AIAI Governance StackFree kit

Lakera vs Dynamo AI

Both compete in Runtime Enforcement & Guardrails. Lakera positions itself as “AI-native security platform guarding GenAI apps against prompt attacks and data loss”, while Dynamo AIleads with “Customizable runtime guardrails, evaluation, and red-teaming for enterprise generative and agentic AI”. The table below compares what each publishes.

Where Lakera pulls ahead

Security teams needing continuously updated, model-agnostic runtime protection for GenAI apps

Where Dynamo AI pulls ahead

Regulated and security-sensitive enterprises that need self-hosted, customizable runtime guardrails plus pre-deployment red-teaming for LLM and agentic applications.

Both map to EU AI Act, 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.

PositioningAI-native security platform guarding GenAI apps against prompt attacks and data lossCustomizable runtime guardrails, evaluation, and red-teaming for enterprise generative and agentic AI
CategoryRuntime Enforcement & GuardrailsRuntime Enforcement & Guardrails
FrameworksEU AI Act, NIST AI RMFEU AI Act, NIST AI RMF
DeploymentSaaS, On-prem, APIOn-prem, Cloud, API, SaaS
Built forSecurity, Data Science / MLSecurity, Compliance, Risk, Legal, Data Science / ML
Founded20212021
HeadquartersZurich, SwitzerlandSan Francisco, California, USA
OwnershipAcquired by Check Point Software (announced 2025, ~$300M; deal expected to close Q4 2025)Independent
Funding~$30M total; $20M Series A (2024) led by Atomico with Citi Ventures and Dropbox VenturesApproximately $19-24M total; $15M Series A (Aug 2023). Originally operated as DynamoFL
PricingCommercial SaaS / enterprise licensing (free community tier for Lakera Guard)Not published
Key capabilities
  • Lakera Guard real-time input/output screening
  • Prompt-injection and jailbreak detection
  • PII and data-loss protection
  • Content moderation
  • Gandalf-fed live threat intelligence
  • Automated red teaming (Lakera Red)
  • Real-time customizable guardrails (DynamoGuard)
  • Automated evaluation and red-teaming (DynamoEval)
  • Risk remediation (DynamoEnhance)
  • Agentic AI security (AgentWarden)
  • Hallucination detection with root-cause analysis
  • On-device / in-cluster deployment
IntegrationsOpenAI, Anthropic, Azure OpenAI, LangChain, Model-agnostic REST APIMajor LLM providers, Kubernetes
Notable customersDropbox, Citi, Microsoft (Gandalf for security training)Qualcomm, Lenovo, Intel, Experian, U.S. Army
Best forSecurity teams needing continuously updated, model-agnostic runtime protection for GenAI appsRegulated and security-sensitive enterprises that need self-hosted, customizable runtime guardrails plus pre-deployment red-teaming for LLM and agentic applications.
LimitationsNow part of Check Point, so roadmap and packaging may shift toward that portfolio; focused on security rather than broad GRC/compliance workflow toolingIts Kubernetes-native, self-hosted model requires meaningful engineering resources to deploy and run, making it heavier to adopt than SaaS-only governance tools and less suited to non-technical buyers.

Which should you shortlist?

Choose Lakera if security teams needing continuously updated, model-agnostic runtime protection for GenAI apps

Choose Dynamo AI if regulated and security-sensitive enterprises that need self-hosted, customizable runtime guardrails plus pre-deployment red-teaming for LLM and agentic applications.

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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