Lakera

✓ Editorially verified

Runtime security and guardrails for GenAI apps, agents, and RAG systems.

Freemium· Free community/developer tier at platform.lakera.ai; paid Enterprise plans (custom pricing, contact sales). No public price list.EvaluationProprietary in-house classifiers; model-agnostic (works in front of GPT-4o, Claude, Gemini, Llama, and custom LLMs)

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Best for

Security, platform, and applied-AI teams shipping customer-facing LLM chatbots, RAG systems, or agents at enterprise scale who need governed, low-latency guardrails against prompt injection and data leakage.

Skip if

Solo developers, hobby projects, or early prototypes on a tight budget — the enterprise sales motion and lack of public pricing make it a poor fit until you have real production traffic and compliance requirements.

Lakera is an AI-native security and guardrails platform built to protect production LLM applications, RAG pipelines, and autonomous agents from prompt injection, jailbreaks, data leakage, toxic content, and other GenAI-specific threats. Its flagship product, Lakera Guard, sits in front of (or beside) your model calls as a low-latency policy engine — the company advertises sub-50ms overhead — and classifies each inbound prompt, outbound completion, and tool-call payload against a library of attack detectors and configurable policies. It is model-agnostic and works with OpenAI, Anthropic, open-weights models, and internal fine-tunes, and supports 100+ languages so it can be dropped in front of multilingual assistants without retraining per locale.

Beyond runtime blocking, the platform includes Shadow AI discovery to surface unsanctioned employee AI usage, context-aware data protection to prevent PII/secret leakage, granular per-app policy controls, and centrally managed rules that can be updated without shipping application code. Threat intelligence is fed in part by Gandalf, Lakera's famous public prompt-injection challenge, which continuously generates novel adversarial prompts that harden the detectors.

Typical workflows: wrap an internal chatbot or customer-facing agent with Guard's REST API so every turn is screened; enforce a GenAI gateway policy across many teams' LLM traffic; add guardrails to a RAG stack to stop indirect injections hidden in retrieved documents; monitor and audit agent tool-calls for exfiltration attempts. Lakera is now part of Check Point Software following a 2025 acquisition, and is primarily sold to security-conscious enterprises and regulated industries deploying GenAI at scale.

Editor's take

Lakera is one of the most credible names in GenAI runtime security, and Gandalf gives its detectors a genuine data moat competitors can't easily replicate. If you're a security team being asked to sign off on a customer-facing LLM app, this is a serious answer. The trade-off is a closed, quote-only enterprise product — great for CISOs, frustrating for developers who want to kick tires without a sales call.

— The AI Tool Bible editorial team

Pros

✅ Purpose-built for GenAI threats — prompt injection, jailbreaks, PII leakage, and indirect-injection in RAG contexts
✅ Very low added latency (sub-50ms) makes it viable inline in front of production chat and agent traffic
✅ Model-agnostic and multi-lingual (100+ languages), so it fits mixed OpenAI/Anthropic/open-source stacks
✅ Detectors are hardened by data from Gandalf, a large-scale adversarial red-team game with millions of attack prompts
✅ Central policy management and Shadow AI discovery give security teams governance beyond just runtime blocking
✅ API-first with SDKs and framework integrations, so it drops into existing LangChain / gateway architectures
✅ Backed by Check Point post-acquisition, which reassures enterprise procurement and compliance reviewers

Cons

⚠️ Pricing is not public — Enterprise plans are quote-only, which slows evaluation for smaller teams
⚠️ Closed-source, so you cannot self-host the detectors or fully audit their logic
⚠️ Adds an external network hop for every LLM call unless you deploy a regional/edge instance
⚠️ Overlaps with newer guardrail options (NVIDIA NeMo Guardrails, Protect AI, Guardrails AI) that may be cheaper or OSS
⚠️ Effectiveness against novel jailbreaks depends on Lakera's detector update cadence, which is a vendor black box
⚠️ Overkill for hobby projects or prototypes that don't yet handle sensitive data or untrusted inputs

Use cases

Prompt injection defense for chatbotsRAG guardrails against indirect injectionAgent tool-call abuse monitoringPII and secret leakage preventionJailbreak and policy-violation blockingMultilingual content moderation for LLM appsShadow AI discovery inside enterprisesGenAI gateway policy enforcementLLM red-teaming and adversarial evaluationCompliance auditing of LLM traffic