Lakera

Lakera delivers real-time threat detection, privacy, and compliance, offering a powerful defense for AI systems.

Free Triallakera.aiJun 4, 2026

Real-time Threat Detection

Continuously monitors AI interactions to instantly identify and block prompt injections, jailbreaks, and insecure or harmful content generation.

Lakera Guard

A lightweight, low-latency security API that screens inputs and outputs in real time, catching toxic language, prompt attacks, and off-topic content without disrupting the user experience.

Lakera Red

An advanced red teaming tool that simulates adversarial attacks on your AI applications, helping you find and fix security gaps before they reach production.

Lakera PII Detection

Automatically identifies and masks personally identifiable information (PII) and sensitive data flowing through AI systems, supporting compliance with global privacy regulations.

Comprehensive Threat Intelligence Database

Backed by a continuously updated knowledge base of attack patterns, known exploits, and emerging threats tailored specifically to large language models.

Flexible Deployment Options

Available as a cloud-based service or self-hosted solution, enabling organizations to meet data residency, latency, and security policy requirements.

What is Lakera?

Lakera is positioned as the world’s most advanced AI security platform, purpose-built to protect organizations from the unique threats that come with generative AI applications. The platform delivers a suite of specialized security products—Lakera Guard, Lakera Red, and Lakera PII Detection—that cover the entire AI lifecycle, from development through deployment. It helps enterprises and developers detect and stop prompt injections, prevent sensitive data leakage, ensure model output stays on-brand and safe, and simulate attacks to uncover vulnerabilities before they can be exploited.

Core Features

Real-time Threat Detection: Continuously monitors AI interactions to instantly identify and block prompt injections, jailbreaks, and insecure or harmful content generation.
Lakera Guard: A lightweight, low-latency security API that screens inputs and outputs in real time, catching toxic language, prompt attacks, and off-topic content without disrupting the user experience.
Lakera Red: An advanced red teaming tool that simulates adversarial attacks on your AI applications, helping you find and fix security gaps before they reach production.
Lakera PII Detection: Automatically identifies and masks personally identifiable information (PII) and sensitive data flowing through AI systems, supporting compliance with global privacy regulations.
Comprehensive Threat Intelligence Database: Backed by a continuously updated knowledge base of attack patterns, known exploits, and emerging threats tailored specifically to large language models.
Flexible Deployment Options: Available as a cloud-based service or self-hosted solution, enabling organizations to meet data residency, latency, and security policy requirements.
LLM-Agnostic Integration: Works with a wide range of large language models and AI frameworks, so teams can secure their applications regardless of the underlying model provider.

Use Cases & Considerations

Use Cases

Securing Customer-Facing Chatbots: Prevent prompt injection and jailbreak attempts in real time, ensuring that chatbots stick to their intended purpose and never leak system prompts or sensitive data.
AI Red Teaming for Product Releases: Use Lakera Red to simulate sophisticated adversarial attacks during the QA cycle, giving security and product teams confidence that the AI feature is robust before launch.
PII and Sensitive Data Leakage Prevention: Automatically scan both user prompts and model responses to detect and redact personal information, helping organizations meet GDPR, HIPAA, or SOC2 requirements.
Content Moderation in Generative Apps: Block toxic, hateful, or NSFW content at the output level, making AI-generated text, images, or interactions safe for users in sensitive industries like education or healthcare.
AI Security Audit for LLM Builders: Provide auditable security assurances to clients by integrating Lakera’s threat detection into the API layer, demonstrating a proactive security posture.
Research and Education on AI Threats: Academic institutions and research labs use Lakera to study adversarial AI behavior, test defense mechanisms, and teach students about real-world AI security challenges.

Limitations & Considerations

Learning Curve for Newcomers: Teams without prior AI security experience may need time to understand the toolkit’s full capabilities and how to interpret threat alerts effectively.
Pricing Opacity: The lack of public, tiered pricing can make it difficult for small startups to budget without initiating a sales conversation.
Integration Breadth: While API and self-hosted options are robust, native integrations with some low-code platforms or niche AI orchestration tools are still limited.
Dependency on Rapid Threat Updates: Lakera’s strength relies on continuously updated threat intelligence; if internal update processes lag, the protection may be slightly less effective against zero-day style attacks (though this is common across security platforms).
False Positives: Overly aggressive content filtering thresholds can erroneously block legitimate user requests; fine-tuning is required for each application’s context.

How to use Lakera

Sign up for a free trial: Create an account on the Lakera website to get immediate access to the Lakera Guard API and test its security features against your own AI workflows.
Integrate the Guard API: Add a few lines of code to your existing LLM pipeline (Python, JavaScript, or cURL). Incoming prompts and model outputs are routed through Lakera Guard for real-time analysis.
Configure PII detection and content policies: Within the dashboard, define which types of PII to detect (names, emails, credit cards, etc.) and adjust content safety thresholds to match your organization’s risk tolerance.
Run a red teaming exercise: Use Lakera Red to launch simulated attacks against your AI endpoints. Review the identified vulnerabilities and prioritize fixes based on severity and potential impact.
Deploy to production: Once you're confident in your security rules and settings, switch to a production plan and deploy Lakera in your live environment—either via the cloud API or a self-hosted instance.
Monitor and iterate: Use the analytics dashboard to track blocked threats, view statistics on PII leaks, and fine-tune your security rules as your AI application evolves.

