Chapter 01Agentic AI in industrial settings
AI agents where the work happens
A plant, a wastewater network, a production site pile up readings, service reports, drawings and photos every day, and nobody has time to read them. Laitao designs and commissions AI agents that read this data, connect it to the systems already in place and prepare the decisions. The teams stay in charge.
What an agent does on an industrial site
Read what piles up
Maintenance reports, purchase orders, quality sheets, handwritten notes snapped with a phone: the agent reads them and pulls out what is useful.
Connect the systems
The ERP, the maintenance system, the shop-floor spreadsheets and the digital model rarely talk to each other. The agent fetches the information wherever it lives.
Flag things early
A sensor out of range, readings drifting, a defect that keeps showing up in photos: the agent spots it and alerts the right person.
Prepare the decision
The agent proposes an action and explains why. The person in charge approves, corrects or rejects it, and every choice is logged.
What is not up for negotiation in a plant
A person decides
An agent does not run a machine or place an order without approval.
Everything is traced
What the agent read, what it proposed, who approved it: all of it is logged and can be reviewed.
The data stays under control
Hosting is chosen with the client, and access is limited to what the agent needs.
Control systems stay separate
The agent works alongside the automation layer, never in its place.
What industry has taught us
- Since 2013More than 270 digital maturity assessments of companies of every size, using the eCAC40 method.
- 2023 – 2024A training program on machine learning and the environment for industry, designed for a major steelmaker and built on interviews with manufacturers.
- Since 2023Training for the top management of a Moroccan industrial group, then the design of its Industry X.0 school.
- Since 2024AI, then AI applied to the digital building model (BIM), for a public wastewater utility.
- Since 2025AI tools in production at an industrial joinery manufacturer.
How a deployment unfolds
On the shop floor
We start on site, with operators and supervisors: where time gets lost, where information is missing.
One agent, one real flow
A single use case, picked for its value and feasibility, commissioned on real data.
Measure, then widen
We measure the time saved and the errors avoided before extending to other flows or other sites.
Hand over
Teams are trained to keep the agents running. Gilles Babinet leads the strategy; partner engineers build.
Let’s talk about your site
Tell us about your environment, and we will get back to you to set up a first conversation.