A Large Language Model (LLM) is a neural language model with billions of parameters, pretrained on massive text corpora. Current examples: GPT-4, Claude, Gemini, Llama. Inside an AI phone assistant the LLM generates the response after STT transcribes the caller’s utterance.
Pure LLMs are a strong conversational engine — but not a knowledge store for company-specific content. The standard pattern is LLM + RAG (Retrieval-Augmented Generation): for every reply, the model retrieves relevant documents from a knowledge base instead of relying on trained-in facts. Fresh, auditable, and no fine-tuning.
Production selection criteria: latency (smaller models for real-time), language quality in the target locale, hosting region (EU for GDPR), cost per token, and hallucination-robustness on bounded tasks.