Lakera
Runtime AI security for GenAI apps, agents, and workforce AI
A robust, enterprise-grade choice for production AI apps, but the cloud-only model and sales-led pricing will frustrate smaller teams. If you need runtime protection for GenAI and have compliance budget, it's a strong pick—otherwise, consider open-source options or vendor-native guardrails. Its sub-50ms latency and 0.01% false positive rate are standout specs for high-traffic apps, and the Gandalf community threat intel is a differentiator. Yet the lack of transparent pricing and on-prem deployment make it a poor fit for SMBs or air-gapped needs.
Verified 9d ago · liveness 78/100 · cite: rightaichoice.com/tools/lakera
- Enterprise teams with GenAI apps in production needing runtime protection
- Regulated industries (banking, healthcare) requiring high accuracy and multilingual support
- Organizations managing employee shadow AI usage and governance
- Security teams conducting risk-based AI red teaming exercises
- Teams needing on-premise or air-gapped deployment (cloud-only)
- Organizations without any GenAI usage in production
- Budget-constrained teams seeking transparent, self-service pricing
We scan live Reddit threads, YouTube comments, X posts, G2 reviews and other communities — and hand you an honest verdict in under a minute.
- Honest verdict, not marketing
- Real pros & cons from real users
- Attributed quotes with receipts
3 free scans · no card needed
Skip Lakera if you need on-premise or air-gapped deployment, if you lack dedicated budget for enterprise AI security, or if you're a small team wanting self-service pricing—its cloud-only model and sales-led engagement won't fit.
Pricing is not publicly listed; you must engage sales, which may involve annual contracts and minimum commitments that surprise smaller teams.
Lakera targets enterprises with compliance budgets; its contact-based pricing fits Fortune 500s and regulated industries. Cheaper alternatives like open-source guardrails (e.g., Rebuff, NeMo Guardrails) or vendor-native safety filters (OpenAI moderation) are free or included, but lack Lakera's dedicated runtime threat intelligence and centralized policy control. If you're a startup without deep pockets, expect to pay a premium for Lakera's enterprise-grade features.
In short
Lakera — Runtime AI security for GenAI apps, agents, and workforce AI. Best for Enterprise teams with GenAI apps in production needing runtime protection, Regulated industries (banking, healthcare) requiring high accuracy and multilingual support, Organizations managing employee shadow AI usage and governance. Contact Sales pricing.
Viability Score
How well maintained and how widely used is Lakera? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: September 2026
How we score →Key Features
- Real-time prompt injection detection
- Data leakage protection for AI apps
- Shadow AI discovery across apps and browsers
- Context-aware data protection in prompts
- Granular policy controls by user, app, and action
- Risk-based AI red teaming with simulations
- Direct and indirect attack simulations
- Multimodal detection (text, audio, image)
- Sub-50ms runtime latency
- 100+ language support
- 0.01% production false positive rate
- Centralized policy management without code changes
- Automatic adaptation to evolving threats
- Cloud-native, API-first architecture
- Continuous threat intelligence from Gandalf community
About Lakera
Lakera is an AI-native security platform that helps enterprises protect their generative AI applications, agents, and employee AI usage from threats like prompt injection, data leakage, and toxic content. It combines three core products: Workforce AI Security for shadow AI discovery and governance, AI Agent Security for real-time threat detection and prevention, and AI Red Teaming for risk-based vulnerability testing. The platform is designed to secure AI without slowing development—it offers ultra-low latency (sub-50ms), supports 100+ languages and multimodal content, and adapts automatically to evolving threats without manual updates. Built for organizations with production GenAI deployments, Lakera is purpose-built for the unique risks AI introduces. It goes beyond controlling what AI can access—it controls what it does, using context-aware policies to block attacks before they impact business. The platform is cloud-native and API-first, making it easy to integrate into existing workflows via enterprise integrations like Slack, Microsoft Teams, LangChain, and major cloud AI services. It also claims a production false positive rate of just 0.01%, minimizing alert fatigue. Lakera is validated by industry recognition: it's cited in OWASP's LLM and GenAI Security Landscape Guide 2025, named a TRiSM vendor in Gartner's Innovation Guide, and is a partner with Snyk on AI agent security research. Trusted by enterprises like Dropbox and used in regulated banking environments, Lakera is a specialist in GenAI threats, offering a comprehensive security layer for AI workloads. Compared to general-purpose security platforms like Snyk or Cloudflare, Lakera focuses exclusively on GenAI risks, making it a stronger fit for teams needing deep, runtime protection for LLM-powered features. However, its cloud-only deployment and contact-based pricing limit its appeal for smaller teams seeking self-service or air-gapped solutions.
