Protect AI vs Vijil
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 Vijilleads with “Trust infrastructure to make enterprise AI agents secure, reliable, and resilient”. The table below compares what each publishes.
Where Protect AI pulls ahead
Publishes support for NIST AI RMF, SOC 2, which Vijil does not. Security and ML teams needing to scan and defend models, pipelines, and LLM apps across the AI lifecycle
Where Vijil pulls ahead
Teams building enterprise AI agents that need lifecycle testing, hardening, and trust evidence
| Positioning | End-to-end security for the AI and machine-learning supply chain | Trust infrastructure to make enterprise AI agents secure, reliable, and resilient |
|---|---|---|
| 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, API |
| Built for | Security, Data Science / ML, Risk | Security, Data Science / ML, Risk |
| Founded | 2022 | 2023 |
| Headquarters | Seattle, Washington, USA | California, 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 | $23M total; $17M round in November 2025 led by Brightmind Partners with Mayfield and Gradient Ventures, following a $6M seed in 2024 |
| Pricing | Enterprise licensing; open-source tools (ModelScan, LLM Guard) free | Not published |
| Key capabilities |
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| Integrations | Amazon Bedrock, Hugging Face, MLflow / CI-CD pipelines, Major LLM providers, Palo Alto Prisma AIRS | Not published |
| Notable customers | None published | SmartRecruiters |
| Best for | Security and ML teams needing to scan and defend models, pipelines, and LLM apps across the AI lifecycle | Teams building enterprise AI agents that need lifecycle testing, hardening, and trust evidence |
| 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 | Early-stage vendor; detailed framework mappings and integration list are not extensively documented publicly. |
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 Vijil if teams building enterprise AI agents that need lifecycle testing, hardening, and trust evidence
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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