A large language model (LLM) is an AI model trained on vast amounts of text to understand and generate human-like language by predicting the most likely next words in a sequence. Models like Anthropic's Claude are LLMs, and they power most modern conversational and agentic AI.
An LLM is powerful but, on its own, ungoverned. It predicts plausible text, which means it can be fluent and wrong at the same time. That gap between fluent and correct is exactly why shipping an LLM straight into customer conversations without guardrails is risky.
LLM is a foundational industry term, not Aide-owned. Aide, the agentic AI platform for customer experience, uses Anthropic's Claude models (on zero data retention terms) and open-weight models that run on Aide's own servers, such as multilingual-e5-large for search, but treats the raw model as an input, not the product. The product is the intent-first architecture and the verified procedures wrapped around the model, not the model itself.
Guardrails are the point. Automation is scoped by intent, written into verified procedures, and tested before anything goes live, so fluent-but-wrong answers do not reach customers. The team can read the logic around the model, which keeps their understanding of how resolutions happen growing rather than atrophying behind it.