ChatGPT is an app built on OpenAI's GPT family of large language models. Claude (Anthropic) and Gemini (Google) are other LLM families with their own apps and APIs.

Do LLMs learn from my conversations?

It depends on the provider and plan. Business and API offerings generally let you keep your data out of model training. Always check the terms.

Can an LLM access the internet?

Only if it's given a web search or browsing tool. Otherwise it answers from its training plus whatever you supply.

blog/llms & ai models

What Is an LLM? Large Language Models Explained for Business Owners

SoftiIntel Team · 30 September 2026 · 7 min read

the short answer

A large language model (LLM) is an AI system trained on huge amounts of text to predict and generate language. That lets it write, summarise, translate, classify, extract information and reason through problems. Well-known LLMs include Anthropic's Claude, OpenAI's GPT models behind ChatGPT, Google's Gemini and open-weight models such as Meta's Llama. For business, LLMs are most reliable when they're given your own data and clear instructions, with people checking the outputs that matter.

How an LLM works, in one minute

During training, the model reads a vast amount of text and learns patterns: which words, ideas and structures tend to follow others. When you give it a prompt, it generates a response one small piece at a time, choosing what best continues the text. Modern LLMs are also trained to follow instructions, use tools and reason step by step, which is why they feel like assistants rather than autocomplete.

Five terms worth knowing

Token: a chunk of text (roughly part of a word). Models read and bill by tokens.
Context window: how much text the model can consider at once, from a few pages to very long documents, depending on the model.
Prompt: the instructions and information you give the model.
Hallucination: a confident but wrong answer, often when the model lacks the facts.
Tool use: the model calling software (search, a CRM, a calculator) to get information or take an action.

What LLMs are good at

Drafting and rewriting text in a given tone.
Summarising long documents, chats and calls.
Extracting fields from messy documents.
Answering questions from supplied material.
Classifying and routing messages.
Writing and explaining code.

Where they go wrong

An LLM only knows what it learned in training plus what you give it. Asked about your prices or policies without being given them, it may guess. The fix is grounding: supplying the right documents at answer time (RAG), telling it to say when it doesn't know, and keeping people in charge of high-stakes decisions.

Using LLMs in your business

Most businesses don't train their own model. They pick an existing LLM (Claude, GPT, Gemini or an open-weight model), connect it to their data and tools, and design the workflow around it. That's what our AI integrations and AI agents work covers. To pick a model, see how to choose an LLM.