Artificial intelligence,
where it actually helps.
Agents, automation and bespoke integration.
We use it every day, for ourselves and for our clients. We know it well enough to tell where it creates value - and where a traditional function is more than enough.
AI, the way we mean it.
We use it every day, for ourselves and for our clients. We know it well enough to tell where it truly helps - and where it doesn't.
- 01
A tool we steer
It doesn't make decisions. It speeds the work up, but the choices stay human: ours and yours, always reasoned.
- 02
Full transparency
We're open about how and where we use it. Nothing hidden: if there's AI in a project, you'll know.
- 03
Where we put it to work
In development and testing, documentation, automations and quality checks. And we build the same solutions inside our clients' workflows.
- 04
Support, not replacement
It fascinates us and we believe it's the future. But it will stay a support for the people who work - not a replacement for them.
We use AI every day, for ourselves and for our clients. It's a powerful tool - but we're the ones steering it.
Data foundations. The step before AI.
Before AI goes to work in a company, something dull has to happen first: the data in one place, in a readable format. It's the work that makes a company ready without tying it to its own ERP, to the vendor that sold it, or to whichever model is current. And it pays off anyway, even if AI stays a conversation for next year.
How we work on dataAI Agents. Fewer manual steps, more logic.
We build specialised software agents that don't just answer a command, but orchestrate complex flows autonomously, interfacing directly with your APIs and databases. AI becomes a module of the infrastructure, designed to act in a deterministic and traceable way.
Document processing
Automatic extraction and normalisation of data from unstructured sources - contracts, logs, invoices - making it ERP-ready.
→ zero manual data entry
Flow reconciliation
Autonomous monitoring and resolution of anomalies in inventory, order or financial transaction flows.
→ fewer surprises at month-end
Semantic integration
Systems that translate user intent into structured queries, making historically siloed applications cooperate.
→ silos start talking to each other
We don't add AI where a traditional function will do. We use language models only when data variability calls for flexibility, keeping the software control strict and secure.
AI for business. Intelligence where it counts, without chasing the hype.
Adopting AI in a company shouldn't be an upheaval, but a targeted optimisation. We help businesses spot operational friction and integrate language-model solutions to boost department efficiency, while protecting the confidentiality of company data.
Knowledge management
Centralising the company's information assets - manuals, procedures, project history - instantly queryable in natural language by teams.
Company knowledge stops living in a few people's heads.
Process automation
Cutting the time spent on repetitive data-entry, request classification and workflow routing.
Repetitive work shrinks, freeing up the team's capacity.
Decision support
Protected predictive-analysis and synthesis tools, built to support management with advanced reporting drawn in real time from internal data.
Management decides on fresh data, not yesterday's reports.
Every business AI solution is built to strict privacy and compliance standards, ensuring your sensitive data stays confined within the secure perimeter of your infrastructure.
We use it on ourselves, before we use it on you.
We don't sell what we don't practise. AI has been part of our daily workflow since before we proposed it to clients: we use it, we hit its limits, we learn where it holds and where it doesn't. If we put it in your hands, it's because it's already in ours.
- $ dev · test
Development & testing
We write and verify code faster, with review and architecture decisions always in our hands.
- $ docs
Documentation
We keep documentation readable and up to date, without it becoming a separate job.
- $ automation
Internal automation
We delegate the repetitive tasks in our own flow, so we stay on the work that really matters.
- $ qa
Quality checks
We catch what slips through sooner: regressions, edge cases, inconsistencies - before they reach production.
The same solutions we test on ourselves end up, already proven, in our clients' flows. It's a powerful tool, and exactly for that reason we treat it with method - without fear, without shortcuts.