Pricing & Plans

Lakera offers a free trial that gives hands-on access to core features without any initial payment. For production use, subscription plans are tailored to the size and scope of the organization—pricing details are typically provided upon request. Larger enterprises with high request volumes and custom deployment needs should contact Lakera’s sales team for a custom quote. Because the platform is built to scale, the cost structure generally reflects the number of API calls, the deployment model (cloud vs. self-hosted), and any add-on services like guided red teaming. For the most current pricing, check the official Lakera website.

Platforms

Web Application: Full-featured dashboard for managing APIs, configuring policies, and reviewing threat analytics.
REST API: Core integration point for Lakera Guard and PII Detection, simple to drop into any backend language.
Self-Hosted Deployment: On-premise or private cloud option for organizations with strict data control requirements.
SDKs and Quickstart Scripts: Ready-made code snippets for Python, Node.js, and popular LLM frameworks to accelerate integration.

Tips & Best Practices

Start with the free trial on a non-critical application to understand how Lakera interacts with your specific models before rolling it out across production services.
Leverage Lakera Red early in the development cycle, not just before launch. Treat red teaming as a continuous practice, especially after model updates or new feature additions.
Gradually tighten content safety thresholds instead of enabling maximum filtering right away; this helps balance security with user experience and reduces false positives.
Combine Lakera Guard with human-in-the-loop reviews for high-stakes applications—automated detection catches most threats, but a manual oversight step can handle edge cases.
Self-host if data residency or latency are critical; securing sensitive data often requires that no prompts or outputs leave your infrastructure.
Use PII detection with encryption and access controls—redacting PII is powerful, but ensure that the underlying storage and logging also follow compliance best practices.

Who is Lakera for?

Enterprise Security Teams: Protecting large-scale AI deployments from reputational and compliance risks by blocking prompt injections, data leaks, and unsafe content in real time.
Product and Engineering Teams: Building AI-powered features who need an easy-to-integrate safety layer that doesn’t degrade user experience or slow down development velocity.
LLM Builders and AI Platform Providers: Offering AI security as a native feature to their own customers, often using Lakera’s APIs under the hood to provide guardrails out of the box.
Compliance and Privacy Officers: Ensuring that generative AI applications automatically detect and mask PII, helping the organization adhere to GDPR, HIPAA, and other privacy frameworks.
AI Startups: Moving fast but needing a robust security foundation without building in-house threat detection from scratch; the free trial and scalable plans make it accessible.
Academic and Research Institutions: Teaching AI security concepts or conducting cutting-edge research into adversarial machine learning, using Lakera as a hands-on lab environment.

Alternatives

View all

Robust Intelligence

Concentrates on AI model validation, ongoing monitoring, and supply chain risk, with a strong emphasis on pre-deployment testing and compliance.

HiddenLayer

Provides threat detection and response specifically for machine learning models, focusing on adversarial attacks and model theft without requiring code changes.

ProtectAI

Offers a platform for securing the machine learning supply chain, including vulnerability scanning for ML components and tools like **Robust Intelligence** for model testing.

CalypsoAI

Delivers AI security testing and validation, often used in high-compliance government and defense environments to certify model safety.

WhyLabs

An AI observability platform that monitors model performance and data drift, with some capabilities for detecting malicious inputs and outputs.

PromptArmor

Specialized in defending against prompt injection and jailbreak attacks, similar to Lakera Guard but currently narrower in scope and deployment options.

FAQ

Q1. What is Lakera mainly used for?

Lakera is primarily used to protect generative AI applications against prompt injections, data leakage, and unsafe content. It provides real-time threat detection, red teaming simulations, and PII redaction tools that secure the AI pipeline from input to output.

Q2. Does Lakera work with any large language model?

Yes, Lakera is designed to be LLM-agnostic. It can integrate with OpenAI GPT models, Anthropic Claude, Cohere, open-source models like Llama, and custom fine-tuned models via a simple API layer, making it flexible across different providers.

Q3. Can I try Lakera before purchasing a plan?

Absolutely. A free trial is available that lets you test Lakera Guard and evaluate its threat detection capabilities on your own prompts and AI workflows. No credit card is required to start.

Q4. Is it possible to run Lakera completely within my own infrastructure?

Yes, Lakera offers a self-hosted deployment option for organizations that require on-premise or private cloud control over data. Contact Lakera for details on deployment architecture and licensing.

Q5. How does Lakera handle data privacy?

Lakera’s PII Detection feature actively scans and redacts sensitive information in real time. Additionally, when deployed in self-hosted mode, all data processing can remain within your secure environment, aiding compliance with GDPR, SOC2, and other regulations.