Definition

LLM (Large Language Model)

An LLM is an AI model trained on large amounts of text data to understand and generate human-like language, powering tools like ChatGPT and the AI models behind chatbots and calling agents.

LLMs work by predicting the most likely next piece of text based on patterns learned during training, which allows them to hold conversations, answer questions, and generate content across a huge range of topics. Businesses can use general-purpose LLMs through an API, or fine-tune a model on their own data for more accurate, specific behavior — the approach ZAVYANS uses for custom AI model development.

LLM in practice

When a customer asks a clinic's AI assistant "Do you do root canals on Saturdays?", the LLM understands the question even though it's phrased casually and, when connected to the clinic's own information, replies with the correct hours and an offer to book an appointment.

Common questions about LLM

How do LLMs work?

They are trained on very large amounts of text to predict the next word in a sequence. At scale, that ability lets them answer questions, summarise, translate and write in natural language.

Do LLMs make mistakes?

Yes. They can state wrong information confidently, which is often called hallucination. Connecting them to verified sources through retrieval (RAG) and checking outputs reduces this.

How do businesses use LLMs?

For customer support chatbots, drafting content, summarising documents, classifying leads and emails, and automating routine workflows with human review where accuracy matters.

Can an LLM be trained on my business information?

Usually you don't need to retrain the model. A technique called retrieval-augmented generation (RAG) connects it to your own documents, prices and policies, so it answers from your information when it replies.