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Protect Your AI Implementation

Safeguard your AI systems from emerging threats like shadow AI and prompt injection. Our solutions protect both external apps and those you develop, ensuring robust security and compliance
Protection from new attacks
Security analytics and observability
On-premises deployment option
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Backed by
Prompt Injections and LLM Vulnerabilities

Security for
internal GenAI deployment

Glaider safeguards your GenAI applications, securing all inputs against prompt injections, jailbreaks, and other LLM vulnerabilities.
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prompt injection detection
Shadow AI and Data Loss Prevention

Protection for Consumer GenAI Apps

Glaider empowers enterprises to securely leverage public GenAI technology. Discover all shadow GenAI tools, reveal their risks and apply real-time data protection policies.
Shadow AI
Data Leakage
Regulatory and Compliance Risks
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Integrations

Seamless Integration Across GenAI Apps

Glaider allows your company to securely engage with one or multiple generative AI models and scales with your evolving generative AI needs.

FAQs

Why should I implement Glaider?
When deploying generative AI systems like large language models (LLMs), it can be challenging to monitor everything they're saying on your behalf or to detect attacks targeting them. Glaider addresses these challenges by protecting your AI from attacks and manipulation, giving you visibility into its operations, and allowing you to define behaviors it should avoid. This means you can ensure your AI systems are not only secure but also align with your intended use, maintaining control over their outputs and preventing unintended consequences.
Why should we choose Glaider over traditional security measures for our AI applications?
Traditional security measures often fail to address the unique vulnerabilities of AI models, such as prompt injection attacks that manipulate AI behavior. Glaider is specifically designed to protect against these AI-centric threats. It seamlessly integrates with your existing applications, offering features like real-time detection, adjustable strictness levels, and automated enforcement of security policies. This ensures your AI models remain secure without compromising performance or requiring significant changes to your workflows.
What is the difference between Glaider and classical guardrails in AI security?
Classical guardrails rely on predefined rules and filters to block known malicious inputs, which can be limited and inflexible against evolving threats. Glaider, on the other hand, uses advanced, real-time analysis to detect and prevent prompt injection attacksā€”even those that are sophisticated or previously unknown. This dynamic approach allows Glaider to adapt to new attack patterns, providing a more robust and comprehensive defense for your AI systems compared to traditional guardrails.