This is like putting a smart safety inspector in front of your company’s AI chatbot. Before the AI answers, the inspector checks if the question or answer is unsafe (toxic, leaking secrets, non‑compliant) and blocks or rewrites it.
Prevents large language models used in operations (e.g., safety guidance, maintenance assistants, internal knowledge bots) from generating harmful, non‑compliant, or high‑risk content, reducing regulatory, reputational, and safety risk in a high‑hazard industry.
Tight integration of guardrails with IBM’s Granite model family and broader IBM watsonx stack, plus policy templates and governance workflows that can be embedded into existing enterprise IT and compliance processes.
Hybrid
Context Window Stuffing
Medium (Integration logic)
Policy complexity and latency added by pre- and post-processing every LLM call, especially under high conversational load.
Early Adopters
Positions risk detection and policy enforcement as a first‑class, configurable layer around Granite LLMs, rather than an afterthought, targeting regulated and high‑risk sectors like mining where AI safety is a deployment blocker.