How a Blue Lemon Agent agent works
The market sells "an LLM". An agent that actually works inside a company has four layers, and the model is the one that decides least. Here is what each does, and which one you will have to build yourself if you go without us.
A language model watches nothing, triggers nothing and enforces no ceiling. It reads, it classifies, it writes. Everything that commits your company — what goes out on its own, what waits for approval, what alerts whom — is decided by the three layers around it. That is where our work is, and that is what you are buying.
The four layers
In the reverse of the market's order: starting with what everyone sells, ending with what makes the difference.
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1
The language model
It understands a request written in plain language, classifies it, pulls what is needed from a document and drafts a reply. That is all, and it is already a great deal. Mistral, Lucie, EuroLLM, Teuken: at this level of task the sovereign models do the job, and a model running on your own machine is enough.
Who provides it An open model, run locally or on your isolated resource. Interchangeable.
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2
The rules and the guardrails
What goes out on its own and what waits for a signature. Ceilings, pre-approved categories, the cases that stay human, the log of who decided what. A ceiling enforced by a model is not a ceiling: it would hold ninety-five times out of a hundred and give way on a money decision, without being reproducible. This layer is deterministic code, not an instruction written to the model.
Who provides it Us. Configured with you, revocable by you, logged.
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3
The connectors and the scheduler
What gives the agent something to look at, and a reason to look now. Email, ERP, CRM, ticketing, document base, staff directory — plus the clock that fires the morning report and the memory of what has already been seen. Without this layer there is no monitoring: there is a conversation.
Who provides it Us. This is where most of the deployment effort goes, and what varies from client to client.
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4
The supervision
What makes the whole thing checkable: the trace of every action with its source, the screen showing what the agent did, the button that stops it. It is the layer you notice on the day something went wrong — and on that day it decides whether you understand in ten minutes or in three days.
Who provides it Us. Included in the subscription, not an option.
So what does the model actually do?
The four behaviours our demonstrators show, and what really produces them.
| The behaviour | What does it | The model's part |
|---|---|---|
| Continuous monitoring, daily report | Scheduler, connectors, memory of what has been seen | Draft the summary |
| Activatable rules, ceilings | Rules engine, audit log, configuration screen | Classify the request into a category |
| Routing, reminders, summary up the line | Staff directory, timers, approval workflow | Draft the summary |
| Spotting a pattern (bank details, domain, due date) | A query, a string comparison, a subtraction of dates | Explain the result in plain language |
None of these four lines is an emergent capability to be hoped for from the right model. It is ordinary, well-understood software, built during deployment — and that is why we can commit to it.
What this architecture changes for you
Your questions, our answers
Do your agents use ChatGPT?
What happens if the model gets it wrong?
Can we take our rules with us if we change provider?
How long does all this take to put in place?
Want to know which layers you already have, and which are left to build? Book the free 15-minute audit