Production AI

We design, build, and operate AI systems that have to work inside real products: reliable, observable, cost-aware, and ready for European production environments.

Capabilities

AI architecture strategy

Reference architectures, ROI models, build-vs-buy decisions, and delivery sequencing for teams that need AI inside the product, not beside it.

Reference Architecture Build vs Buy Roadmapping

AI product engineering

Real-time AI pipelines, agentic workflows, retrieval layers, model orchestration, and the integrations that make AI usable in an existing codebase.

RAG Agents Model Orchestration

AI platform operations

The operating system around AI: evals, observability, guardrails, governance, cost controls, and model lifecycle management.

Evals Observability Guardrails Cost Control

Sovereign deployment

Deployment in your own Azure or AWS tenant, dedicated managed cloud, or on-premise environment with EU data residency as the default posture.

Azure / AWS EU On-premise EU Data Residency

Compliance readiness

EU AI Act readiness from day one, including risk classification, human oversight, audit logging, and explainability where the use case requires it.

EU AI Act Audit Logging Human Oversight

Operate and scale

SLA-backed operate models, on-call continuity, incident review, and release discipline for AI features that keep running after launch.

SLA Operations Incident Review 24/7 On-call

How we work

1

Use case and risk discovery

We map the product workflow, data boundaries, compliance obligations, and the operational risks that can break an AI feature in production.

2

Architecture and eval design

We define the model layer, provider strategy, deployment target, observability signals, and evals before the build becomes expensive.

3

Production slice

We ship a narrow, real workflow in the target environment so integration, latency, data quality, and user trust are tested early.

4

Governance and handover

Guardrails, audit trails, runbooks, cost ceilings, and engineering documentation are built into the release path, not added at the end.

5

Operate and iterate

After launch, we monitor quality, cost, incidents, model changes, and customer feedback so the AI system improves instead of drifting.

Next steps

We combine the industry’s best service delivery standards with unprecedented solution personalization practices.

Book a meeting

Schedule a no-obligation meeting with us. Share your availability and we will arrange a meeting at your earliest convenience.

Get in touch

Meet the team

Get personalized guidance. Meet our team for an initial use case discovery.

Design and development

We craft a solution design tailored to your success. Development follows, once we have your sign-off.

Launch with confidence

Go live with ease. Our ongoing support ensures your technology performs at its peak.