Roles, not people
Each agent always does the same thing, whatever the team. It has its own access, tools and budget; nothing beyond what its task requires.
OUR AI KNOW-HOW
What we build with AI.
And how far.
Agents working as a team, custom tools plugged into yours, prototypes taken through to product. Each time, a dial: you decide what AI does on its own, we tell you what it costs and what it exposes.
Agents that work as a team
An agent is a role: a know-how defined once, assigned to a team. The team is put together for the task: a lone archivist here, a writer and their reviewer there, a developer, a tester and a reviewer elsewhere.
A loop set with you
A request comes in, the agent reads, proposes, comments, delivers, hands back. What goes out on its own and what waits for a look is a setting, not a dogma.
The model is chosen role by role
The same model can come from several providers: the cheapest first, and if one goes down, the next takes over. No dependency on a vendor: changing the model does not change the team.
Custom tools, plugged into yours
MCP is the USB port of AI: an open standard that plugs a model into any tool. What sits at the end of the cable, we build to your measure, with rights per agent.
A shared memory: what a team has understood stays available, can be found by meaning as well as by words, and gently fades when nobody reads it anymore. A document attic: years of tenders, quotes and meeting notes, cut into passages the model can find, whether typed, scanned or photographed. It is a search system plugged into the model; technicians call it RAG.
Relays to your everyday tools: sales management, invoicing, shared documents, the website. Each agent is identified and gets the rights of its role, no more. And your website itself can be fed by an agent: it publishes what you allow it to publish, and nothing else.
What goes in and what goes out
What an agent drops into your knowledge base can wait for validation, or go straight in. It is your choice, and it is set tool by tool: we build the one that looks like you.
Taking over a prototype made with AI
You prototyped an application, and it works. That is good news: the idea is proven. It is not a product yet.
We take the prototype as it is, and we make it last: a structure any developer can pick up, building blocks maintained by their community instead of copies, tests on real data, a go-live that replays identically, maintenance that does not depend on the person who prototyped it.
Everything that was generated is read before it is kept. What holds stays; what rebuilt a proven component by hand is replaced by that component. The prototype showed what to build; we build how it lasts over time.
Reading your documents with a model
Invoices, contracts, meeting notes, forms: the model reads, extracts, sorts. You decide what goes through without a look and what waits for a human.
Read
Typed, scanned or photographed: a document comes in, the model pulls out what you asked for, reference, amount, date, customer, and files it where it belongs.
Validate
Each extraction can go through a validation queue, or not. By document type, by amount, by source: the dial is yours.
Plug in
The result enters your tools through the same relays as everything else: your management software, your accounting, your website. No retyping.
Your content, readable by agents
Generative engines read your pages. We make sure they find what you want to show, and nothing else.
Our CMS describes every page for classic and generative engines, offers them a dedicated reading plan and a stripped-down version of each page. What is exposed is chosen page by page: not everything is meant to be read by a machine.
On the administration side, an agent can write, translate, illustrate, update, with a key that grants only those rights. Your contributors keep the hand: they publish, the agent proposes.
The dial is yours
With validation or without, autonomous or under review, a single model or several: we do not sell a setting, we build the tool that looks like you, and we tell you what each setting costs and exposes.
Let's talk about what you want to hand over to AI
And about what you want to keep.