Protect AI vs Cranium AI
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 Cranium AIleads with “End-to-end AI security and governance platform to discover, monitor, red-team and prove enterprise AI”. The table below compares what each publishes.
Where Protect AI pulls ahead
Publishes support for SOC 2, which Cranium AI does not. Security and ML teams needing to scan and defend models, pipelines, and LLM apps across the AI lifecycle
Where Cranium AI pulls ahead
Publishes support for EU AI Act, ISO/IEC 42001, which Protect AI does not. Enterprises that need to secure, red-team, and prove governance across internal and third-party AI in one platform
Both map to NIST AI RMF, so framework coverage alone will not separate them — the decision usually comes down to who operates the tool and how it fits your existing stack.
| Positioning | End-to-end security for the AI and machine-learning supply chain | End-to-end AI security and governance platform to discover, monitor, red-team and prove enterprise AI |
|---|---|---|
| Category | Red-Teaming & AI Security | Red-Teaming & AI Security |
| Frameworks | NIST AI RMF, SOC 2 | EU AI Act, NIST AI RMF, ISO/IEC 42001 |
| Deployment | SaaS, On-prem, Open-source, API | SaaS, Cloud, API |
| Built for | Security, Data Science / ML, Risk | Security, Risk, GRC, Compliance, Data Science / ML |
| Founded | 2022 | 2023 |
| Headquarters | Seattle, Washington, USA | Short Hills, New Jersey, USA |
| Ownership | Acquired by Palo Alto Networks (announced April 2025, ~$700M); part of Prisma AIRS | Private (venture-backed; spun out of KPMG Studio) |
| Funding | $60M Series B (2024) at ~$400M valuation prior to acquisition | ~$32M total; $25M Series A (Oct 2023) led by Titanium/Telstra Ventures with KPMG and SYN Ventures |
| Pricing | Enterprise licensing; open-source tools (ModelScan, LLM Guard) free | Enterprise subscription; quote-based (annual subscription also listed on Azure/Microsoft marketplaces) |
| Key capabilities |
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| Integrations | Amazon Bedrock, Hugging Face, MLflow / CI-CD pipelines, Major LLM providers, Palo Alto Prisma AIRS | Weights & Biases, Microsoft Azure / Azure Marketplace, MITRE ATLAS, OWASP |
| 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 that need to secure, red-team, and prove governance across internal and third-party AI in one platform |
| 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 | Security- and red-teaming-first orientation means it emphasizes threat testing and monitoring over deep policy/GRC workflow; enterprise pricing is not publicly listed; still a relatively young company with limited publicly named customers. |
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 Cranium AI if enterprises that need to secure, red-team, and prove governance across internal and third-party AI in one platform
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.
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