One system around your company. Information comes in, AI does the work, your team approves and the system gets better with every approval.
Knowledge graph
Four ways companies use AI. Most stop at the first. We build the second and the third, often combined in one flow. The fourth we are building for ourselves first.
Where most companies are
A chat window next to your work. One colleague automates, the rest cannot use it. Confidential files end up anywhere, and when the subscription or the colleague goes, you start from zero.
ChatGPTLive at our clients
One step where you know exactly what should come out: reading a document, comparing photos, drafting an email. Built into your own software.
Rolling out at our clients
You do not know the outcome upfront. It runs a whole workflow: sends out quote requests, follows up, compares the answers and puts the best options in front of you.
Building it for ourselves first
Calls, mails and documents come together in one place. AI does not only execute, it spots where your company needs attention, before anyone asks.
Follow one purchase order from Debaere through the system. Nobody retypes a thing.
AI reads mails, documents and orders and recognises the client, the file and the question.
Files, clients, prices and history together, for every colleague and every agent.
Agents link, follow up and prepare quotes, planning and invoices.
Per task you decide what AI may do on its own. Everything is traceable.
The system learns from every correction and flags what needs attention.
Your ERP and accounting stay. Mail moves from personal inboxes to one shared inbox, so knowledge comes together instead of staying with one person. We connect to what you have and build only what is missing. No big migration before you see results.
Connected
Built by us
Context management
We centralise and guard all the context that goes around, so every agent works with correct, current information. Nothing is read twice, which saves cost, and no agent works with an overloaded context, which keeps the quality high.
Same flow, different files. Pick your sector for concrete examples.
At Dermul, AI reads incoming mail, follows up certificates and proposes the next action itself. The team approves. Rolling out now.
Read the case →Today · Dermul
3 waitingYou decide per task what may happen on its own.
It asks, and shows the source it used.
It takes the retyping and chasing. People keep the decisions and finally have time for work that adds value.
Your data, and everything the system learns, stay yours.
Tell us what costs your team the most time. We show where AI and software make the biggest difference, and tell you honestly whether we can help.
