML, Risk |
| Founded | 2022 | 2022 |
| Headquarters | Seattle, Washington, USA | Austin, Texas, USA |
| Ownership | Acquired by Palo Alto Networks (announced April 2025, ~$700M); part of Prisma AIRS | Private (VC-backed) |
| Funding | $60M Series B (2024) at ~$400M valuation prior to acquisition | $56M total; $50M Series A in 2023 led by M12 and Moore Strategic Ventures, with Booz Allen, IBM and Capital One Ventures |
| Pricing | Enterprise licensing; open-source tools (ModelScan, LLM Guard) free | Not published |
| Key capabilities |
|
|
| Integrations | Amazon Bedrock, Hugging Face, MLflow / CI-CD pipelines, Major LLM providers, Palo Alto Prisma AIRS | Not published |
| Notable customers | None published | None published |
| Best for | Security and ML teams needing to scan and defend models, pipelines, and LLM apps across the AI lifecycle | Enterprises and regulated organizations needing runtime protection and detection for production ML models |
| Limitations | Now integrated into Palo Alto Networks, so standalone products may converge into Prisma AIRS; breadth means some components (runtime guardrails vs. model scanning) are stronger than others | Historically ML-model centric; buyers seeking full agentic AI governance or compliance certification may need complementary tooling. |
Which should you shortlist?
Choose Protect AI if security and ML teams needing to scan and defend models, pipelines, and LLM apps across the AI lifecycle
Choose HiddenLayer if enterprises and regulated organizations needing runtime protection and detection for production ML models
Neither is a substitute for a governance program. Whichever you pick, you still need people who can define the policies the tool enforces.
AI Governance Tool Selection Kit
A vendor-comparison worksheet plus EU AI Act, NIST AI RMF and ISO/IEC 42001 requirement checklists — so you can shortlist tools against the obligations that actually apply to you.
Free. No spam — unsubscribe anytime.