AI Risk Visibility

Surfaces high impact AI risks including architecture, integration and intellectual-property vulnerabilities across agents, applications and models. Provides deep, attacker-centric visibility into how AI systems behave under real adversarial pressure.

Delivers real-time threat detection and unsafe-output filtering for LLM interactions. Provides visibility into model misuse and potential data leakage at the prompt and response level across supported applications.

Shadow AI Discovery

Surfaces a full AI asset inventory and hidden AI usage across the environment. Detects ungoverned model deployments, shadow agents, and unapproved data flows before they introduce risk.

Monitors endpoints, prompt flows, and outside-model interactions to identify unsanctioned AI tool usage within monitored environments.

AI Risk Assessment

Continuous and automated AI red teaming across agents, models and applications. Identifies how attackers can exploit architectural, behavioral, and integration vulnerabilities.

Assesses AI model risk through the Lakera AI Model Risk Index. Simulates selected adversarial attacks on LLMs and generates score-based outputs that reflect model-level exposure.

Behavioural Science Testing Capabilities

Models attacker behavior across human, linguistic, and system biases to surface vulnerabilities that static and score-based testing miss.

Models behavioral attack vectors (memory poisoning, long-horizon goal hijacks, and agentic workflow manipulation) to flag risky model behavior and ouptut anomalies.

AI Security R&D Talent

86% of staff on R&D team, 38% hold PhDs. Founded by Professor at Lancaster University. Research pipeline from the UK’s top AI security lab.

~22% on R&D team; per People statistics on LinkedIn Sales Navigator.

Simplicity and Usability

Designed for both security engineers and AI builders, Mindgard delivers a clean, intuitive interface with clear risk visualizations, guided workflows, and one-click retesting—no steep learning curve required.

Central monitoring dashboard and policy control center for non-coding teams. Visual workflows simplify policy setup and guardrail configuration for supported use cases.

AI Guardrails

Nascent capabilities

Offers guardrails for prompt defense, content moderation, data leakage prevention, and malicious link detection. Uses a combination of Lakera-managed and custom guardrails.

Attack-Driven Testing

Continuously red-teams models, agents, and applications through attack-driven testing—covering jailbreaks, data exfiltration, and prompt injection. Supports multi-turn adversarial chains with reproducible results to validate fixes.

Simulates real-world adversarial attacks against GenAI systems before deployment. Covers multilingual inputs, multi-modal inputs, and emerging threat vectors. Customizes attack campaigns based on architecture and business logic and delivers actionable findings with severity ratings and remediation guidance.

Runtime Detection & Policy

Provides inline detection and enforcement for prompt injection, data leakage, and tool abuse with configurable block/alert/enrich options.

Screens live model interactions for prompt attacks, data leakage, malicious links, and content violations. Centralized policy management assigns guardrails per-project with configurable sensitivity ranges and allow/deny lists. Flagged content can be blocked, logged, or escalated.

Enterprise Controls

Delivers enterprise-grade governance with granular permissions, policy enforcement, detailed audit trails, and full SAML/SSO, SCIM, and RBAC support. Aligns security testing with organizational compliance and reporting standards.

Enterprise customers can configure RBAC for the dashboard and integrate with SIEM and logging tools. Admins manage retention and access settings within the platform’s available controls.

Integrations

Integrates seamlessly across developer and security workflows, including CI/CD pipelines, IDE hooks, SIEM, and ticketing systems. The first AI red teaming solution with a native Burp Suite integration, enabling red teams to extend attack-driven testing into familiar tooling.

Integrates with customer environments through API-based connections that connect Lakera’s guardrails to supported architectures and workflows.

Deployment Options

Most flexible: SaaS, Private cloud, Customer‑managed. On-prem available for regulated and high-sensitivity environments.

Cloud-based SaaS and self-hosted deployments.

Reporting & Scorecards

Provides end-to-end reporting that connects testing outcomes to business, compliance, and architectural risk. Scorecards, trend analytics, and executive summaries demonstrate measurable AI security posture improvement over time.

Central dashboard monitors interactions, threats, and policy enforcement, with logs exportable to external reporting systems. SIEM integration extends visibility into broader enterprise tooling.

Support & Partnership

Customers gain a dedicated success team backed by world-class AI security researchers. Mindgard provides hands-on guidance informed by active attack research, helping enterprises apply the latest insights to their own AI environments and continuously strengthen defenses.

Offers standard enterprise support and onboarding. Shares research on emerging GenAI threats and adversarial patterns primarily through product updates and public articles.

Pricing Model

Contact sales for tailored pricing.

Free Community plan for up to 10,000 requests per month and a maximum prompt size of 8,000 tokens. Contact sales for Enterprise pricing.