Glaider enables companies to develop GenAI solutions confidently, safeguarding against prompt injection, data leakage, RAG poisoning, and various LLM vulnerabilities.
Generative AI unlocks incredible opportunities, but also introduces new vulnerabilities. Without proactive security measures, your AI systems risk exposure to evolving threats. Glaider provides the expertise to help you stay ahead
Prompt Attacks
Identify and neutralize both direct and indirect prompt attacks in real time, safeguarding your application from malicious manipulation
Inappropriate Content
Prevent harmful or policy-violating content from slipping through by proactively detecting and filtering inappropriate outputs
PII & Data Loss
Protect sensitive personal data and prevent costly breaches, ensuring full compliance with privacy standards
Data Poisoning
Protect your RAG systems from data poisoning by analyzing uploaded documents for potential threats.
Why to safeguard your GenAI implementation?
As GenAI technology becomes more integrated into business operations, the risks associated with unsecured systems grow. Protecting your AI implementation is essential to mitigate potential threats and ensure business continuity
AI Chatbots
Brand damage, exposure to harmful content could severely damage your brand reputation
Inappropriate content can result in customer dissatisfaction and public backlash
Failure to monitor chatbot behavior could lead to legal actions or fines for non-compliance with regulations
RAG Applications
Exposing sensitive informations through indirect prompt injection
Attackers may manipulate RAG systems by crafting malicious prompts, impacting model behavior
Lack of safeguards can lead to unauthorized access or data tampering
AI Agents
Autonomous agents operating unsupervised can be exploited without detection
Unforeseen actions by AI agents may cause critical infrastructure disruptions
Compromised agents can trigger chain reactions, leading to large-scale damage
Whether you're using GPT-X, Claude, Bard, LLaMA, or even your own custom LLM, Glaider ensures you stay in control. It seamlessly integrates into your current setup without the need for significant changes
Extremely low latency
Glaider's advanced prompt injection protection delivers top-tier security with ultra-low latency, ensuring no impact on LLM execution or performance
Flexible deployment options
Choose the deployment method that suits your organization's needs, whether you're a fast-growing startup or a large enterprise.
Glaider SaaS is designed for those seeking a straightforward, scalable solution.
Rapid deployment
Zero infrastructure management
Continuously updated to counter the latest threats
Glaider Self Hosted
Glaider Self-Hosted is tailored for those who want complete control over their data and infrastructure.
Your data stays within your organization
Full control over your architecture
Continuously updated to counter the latest threats
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 attacks—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.
.png){kind=logo}
