Lakera

Overview

Lakera is an AI-native security platform designed to protect enterprises from the unique risks of generative AI. Traditional security tools only control what AI can access; Lakera goes further by controlling what AI actually does. Using a context-aware, runtime-first approach, it safeguards AI applications, enterprise AI agents, and employee AI usage against prompt injection, data leakage, jailbreaks, toxic content generation, and indirect or multilingual attacks. The platform is built to keep pace with rapidly evolving GenAI threats without slowing down development or forcing teams to change how they build.

The core engine learns from more than 1 million hackers and red-teamers worldwide, observing over 100 languages in real time. This intelligence is delivered with sub-50 ms runtime latency, enabling protection at scale for even the largest prompts and context windows. Lakera’s context-aware detection reduces risk by 3–4 orders of magnitude while achieving a production false positive rate as low as 0.01%. It is multimodal and model-agnostic, securing chatbots, audio bots, and other AI interfaces across any LLM or agent framework, and can scale effortlessly from zero to hundreds of prompts per second.

The platform offers three primary product areas. AI Agent Security provides real-time runtime protection for AI applications, including threat detection, prompt attack prevention, and data leakage protection. Workforce AI Security secures how employees use AI by discovering shadow AI across browsers and applications, enforcing context-aware data protection, and applying granular policies based on user, app, and action. AI Red Teaming delivers risk-based testing for GenAI applications, simulating direct and indirect attacks, managing vulnerabilities by risk, and providing collaborative remediation guidance. Lakera also offers an expert-led AI Red Teaming service for adversarial testing.

Deployed via an API-first, cloud-native architecture, Lakera integrates horizontally with enterprise systems and provides central policy control without requiring code changes. It is trusted by Fortune 500 companies, regulated financial institutions, and AI startups. The platform is recognized by industry analysts and referenced in OWASP LLM security guidance, Gartner GenAI TRiSM innovation research, and World Economic Forum discussions. By combining continuous threat intelligence, ultra-low latency, and enterprise-grade scalability, Lakera enables teams to launch AI applications confidently, satisfy compliance requirements, and accelerate GenAI innovation securely.

Core capabilities

Real-Time Threat Detection

Runtime protection for AI applications that detects and blocks prompt injection, jailbreaks, and data leakage before they impact business.

AI Agent Security

Secures enterprise AI agents and LLM-powered applications with real-time threat monitoring, prompt attack prevention, and data leak protection.

Workforce AI Security

Discovers shadow AI across browsers and applications, with context-aware data protection and granular policy controls by user, app, and action.

AI Red Teaming

Risk-based adversarial testing for GenAI applications, including direct and indirect attack simulations, vulnerability management, and remediation guidance.

Ultra-Low Latency

Sub-50 ms runtime latency ensures security does not degrade user experience, even for very large prompts and context windows.

Multimodal and Model Agnostic

Protects chatbots and audio bots across any model or agent framework, with support for expanding input modalities.

Context-Aware Precision

Uses a unique context-aware approach to reduce risk by 3–4 orders of magnitude while maintaining a 0.01% production false positive rate.

Continuous Learning

Learns from over 1 million hackers and observes 100+ languages in real time to adapt to emerging GenAI threats without manual updates.

Central Policy Control

Customize and enforce security policies horizontally across applications without changing code.

Enterprise-Grade Integration

API-first, cloud-native architecture with easy deployment, horizontal scaling, and seamless enterprise integration.

Use cases

Securing conversational AI chatbots against prompt injection, jailbreaks, and data leakage in production.

Protecting document-based RAG agents from indirect prompt injection and unauthorized data access.

Governing employee use of public GenAI tools and detecting shadow AI across enterprise browsers and applications.

Red teaming GenAI applications before launch to identify vulnerabilities and remediate risks.

Enforcing data protection, privacy, and compliance in banking, financial services, and other regulated industries.

Safeguarding enterprise AI agents that interact with external tools, databases, and MCPs.

Monitoring and defending AI workloads in real time to meet strict security and reliability standards.