Lakera is an AI security platform that protects LLM applications from prompt injection, jailbreaks and data leaks with real-time guardrails.
Lakera builds defenses for the new attack surface of generative AI. Its flagship products include Lakera Guard, an API that screens prompts and responses for injection attacks, toxic content and data loss in milliseconds, and interactive training that teaches developers to think like attackers. Powered by continuously updated threat intelligence, it adapts to new jailbreak techniques as they emerge.
Guard is model-agnostic and drops in front of any LLM application — chatbots, RAG pipelines, agents — adding minimal latency. The team also maintains Lakera’s well-known prompt injection knowledge base, which is widely used as a reference in the AI security community.
Lakera’s detection models are trained on a continuously updated corpus of attack techniques gathered from research and real-world traffic, which keeps pace with rapidly evolving jailbreak methods. The guardrail API screens both prompts and responses, catching injection attempts, toxic content and sensitive data exposure with low latency. For teams building RAG systems and agents, Lakera provides protection at the exact points where untrusted input meets model instructions.
Lakera Guard offers a free tier for developers and evaluation, with usage-based paid plans and enterprise options for scale and customization.
Teams shipping LLM-powered products who need production guardrails against prompt-based attacks and data leakage.
Yes, a free developer tier lets you integrate and test Lakera Guard; production scale requires a paid plan.
Yes — Lakera Guard is an API-first product designed to sit in the request path of LLM applications.
Its specialized prompt-injection intelligence and speed make it more effective than generic content filters.
Yes — Lakera Guard detects sensitive information in prompts and responses, supporting data loss prevention policies alongside injection defense.
Lakera is used wherever untrusted input reaches a language model. Teams deploy Lakera Guard in front of customer support chatbots to stop users from hijacking system instructions, inside retrieval-augmented generation pipelines to neutralize malicious content embedded in documents, and around autonomous agents that execute tools and actions. Security teams also use it to enforce content policies and prevent sensitive corporate data from leaving through prompts. Because it operates as a lightweight API check, most organizations integrate it within days and simply monitor blocked-attack dashboards from then on.