A Sidecar Design for AI Safety
In industrial, manufacturing and regulated industries, ensuring model reliability, safety and security is more paramount than ever. AutoAlign's supervisory approach — a safety framework that is capable of scaling across modalities and agentic platforms — ensures that models are reliable, safe and powerful.
An effective strategy to ensure model performance and safety is critical to the adoption of AI in industrial use cases as well as other regulated industries.
Traditional AI safety approaches do not address the breadth and depth of LLM issues and vulnerabilities. In this technical report, AutoAlign presents a holistic approach to establishing comprehensive safety and reliability for all major LLMs, including their integration into NVIDIA's NeMo Guardrails.
Read to learn about:
A supervision architecture capable of real-time error correction and monitoring
Methodologies that reduce models' refusal rates while also reducing errors
How the sidecar supervisory approach can flexibly scale to support agent frameworks and future AI advances
