AI Risk Visibility

Surfaces high impact AI risks including architecture, integration and intellectual-property vulnerabilities. Works across agents, applications and models, providing full-stack visibility and giving teams earlier, deeper risk discovery than runtime-only inspection.

Provides AI runtime threat inspection to monitor AI interactions in production. Surfaces abuse, emerging attack patterns, and policy violations across LLM apps, deployed systems, and agentic workflows.

Shadow AI Discovery

Surfaces AI asset inventory and hidden AI usage. Detects ungoverned model deployments and unapproved data flows that runtime tools miss.

Detects LLMs, AI workflows, MCP servers, and guardrails automatically. Teams can compare safety scores to benchmarks and approve or block usage.

AI Risk Assessment

Delivers continuous and automated AI red teaming across agents, models and AI applications. Identifies real exploitation paths to demonstrate exactly how attackers can compromise AI systems.

Automated AI risk assessments, red teaming, and simulated domain-specific attacks on AI systems from build to runtime.

Behavioural Science Testing Capabilities

Models attacker behavior across human, linguistic, and system biases to surface vulnerabilities that static testing and persona-based probes cannot surface.

Simulates different user types to test prompts from adversarial and regular user personas. Teams can define and run custom probes and upload custom datasets to use their own AI attack prompts.

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.

14% on R&D team; per People statistics on LinkedIn Sales Navigator.

Simplicity and Usability

Designed for both security engineers and AI builders. Offers clear, explainable risk visualizations, guided workflows, and one-click retesting to minimize noise and accelerate remediation.

Intuitive dashboard offers overall and category scores, insights on test runs with drill-down details, probe settings, target settings, compliance, prompt hardening, and log analysis.

AI Guardrails

Nascent capabilities

Deploys real-time guardrails to block jailbreaks, sensitive data leaks, and unsafe outputs.

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.

Runs high-scale vulnerability assessments, automated red teaming, and domain-specific attack simulations. Multi-modal testing protects against prompt injections, off-topic, hallucinations, and social engineering.

Runtime Detection & Policy

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

Detects and blocks jailbreaks, prompt injections, data leaks, and off-topic behavior. Offers custom AI policy creation and adjustable detection thresholds to fine-tune filter sensitivity and feedback loops.

Enterprise Controls

Delivers enterprise-grade governance with granular permissions, policy enforcement, and detailed audit trails. Supports SAML/SSO, SCIM provisioning, and RBAC to align security testing and policy decisions with organizational compliance and security standards.

Automatically maps test results to AI frameworks for audit-readiness. Users can set custom governance rules or import JSON policies to enforce internal security standards.

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 cloud providers, source code repositories, AI and ML platforms, and data platforms for AI asset management. Integrates into CI/CD pipelines and connects to conversational platforms, LLMs, and any type of endpoint via REST API for runtime protection.

Deployment Options

Most flexible: SaaS, Private cloud, Customer‑managed. On-prem available for certain use cases. 

SaaS deployment. On-premises and hybrid/VPC deployment options available on Enterprise plans.

Reporting & Scorecards

Provides comprehensive reporting that connects testing outcomes to business risk. Teams can assess how attackers could exploit their AI, validate defenses, and evidence compliance through detailed scorecards, trend analytics, and executive summaries.

Provides interactive visualizations with detailed insights on executed tests, overall and risk category scores, and detailed reporting on individual test runs. Teams can align AI deployments with standards and regulations through AI compliance mapping and monitoring.

Support & Partnership

Every customer receives 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.

Community support is available for all users, with designated support for Professional and Enterprise users. Enterprise users also receive premium support, access to a Customer Success Program, a Technical Account Manager, and training and onboarding.

Pricing Model

Contact sales for tailored pricing.

Contact sales for pricing.