AI & Intelligent Systems
We help decide which processes are worth automating with AI, then build them: retrieval over your own documents, assistants with proper access control, and agents whose actions a person can review.
Explore AI engineeringAI, Data & Cloud Engineering
Intelligence,
Engineered.
Architecture and hands-on engineering for AI, data, and cloud systems.
We help organizations in Belgium and across Europe decide what to build, then build it with their own teams: data platforms on Databricks, Kubernetes platforms on AWS and Azure, and AI workflows that make it past the pilot.
CONNECTED EXPERTISE
What we do
AI, data, and cloud,
built by the same team.
An AI assistant is only as good as the data it reads, and that data is only as reliable as the platform it runs on. We work on all three layers, so a problem in one is not left for another team to find.
Data & Analytics Engineering
We design and build data platforms on Databricks, AWS and Azure, starting from the definitions people argue about. Data contracts, tested pipelines, and a named owner for every dataset.
Explore Data engineeringCloud & Platform Engineering
We build and harden cloud and Kubernetes platforms on AWS, Azure and OpenShift, with infrastructure in Terraform, recovery that has been tested, and on-call ownership that is written down.
Explore Cloud engineeringArchitecture & Advisory
Before any build: an independent view on the decision itself. Architecture reviews, platform selection, AI strategy, and roadmaps.
Typical engagements
Problems we are often
asked to solve.
Six situations that come up again and again. Most engagements start with one of them, scoped to a single team or system.
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Intelligent Process Automation
Invoices, claims, or support tickets that people copy between systems by hand. We automate the routine steps and leave the judgment calls to people.
Cloud Modernization & Optimization
Moving workloads out of a data center, or tidying up a cloud estate that grew faster than anyone planned, including the bill.
AI-Driven IT Operations
Help for on-call engineers: pull together the relevant logs, metrics, and runbook for an incident, and suggest a next step.
Enterprise AI Applications
An assistant that answers from your own policies, contracts, or technical documentation, and only shows each user what they are allowed to see.
Data Platform Modernization
Replacing an ageing warehouse or a tangle of scripts with a lakehouse, without a big-bang cut-over.
Platform Reliability & Engineering
Fewer surprises in production: health checks that mean something, alerts someone acts on, and a restore that has actually been tested.
Don’t see your situation here? Ask anyway.All engagements in detail
How an engagement runs
Four steps.
Each one ends with something written down.
We work inside your team rather than next to it. Every step leaves your people with something they keep, so the work is still useful if we stop after the first one.
More about how we work01
Scope
A few conversations with the people who own the problem and the systems. You get a short written scope: what success looks like, and what is deliberately left out.
02
Design
Options with their costs and trade-offs, a recommendation, and the decisions recorded as ADRs. Assumptions we cannot verify yet are listed so they get tested early.
03
Build
Working increments in your repositories and your CI, reviewed by your engineers. Tests, security checks, and monitoring ship with each increment.
04
Hand over
Runbooks, a handover session, and at least one deploy or restore done by your team while we are still around to help.
AI strategy
Where AI is worth it,
and where it isn’t.
The hard AI questions are rarely about the model. They are about which process to start with, whether the data is good enough, and who signs off on what the system does. We answer those first, then build.
How we approach AI strategyWHAT YOU GET
Three outputs, in order.
A ranked shortlist of use cases, each with a risk and a success measure. A 90-day plan with named owners. Then a first workflow in production, with the tests that show it works.
AWSAzureDatabricksKubernetesOpenShiftTerraform
The tools we work with most. We use what fits your environment.Insights
Engineering notes.
01 / TOPIC
AI in production
Evaluation sets, permissions, and getting from a prototype to daily use.
02 / TOPIC
Data platforms
Contracts, safe reruns, reconciliation, and migrating without a big bang.
03 / TOPIC
Cloud operations
Health checks, failure domains, restore drills, and on-call ownership.
Contact
Tell us what you’re working on.
A few lines about the situation is enough. We reply with the questions we would ask first, and an honest view on whether we can help.