AI agents and automation.
In production, not slides.
AI agents, process automation and custom AI software for business. Deployed on your own servers or in the cloud, wired into the systems you already run.
AI services, from audit to production.
Five ways companies actually put AI to work. Each one starts with a process you run by hand today.
AI agents for business
Agents that read documents, answer customers and draft quotations inside your own systems. Supervised and logged.
- document processing
- customer support
- quotation drafting
AI readiness audit
One week in your real processes, and a ranked shortlist of what AI should automate first.
- ranked use cases with numbers
- build vs buy call
- written 90-day plan
Private AI development
Private LLMs on hardware you own, for data that cannot leave the company.
- self-hosted open models
- GDPR and EU data residency
- hybrid cloud routing
AI for e-commerce
Storefront assistants, catalog generation and fitment checks that stop returns. We run a store ourselves.
- storefront AI assistant
- description generation
- fitment checks
How an AI project runs. Four steps, no magic.
AI audit
One week to find where AI pays back fastest, ranked by hours saved against cost to build.
Pilot
In 2-4 weeks it runs in one real process, with a human approving every output.
Deployment
We integrate with your ERP, CRM and file systems, train the team, hand over control.
Care
SLA, monitoring and model updates, so the system gets reviewed instead of aging out.
AI for your online store, on any platform.
We run e-commerce ourselves, so we know where it hurts: unanswered product questions, empty descriptions, bestsellers out of stock, returns nobody prevented. See what AI does for an online store.
Engineers, not salespeople.
Every day we deploy and run AI inside our own companies: a windows and doors manufacturer, an auto parts e-commerce business and a real estate SaaS platform. That is where the opinions on this site come from.
So we have already paid for the mistakes. We know what an on-premises model costs to keep alive in month nine, and which automations get switched off within a fortnight.
We use daily what we ship to others.
AI in business, answered straight.
The questions every management team asks in the first call.
How much does it cost to implement AI in a company?
Three things drive it: how many systems the AI has to touch, how clean your data is, and whether it runs in the cloud or on your own hardware. A pilot in one process is the cheapest way to get a real number.
How long does an AI implementation take?
An audit takes one week. A working pilot in a single process takes two to four weeks. Full deployment across a department runs six to twelve. Anyone promising a company-wide transformation in days is selling a demo.
What is the difference between an AI agent and a chatbot?
A chatbot answers a question and stops. An agent has a goal, tools and permission to act: it opens the email, reads the attached PDF, finds the customer in your CRM and writes the data in.
Is our company data safe if we use AI?
It depends on the deployment. Business API plans contractually forbid training on your data and EU regions keep it inside the bloc. Where a contract rules that out, the model runs on your own servers instead.
Do we need our own servers to run AI?
Usually not. On-premises pays off when volume is high and steady and the data is genuinely sensitive, and the hardware alone often starts near 10-15k EUR. For a first project, cloud with an EU region is the rational start.
What if we have no IT department?
That is the normal case here. We handle the engineering, deployment and monitoring, and hand your team a system they operate rather than maintain. We need one person who knows the process well enough to spot a wrong output.
Which process should a company automate with AI first?
The one that repeats daily, follows rules a person can say out loud, and eats hours of somebody's week. Usually document intake, customer questions or quotations. Never a chaotic process: AI only speeds up chaos.
Field notes.
On-Premises vs Cloud AI: How to Choose in 2026
When AI has to run on your own servers, when the cloud wins, and how hybrid works in practice. Five questions that settle the decision, with costs and GDPR.
read ->7 E-commerce Processes Worth Automating With AI in 2026
The seven online store processes AI actually improves - product questions, descriptions, stock, pricing, fraud, returns and translation - with the risk in each.
read ->What AI Agents Actually Do in Companies: 4 Real Use Cases
What AI agents really do inside companies in 2026: document processing, customer support, quotations and internal knowledge - plus the limits vendors leave out.
read ->Which process should AI take over first?
Thirty minutes, no deck. Tell us how the work is done today and we will tell you where AI pays off and where it does not.
Book a free 30-minute call