WAM Agents vs ChatGPT

The short version

If you need a quick answer, a chat is enough: open a tab, ask, close it. If you need someone to take a task off your hands, keep track of your projects and be reachable where you already talk, that is an agent. WAM Agents is built for the second case.

	GPT chat	WAM Agents
Where it lives	A browser tab or a separate app	Telegram: DMs, groups and forum topics
What you get back	Text to copy somewhere	Done work: a file, a table in your Drive, a sent reply, an event in your calendar
Memory	Its own memory, kept inside ChatGPT	Remembers your projects, people and preferences across chats
Your data	Your account on OpenAI’s service	Your own isolated container
Model	OpenAI models	DeepSeek included; Claude or Codex on your own subscription (Pro)
In a team chat	Not in your Telegram groups	A participant: quiet until mentioned, answers from the thread everyone sees

Answers versus finished work

Ask a chat to pull the numbers out of a 41-page board pack and it will paste a summary you still have to check and retype. Forward the same PDF to your agent and it comes back with every figure and the page it sits on, and the same table already in your Google Drive.

Documents are one case. The agent plans and carries a task through: it reads documents and voice notes, searches the web, writes and runs code, creates files, drafts and sends mail through Gmail, puts events into Google Calendar, connects to your servers over SSH and sets its own reminders for later. You see each step while it works.

It lives where you already talk

No new tab and no new app. The agent is a contact in your Telegram with the name and avatar you chose. Write to it, send a voice note between meetings, forward a screenshot or a document, whatever is easier at that moment. Add it to a project group and it answers when someone mentions it, using the context of the thread.

Memory that carries over

A chat keeps what it remembers inside its own app. Your agent keeps your projects, contacts and preferences across conversations, and you edit that memory in plain words: “remember that Lena signs off contracts”, “forget the old address”. With forum topics each project gets its own session and its own memory, so contexts do not mix.

Your data stays in your container

Every agent runs in its own isolated container. It knows its owner and the people the owner lets in, nobody else. Requests on the default model go through DeepSeek’s infrastructure, and you confirm that at onboarding. Attach your own model and requests go through your own account with that provider, under its terms.

Pick the model for the task

DeepSeek is included in every plan, Free as well, with no keys to bring. On Pro you can attach Claude with /claude or Codex on your ChatGPT subscription with /codex, and switch with /model right in the chat. The provider then bills those tokens on your own subscription. You are not locked into one model.

What it costs

On Free the agent works with voice, vision, search, files, memory and connectors, with 200  of work in your first month, then 100  a month, no card. Pro is $13.90 a month with 400  and adds recurring reminders, scheduled tasks, top-ups and your own model; the first month is $1.39 if you subscribe within your first 7 days. Details are on the pricing page.

When to choose what

Choose a chat when you want an answer and will do the rest yourself. Choose WAM Agents when you want the rest done: the table built, the reply sent, the meeting booked, the project remembered, in the messenger you already have open.