What each major AI tool actually is — and what the terms you keep hearing actually mean. No jargon. No hype. Just clear, honest explanations.
Each of these is built by a different company. They overlap more than they differ, but each one has its own personality and strengths.
A chatbot focused on being helpful, harmless, and honest. Strong at reading and writing long documents, analyzing code, and reasoning through complex tasks. The interface is clean and the responses tend to be careful and thoughtful.
The chatbot that made AI mainstream. Conversational, fast, and tied to the broadest ecosystem of plugins, image generators, voice modes, and integrations. The default starting point for most people new to AI.
Google's AI assistant, deeply integrated with Gmail, Docs, Sheets, and the rest of Google Workspace. Strong at handling images, voice, and very long inputs. Plays well with everything else Google.
An AI assistant built into X (formerly Twitter). Real-time access to the X feed gives it strong recency on news and trends. Personality is more casual and unfiltered than competitors.
Microsoft's AI layer, built into Word, Excel, PowerPoint, Outlook, Teams, and GitHub. It's less a destination chatbot and more an assistant that lives inside the tools your team already uses every day.
An open-source family of AI models. Free to download, modify, and run on your own infrastructure. Powers many other products you've used without ever knowing Llama was underneath.
A European AI company offering both open-source and commercial models. Known for efficient, fast models that punch above their weight on cost. Strong appeal for teams that care about data residency in the EU.
Less a chatbot, more an AI-powered search engine. Answers your questions with linked sources, like a research assistant that shows its work. Routes your query through whichever model best fits the task.
If you've sat in a meeting where someone said "agentic" or "RAG" and nodded politely, this section is for you.
All of the chatbots above are LLMs — software trained on huge amounts of text that can read and write in human-like language. "LLM" is the technical name for the engine. "ChatGPT" is one product built on top of one.
The instruction you give an AI. "Summarize this email in three sentences" is a prompt. The quality of your prompt usually determines the quality of the answer — the same way a good question gets a good answer from a human.
A token is a chunk of text — roughly 3/4 of a word. The "context window" is how much text an AI can hold in its head at once. A 200,000-token window can read about 150,000 words — roughly a 500-page book — in one sitting.
When an AI confidently says something that isn't true. It's not lying — it just doesn't know what it doesn't know. The fix is verification, especially for anything factual, legal, financial, or otherwise high-stakes.
A technique where the AI looks things up in your documents before answering. Lets the AI use your private knowledge — internal docs, client files, policies — without retraining the underlying model. The most common way SMBs make AI useful on their own data.
Customizing an AI model on your own data so it speaks in your voice or knows your specific domain. More involved than prompting, less invasive than building a model from scratch. For most SMBs, RAG is the simpler first step.
An AI that doesn't just answer questions — it takes actions. An agent can book a meeting, send an email, query a database, or run code on its own. "Agentic" is the adjective that describes any system that operates this way.
A series of steps that combine AI with regular software actions. Example: "When a new support ticket arrives, summarize it with AI, route it to the right team, and draft a reply." Workflows are how AI starts saving real time across a business.
A new standard (introduced by Anthropic in 2024) that lets AI assistants safely connect to outside tools and data — your calendar, your CRM, your codebase. Think of it as USB-C for AI integrations: one connector that works across many tools.
An AI that can handle more than just text — also images, audio, and video. Modern AI is increasingly multimodal: you can show Claude a chart, ask Gemini about a video, or have ChatGPT generate an image from a description.
A type of AI that thinks step-by-step before answering. Slower but more accurate on math, logic, coding, and complex problems. Worth using when accuracy matters more than speed; overkill for quick everyday tasks.
That's exactly what we help SMB leaders figure out. Schedule a free 30-minute call and we'll talk through where AI fits — in plain English.