AIAI Governance StackFree kit

Robust Intelligence vs Mindgard

Both compete in Red-Teaming & AI Security. Robust Intelligence positions itself as “AI Firewall and automated model validation to secure AI from build to production”, while Mindgardleads with “Continuous automated AI red teaming and security testing for enterprise AI systems”. The table below compares what each publishes.

Where Robust Intelligence pulls ahead

Publishes support for NIST AI RMF, which Mindgard does not. Enterprise security and ML risk teams wanting adversarial testing plus runtime protection mapped to AI-security standards

Where Mindgard pulls ahead

Publishes support for SOC 2, which Robust Intelligence does not. Enterprise security teams needing continuous, attacker-perspective red teaming and testing of LLMs and AI systems

Robust Intelligence
Mindgard
PositioningAI Firewall and automated model validation to secure AI from build to productionContinuous automated AI red teaming and security testing for enterprise AI systems
CategoryRed-Teaming & AI SecurityRed-Teaming & AI Security
FrameworksNIST AI RMFSOC 2
DeploymentSaaS, On-prem, APISaaS, API
Built forSecurity, Data Science / ML, RiskSecurity, Data Science / ML, Risk
Founded20192022
HeadquartersSan Francisco, California, USABoston, USA (with London, UK office)
OwnershipAcquired by Cisco (2024, reported ~$400M); now part of Cisco AI DefensePrivate (VC-backed)
Funding~$44M raised prior to acquisition; valued above $200MOver $11.6M raised, including an $8M round in December 2024 led by .406 Ventures, with IQ Capital, Lakestar, Atlantic Bridge and WillowTree Investments
PricingEnterprise licensing (now sold within Cisco AI Defense)Not published
Key capabilities
  • AI Firewall runtime input/output protection
  • Algorithmic red teaming
  • Automated model validation and stress-testing
  • Prompt-injection and jailbreak defense
  • OWASP LLM and MITRE ATLAS mapping
  • Continuous production monitoring
  • Automated AI red teaming
  • AI discovery and reconnaissance
  • Attack surface mapping
  • Vulnerability assessment
  • Model scanning
  • Runtime protection
IntegrationsCisco Security Cloud / AI Defense, Major LLM providers, ML pipelines and model registriesOpenAI, Anthropic, AWS, Docker, Burp Suite, CI/CD pipelines
Notable customersNone publishedNone published
Best forEnterprise security and ML risk teams wanting adversarial testing plus runtime protection mapped to AI-security standardsEnterprise security teams needing continuous, attacker-perspective red teaming and testing of LLMs and AI systems
LimitationsAbsorbed into Cisco, so it is increasingly delivered as Cisco AI Defense rather than a standalone product; enterprise-oriented, less accessible to small teamsFocused on security testing rather than broad AI governance or policy management; some framework-specific compliance mapping is not detailed publicly.

Which should you shortlist?

Choose Robust Intelligence if enterprise security and ML risk teams wanting adversarial testing plus runtime protection mapped to AI-security standards

Choose Mindgard if enterprise security teams needing continuous, attacker-perspective red teaming and testing of LLMs and AI systems

Neither is a substitute for a governance program. Whichever you pick, you still need people who can define the policies the tool enforces.

Full Robust Intelligence profile →Full Mindgard profile →

AI Governance Tool Selection Kit

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