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Agentic automation

From automation to the agent that decides

The next step: AI agents that don't just run a flow but reason, decide and chain actions across your processes — with the guardrails and human control production requires.

What sets an agent apart

An agent combines automation's execution layer with generative AI's reasoning layer. One partner for both.

Reasoning and decision

The agent assesses a situation and chooses the action, instead of following a fixed sequence. It handles cases classic automation cannot anticipate.

Chaining actions

The agent orchestrates several steps and several tools to see a task through, not just answer a question.

Access to your tools

Through function calling and APIs, the agent actually acts in your systems — read, write, trigger — within a scope you define.

Human control

You set what the agent may do alone and what needs approval. Human-in-the-loop is built in, not optional.

Guardrails and scope

Limited rights, reversible actions, stop points. An agent you put into production because its autonomy scope is explicit.

Observability

Every decision and action the agent takes is traced and auditable. You know what it did, why, and you can roll back.

When an agent makes sense

When a process needs more than a fixed sequence — judging, arbitrating, adapting — but you want to keep control over what gets decided without you.

  • Autonomous tier-1 support

    The agent handles routine requests end to end and escalates what is beyond it.

  • Case handling

    The agent works a case — gathers, checks, prepares — and presents it to a human for decision.

  • Business copilot

    An assistant that acts in your tools on request, instead of only advising.

  • Cross-tool orchestration

    The agent coordinates several systems to carry out a full operation.

Our approach

Autonomy under control

An explicit action scope, never a black box.

Human-in-the-loop by default

Human validation where the decision commits.

Grounded in your data (RAG)

The agent reasons on your context, not in a vacuum.

Sovereign, hosted in Europe

Data and models under your control.

Technologies

The orchestration, reasoning and control building blocks we assemble for a reliable agent.

Agents LLMFunction callingRAGOrchestrationHuman-in-the-loopLaravelNode.jsVue.jsERP / CRMHébergement UE

Frequently asked questions

What people ask about agentic automation.

Classic automation follows a sequence you defined in advance. An agent reasons about the situation, decides on the action, then executes it. Automation is the execution layer; the agent adds a decision layer on top.
Exactly as far as you decide. We define an explicit autonomy scope: what the agent does alone, what needs human approval, what it is not allowed to do. Human-in-the-loop is a design point, not an option.
Provided it is framed: limited rights, reversible actions, checkpoints, full traceability. We put an agent into production on a controlled scope, then widen it — not the other way around.
Not necessarily, but it helps: an agent relies on tools and actions reachable via API. We often start by automating and integrating, then add the agent layer where the decision adds value. We can support the whole chain.
Yes: European hosting, data that stays with you, and sovereign models deployable on your infrastructure where sensitivity requires it. GDPR and EU AI Act readiness are anticipated from the design stage.
Yes, that is our edge: we cover the plumbing (integration, ERP/CRM, workflows) and the AI depth (LLM, RAG, agents) under one roof. You don't have to make an automation agency and an AI agency talk to each other.
MPWB

A process worth an agent?

Let's talk scope. We'll tell you where an agent genuinely adds value, and where simple automation is enough.

Response within 24h 100% confidential No commitment