Services
Data platforms, AI, operations software and advisory from one core team and a network of dedicated engineers.
01 / Service lines
Pick the line that matches your question. Each page shows the problems we solve, how we deliver, what you get and the proof. Operations software, AI workers and document AI follow below, and workshops have their own page.
Databricks
Azure
Terraform
Python
MLflow
Docker
KubernetesOperations and automation
Three focused offers for organisations that run on documents, planning and spreadsheets. Each one connects to the systems you already use and stays in your hands.
02 / Approach
The same standards apply whether we build a platform, an AI pipeline or an app. They are the reason your team can run the result without us.
A defined scope, a named architecture and an agreed end state, before anything is built.
Private networking, Key Vault and Unity Catalog governance in place before the first pipeline runs.
Every workspace, policy and catalogue arrives as a reviewed pull request. Dev, test and production run the same code.
Documented architectures and knowledge transfer, so your teams can own and evolve the platform.
03 / Start here
Both are fixed in scope and end in a written result you can act on. Planning and quote follow a first conversation.
Typical duration: 2 to 3 days
In 2 to 3 days we map how data and documents flow today and rank the three AI or data use cases with the best value for effort.
What you get
Typical duration: 3 days
We check cost, security with the Security Analysis Tool, governance with Unity Catalog and delivery with Asset Bundles and CI/CD, and give you a prioritised fix list.
What you get
Longer engagements are on the engagement models page. All engagement models
Workshops and training: hands-on sessions for company teams and for students. See the workshops
04 / Proof
Outcomes are quoted from our case studies. Your result depends on your data, your teams and your starting point.
Case study
99.5% time reduction, invoice processing reduced from 2 days of manual work to under 10 seconds.
Case study
Data Product and AI teams actively adopting the Data Product Infrastructure for their products, with clear onboarding paths and documentation
Read the caseCase study
Reduced infrastructure provisioning time from weeks to hours through Terraform and Bicep automation
05 / FAQ
No. Databricks is our deepest platform and we are a Databricks partner, but we also build on Azure services such as Event Hubs and Entra ID, and we build the applications and AI systems that use the data. We tell you honestly when another tool fits better.
Mostly project-based, with a defined scope, a named architecture and an agreed end state. A fractional lead role runs for a few days a week instead.
You own the result. Everything is code in your repositories, documented, with knowledge transfer so your teams can run and evolve it.
With the Data & AI quick scan: 2 to 3 days to map how data and documents flow today and rank the three use cases with the best value for effort.
Next step
Tell us what you run today and what you want to change. We will say which service line fits, or that none does.
Currently accepting projects for Q4 2026