As the client expanded the use of generative AI across its digital consumer experiences, ensuring safe and predictable AI behavior became a critical priority. Traditional software testing was not sufficient to evaluate large language models, which can produce unexpected responses when exposed to adversarial prompts or malicious input.

The client needed an efficient and scalable approach to identify potential risks early in the development lifecycle while maintaining an aggressive product delivery schedule.

Krasamo engineered an automated AI security validation engine built upon a robust LLM red-teaming framework. The system employs AI-driven adversarial agents to simulate real-world attacks across diverse scenarios, rigorously evaluating the client’s custom AI solutions before deployment.

The project included designing custom testing scenarios, evaluating model responses under adversarial conditions, identifying unsafe behaviors, documenting findings, and collaborating with product teams to strengthen prompt filtering and AI safety guardrails. Krasamo also integrated the testing process into the client’s development workflow, enabling repeatable AI security validation throughout future releases.

• Identified potential AI safety risks before production deployment.
• Strengthened the client’s AI safety validation process.
• Helped establish a repeatable AI red teaming workflow for future AI initiatives.
• Improved confidence in deploying generative AI responsibly within consumer products.