AIAI Governance StackFree kit

Robust Intelligence vs Giskard

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 Giskardleads with “Open-source and enterprise platform for testing and red-teaming LLM agents”. The table below compares what each publishes.

Where Robust Intelligence pulls ahead

Enterprise security and ML risk teams wanting adversarial testing plus runtime protection mapped to AI-security standards

Where Giskard pulls ahead

Publishes support for EU AI Act, which Robust Intelligence does not. ML, quality, and risk teams wanting open-source-first, framework-aligned LLM testing and continuous red teaming

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.

Robust Intelligence
Giskard
PositioningAI Firewall and automated model validation to secure AI from build to productionOpen-source and enterprise platform for testing and red-teaming LLM agents
CategoryRed-Teaming & AI SecurityRed-Teaming & AI Security
FrameworksNIST AI RMFEU AI Act, NIST AI RMF
DeploymentSaaS, On-prem, APIOpen-source, SaaS, On-prem, API
Built forSecurity, Data Science / ML, RiskData Science / ML, Risk, Compliance
Founded20192021
HeadquartersSan Francisco, California, USAParis, France
OwnershipAcquired by Cisco (2024, reported ~$400M); now part of Cisco AI DefenseIndependent, venture-backed (Y Combinator alumnus)
Funding~$44M raised prior to acquisition; valued above $200MSeed funding (reported ~$2-3M+); investors include Y Combinator, Elaia, and others
PricingEnterprise licensing (now sold within Cisco AI Defense)Open-source library (free); Giskard Hub commercial enterprise subscription
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
  • Open-source LLM/model vulnerability scanning
  • Automated test-suite generation
  • Continuous red teaming
  • Hallucination and prompt-injection testing
  • Robustness and bias evaluation
  • Business-domain test management (Giskard Hub)
IntegrationsCisco Security Cloud / AI Defense, Major LLM providers, ML pipelines and model registriesHugging Face, LangChain, MLflow, Common ML frameworks, Major LLM providers via API
Notable customersNone publishedNone published
Best forEnterprise security and ML risk teams wanting adversarial testing plus runtime protection mapped to AI-security standardsML, quality, and risk teams wanting open-source-first, framework-aligned LLM testing and continuous red teaming
LimitationsAbsorbed into Cisco, so it is increasingly delivered as Cisco AI Defense rather than a standalone product; enterprise-oriented, less accessible to small teamsTesting/evaluation focus rather than inline runtime enforcement; smaller company and funding base; enterprise features concentrated in the paid Hub tier

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 Giskard if mL, quality, and risk teams wanting open-source-first, framework-aligned LLM testing and continuous red teaming

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 Giskard profile →

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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