Open-Source Framework Tackles the Hidden LLM Quality Problem

As companies deploy LLMs in production, they face a critical challenge: knowing if their models are actually working and not degrading over time. This open-source framework automates hallucination detection, adversarial vulnerability testing, and performance regression tracking, achieving 86% accuracy on hallucination classification—addressing a key blind spot in current AI quality assurance practices. Its fully open-source and free deployment model makes professional-grade LLM evaluation accessible to developers at all scales.