Lakera
AI-native security platform for protecting GenAI apps, agents, and prompts.
What is Lakera?
Lakera helps companies secure generative AI applications and agents against prompt injection, data leakage, unsafe outputs, and policy violations. It is built for teams moving AI features from prototype to production and needing guardrails that security, legal, and product teams can understand.
Security, compliance, trust, identity, privacy, and risk management platforms for businesses.
See the full Security & Compliance guide to compare more tools, buyer criteria, and related workflows.
Use cases to evaluate
Detect and block prompt-injection attacks against AI applications
Add policy and content guardrails to copilots, assistants, and agents
Test AI systems for unsafe behavior before launch
Give security teams visibility into GenAI risk without slowing every product experiment
Fit to evaluate
Companies deploying customer-facing chatbots, copilots, or AI agents
Security teams assessing prompt injection and AI data-leakage risk
Product teams that need policy guardrails before launching GenAI features
Regulated or trust-sensitive businesses adopting AI in customer workflows
Business fit
Right for you if AI features are leaving the sandbox and touching customers, employees, or sensitive knowledge. Lakera is most valuable when paired with clear data boundaries, logging, and human escalation. It is less urgent for teams only using private AI assistants internally with no custom app surface.
How to evaluate Lakera
Use this category when security reviews, compliance evidence, or access controls are slowing deals or operations.
Confirm the exact workflow
Map Lakera to one concrete workflow first, such as detect and block prompt-injection attacks against ai applications. Avoid buying before the owner, trigger, output, and success metric are clear.
Check category fit
Compare evidence collection, access controls, integrations, and audit workflows.
Compare practical alternatives
Compare Lakera with other Security & Compliance vendors before committing to a contract or migration.
Validate cost and rollout effort
Lakera does not publish simple self-serve pricing for all deployments. Expect pricing to depend on product surfaces, request volume, guardrail needs, evaluation workflows, and enterprise security requirements. Also confirm implementation time, support needs, and whether the technical setup matches your team.
Compare Lakera with alternatives
Use this quick comparison before booking demos or moving data into a new system.
| Primary workflow | Detect and block prompt-injection attacks against AI applications, Add policy and content guardrails to copilots, assistants, and agents |
|---|---|
| Best-fit team | Companies deploying customer-facing chatbots, copilots, or AI agents, Security teams assessing prompt injection and AI data-leakage risk |
| Implementation effort | Technical setup and maintenance profile |
| Pricing check | Contact sales |
| Closest alternatives | Other Security & Compliance tools |
Lakera pricing
| Model | Contact sales |
|---|---|
| Snapshot | Lakera does not publish simple self-serve pricing for all deployments. Expect pricing to depend on product surfaces, request volume, guardrail needs, evaluation workflows, and enterprise security requirements. |
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Common questions about Lakera
What is Lakera?
Lakera helps companies secure generative AI applications and agents against prompt injection, data leakage, unsafe outputs, and policy violations. It is built for teams moving AI features from prototype to production and needing guardrails that security, legal, and product teams can understand.
What is Lakera used for?
Common use cases: Detect and block prompt-injection attacks against AI applications; Add policy and content guardrails to copilots, assistants, and agents; Test AI systems for unsafe behavior before launch; Give security teams visibility into GenAI risk without slowing every product experiment.
How much does Lakera cost?
Lakera does not publish simple self-serve pricing for all deployments. Expect pricing to depend on product surfaces, request volume, guardrail needs, evaluation workflows, and enterprise security requirements.
Who is Lakera best for?
Lakera fits Companies deploying customer-facing chatbots, copilots, or AI agents, Security teams assessing prompt injection and AI data-leakage risk, Product teams that need policy guardrails before launching GenAI features, Regulated or trust-sensitive businesses adopting AI in customer workflows. Right for you if AI features are leaving the sandbox and touching customers, employees, or sensitive knowledge. Lakera is most valuable when paired with clear data boundaries, logging, and human escalation. It is less urgent for teams only using private AI assistants internally with no custom app surface.