Behind the Verdict
Lakera earns its reputation as a specialist in GenAI security. The platform’s three-pronged approach—Workforce, Agent, and Red Teaming—covers the full lifecycle of AI risk, from employee shadow AI to production runtime attacks. For enterprises with LLM-powered apps, the sub-50ms latency is critical; you won’t degrade user experience while filtering every prompt. The 0.01% false positive rate means security teams won’t drown in alerts, which is a common pain point with other tools. The Gandalf community (1M+ hackers) feeds real threat data into the engine, keeping defenses current without manual updates—a strong advantage over static rule-based systems. Integrations with LangChain, LlamaIndex, and major cloud AI services (Azure, AWS Bedrock, Vertex) make deployment straightforward for modern stacks. However, the cloud-only architecture is a hard blocker for air-gapped or regulated environments that require data residency. Pricing is opaque (contact sales), which hinders evaluation and budgeting. Smaller teams without a dedicated AI security budget may find free or open-source alternatives (e.g., Prompt Guard, NeMo Guardrails) more accessible, though they lack Lakera’s enterprise-grade support and breadth. If you’re a Fortune 500 or a startup with compliance mandates, Lakera is a serious contender; if you’re a solo dev or early-stage team, consider lighter options first.
Researching Lakera? Get your full AI stack in 60 seconds.
Free, no signup — tell us your goal and get tools matched to your budget & existing stack.
Real-world workflow fit
Concrete scenarios for the personas Lakera actually fits — and what changes day-one when you adopt it.
Deploying an AI customer support chatbot that handles money transfers.
Outcome: Using Lakera AI Agent Security, you block prompt injection attempts and data leaks in real time, pass compliance audits, and support Portuguese/Spanish—meeting fraud resistance requirements and accelerating safe innovation.
Employees are using ChatGPT and Copilot without oversight.
Outcome: With Workforce AI Security, you discover shadow AI across browsers, enforce granular policies (e.g., block sensitive data in prompts), and gain centralized control—reducing data exfiltration risk without slowing your team.
Launching a new RAG-based document assistant.
Outcome: You integrate Lakera via API in under a day, run red teaming simulations to find vulnerabilities, then go live with sub-50ms latency protection—catching injection attacks before they impact users.
Use Cases
- Protecting conversational AI agents from prompt injection and data leaks
- Securing document/RAG applications against sensitive data exposure
- Monitoring and governing employee use of ChatGPT, Copilot, Gemini
- Running risk-based AI red teaming simulations before launch
- Enforcing compliance policies across GenAI applications
- Preventing toxic content generation in customer-facing bots
- Securing MCP (Model Context Protocol) servers and agents
- Compliance monitoring for AI-powered customer support in regulated industries
Limitations
- Lakera is a cloud-based AI security platform that protects AI applications, agents, and workforce AI usage.
- It emphasizes runtime protection with sub-50ms latency and claims to deliver AI-native security that scales with enterprise teams.
- The platform is positioned for enterprises, with pricing and onboarding requiring sales engagement, which may deter smaller teams.
- Shadow AI discovery relies on browser extensions, adding deployment complexity.
as of 2026-08-29
Verification history
We have re-verified Lakera 18 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-checked, vendor evidence unchanged
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 18 verification passes.
Free to cite with attribution — this page re-verifies continuously.
Where the pricing makes sense
The company stage and team size where Lakera's pricing actually pencils out — and where peers do it cheaper.
Lakera targets enterprises with compliance budgets; its contact-based pricing fits Fortune 500s and regulated industries. Cheaper alternatives like open-source guardrails (e.g., Rebuff, NeMo Guardrails) or vendor-native safety filters (OpenAI moderation) are free or included, but lack Lakera's dedicated runtime threat intelligence and centralized policy control. If you're a startup without deep pockets, expect to pay a premium for Lakera's enterprise-grade features.
Setup time & first value
How long it actually takes to get something useful out of Lakera — broken out by persona, not the marketing-page minute.
For an API-first integration, most teams can be up and running within minutes to a few hours; the API is straightforward. Workforce AI Security may require deploying browser extensions across your org—allow a few days for rollout. Red Teaming services are expert-led and may take a week or longer to schedule and complete.
Switching to or from Lakera
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From Snyk AI Security: Lakera offers a more AI-specialized runtime layer; you can keep Snyk for code scanning and add Lakera for runtime GenAI protection via API.
- ↗To open-source guardrails (e.g., NeMo Guardrails): You can replace Lakera's runtime filtering with OSS libraries, but you'll lose centralized policy, threat intelligence, and enterprise support—plan for custom
Integrations
Resources & Guides
Tutorials & Learning
Official links
Popular in AI Governance & Guardrails
Mindgard
Automated AI red teaming platform that continuously discovers, assesses, and defends AI systems and agents.
Poolside AI
Open-weight agentic coding models for secure on-prem enterprise AI
Olas Network
Co-own and monetize AI agents on-chain with Olas.
Frequently Asked Questions
Topics
Used Lakera? Help shape our editorial sentiment research.