Secure your generative AI and large language model (LLM) deployments with our comprehensive professional services offering. This package is designed to address the most critical challenges in AI security, including prompt injection, insecure output handling, and training data poisoning and other threats in OWASP TOP 10 LLM. Our Red Teaming services simulate adversarial attacks, stress test AI models, and probe for accountability and data breach scenarios. In addition, our LLMOps services provide a robust framework for monitoring, evaluating, and optimizing the performance and reliability of your AI applications using tools such as Amazon SageMaker Clarify and Giskard for Evalulation, Langfuse for monitoring and Amazon Bedrock Guardrails for safe checks.

Our services include:

• Vulnerability detection for performance biases, hallucinations, data leakage, and more through our Red Teaming Playground.
• A full-scale Red Teaming assessment, including manual and automated security tests.
• Implementation of security best practices for AI models, such as zero-trust approaches, role enforcement, and contextual awareness.

Implementation Phases

Assessment and Planning (1-2 Weeks): We begin by thoroughly assessing your current AI systems, identifying potential vulnerabilities, and defining the scope of the red teaming project. This phase includes risk assessments, setting goals, and developing a strategic plan aligned with your security and compliance objectives.

Attack Simulation Design and Development (3-5 Weeks): During this phase, we design realistic adversarial attack scenarios tailored to your systems. This includes developing the red team infrastructure, tools, and methodologies to simulate various attacks on your AI models, with a focus on areas such as prompt injection, data poisoning, and insecure output handling.

Execution and Stress Testing (2-3 Weeks): We execute the red teaming operations, simulating attacks to test the robustness of your AI systems. This phase includes stress testing, probing for security gaps, and analyzing the system's response to adversarial activities, ensuring no critical vulnerabilities are missed.

Reporting, Optimization, and Mitigation Planning (1-2 Weeks): Post-execution, we deliver a detailed report outlining identified vulnerabilities, the success of simulated attacks, and their potential impacts. We provide actionable recommendations to optimize your AI system's defenses and assist in implementing mitigation strategies.

Why Bother ?

Ensure that your AI models are not only performant but also secure, reliable, and trustworthy especially that organisations must proactively implement the requirements of the EU AI Act to comply with legal obligations and mitigate potential risks. Whether you are developing a Proof of Concept (PoC) for RAG solutions or deploying advanced generative AI applications at scale, our team of experts will guide you through every stage of the process.