Blog
Analogies and real architecture behind building AI agents with Wetel.
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How long does a conversation with an AI employee stay open?
A conversation in Wetel opens when your app starts it and stays open until your app or the workflow ends it. One left idle for 30 days is marked expired, and the next message starts a fresh one. Here is what happens at each point.
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A university library assistant: bookings, renewals and answers, with the library in charge
A walk through one documented deployment: an AI employee that answers students from a library's own catalog, checks rooms and renews loans through the library's own systems, and what the case study does and does not tell us about where people stay in charge.
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When not to use an AI employee: a buyer's guide that says no
An AI employee is the wrong tool for some work: fixed steps with exact numbers, irreversible decisions nobody checks, channels or features we have not built, and processes nobody can write down. Here is how to tell, and what Wetel does not offer today.
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Answering from your own policies, with sources you can check
How a Wetel AI employee answers from your company's own policies and documents, how you can see which passages it used, how you keep the documents current, and what to do when the answer is not in them.
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Which AI model does my AI employee use, and what happens if it fails?
Every AI employee runs on the platform's default model unless someone picks another one, and the default provider tries a second provider automatically if a call fails. Here is who can choose and restrict models, and what you see when something goes wrong.
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Giving an AI employee a new skill with MCP connectors, and what keeps it safe
How to let an AI employee use a tool in another system without writing a plugin: register an MCP server once as a connector, call one named tool from a workflow step, and rely on the checks that sit around every call. What is live, how to test it, and what is not built yet.