Industrialising AI on a group-wide Azure platform
Turning AI pilots into production services on a shared Azure platform, with automated delivery and an API management layer in front of every model.
04 Services
AI & Data
From AI pilots to AI in production, on data platforms you can govern, audit and keep in Europe.
01 Problems we solve
Where we usually step in.
- AI proofs of concept multiply, but few reach production and none share a platform.
- Teams call LLM APIs directly, with no control over cost, data exposure or model choice.
- Answers cannot be traced back to sources, which blocks legal and compliance sign-off.
- Data needed for AI sits in silos, with no pipeline, quality checks or lineage.
02 What we deliver
Concrete deliverables, not slideware.
01
AI platforms
Shared foundations on Azure OpenAI, Microsoft Foundry, Databricks or sovereign European models, ready for product teams.
02
LLM gateways
A single entry point for model calls, with quotas, cost tracking, logging and provider choice per use case.
03
Retrieval-augmented assistants
Assistants grounded in your documents with pgvector or managed search, where every answer cites its sources.
04
Document intelligence
OCR and LLM extraction for invoices, contracts and supporting documents, with human review where it counts.
05
Data pipelines
Ingestion, quality checks and feature preparation feeding analytics and models, versioned and monitored.
06
AI governance
Use-case inventory, risk classification and evidence for the EU AI Act, built into the delivery process.
03 How we work
Pick the engagement that fits the problem.
01
Consulting & audit
Architecture reviews, cloud and FinOps audits, platform roadmaps. A clear diagnosis and a plan your teams can execute.
02
Team extension
Senior engineers embedded in your squads, following your rituals and tooling, with knowledge transfer built in.
03
Delivery projects
A defined scope, a committed outcome: a landing zone, a migration, a CI/CD platform, an AI service in production.
04
Managed run
We operate what we build: monitoring, incident response, upgrades and cost control, under agreed service levels.
04 Related work
AI & Data in practice.
Have a platform to build, migrate or fix?
Tell us about it. An engineer, not a salesperson, will answer within two working days.
Start the conversation →