Services
From a one-week architecture review to building and running a production system, we cover the work between an idea and software your users rely on.
AI engineering
Generative AI that does real work: assistants grounded in your own data, agents that act on your business systems, and the evaluation and guardrails needed to run them safely in production.
Typical work
- Assistants and search over internal documents and knowledge bases (retrieval-augmented generation)
- AI agents connected to business systems through APIs and the Model Context Protocol
- Copilots and automation inside existing business applications
- AI gateways for cost control, model routing and access management
- Taking AI proofs of concept to production
- AI readiness and architecture assessments
AI agent governance and security
AI agents you can trust with real systems and real data: strict control over what they can access and do, protection against manipulation and data leaks, and measurable evidence of their quality before and after release.
Typical work
- Threat modelling and security reviews of AI agents, their tools and MCP servers
- Least-privilege access, identity and secrets management for agents and the tools they call
- Defences against prompt injection, data exfiltration and unsafe tool use, following the OWASP guidance for LLM applications
- Human approval for high-impact actions, with complete audit trails
- Evaluation and red-teaming to measure accuracy, quality and safety before every release
- Monitoring, usage limits and incident response for agents in production
- Governance policies and controls that support compliance with regulations such as the EU AI Act
Cloud architecture and engineering
Cloud platforms on Microsoft Azure, Amazon Web Services and Google Cloud that are secure, reliable and affordable to run, designed and built with your team.
Typical work
- Architecture design and reviews against well-architected principles
- Landing zones, networking and identity foundations
- Migration and modernisation to containers, Kubernetes and serverless
- Infrastructure as code with Terraform, Bicep, CloudFormation and CDK
- Continuous delivery pipelines and platform engineering
- Cost optimisation, security hardening and observability
Platforms: Microsoft Azure, Amazon Web Services, Google Cloud.
Software development
Cloud-native applications, APIs and integrations, built alongside your engineers and handed over with the code, documentation and pipelines your team needs to carry on.
Typical work
- Web applications, backend services and APIs
- Event-driven systems and integrations between business applications
- Step-by-step modernisation of legacy applications
- Automated testing and delivery
- Technical due diligence and code reviews
Technical training
Hands-on workshops on cloud, AI and software architecture for engineers and technical leaders, with a prepared lab environment for every participant.
Typical work
- Cloud architecture on Azure, AWS or Google Cloud
- Building generative AI applications and agents
- Securing and governing AI agents
- Serverless, event-driven integration and infrastructure as code
- AI strategy and governance for technical leaders
Ways to work together
- Assessment
- A fixed-scope review of an architecture, a cloud platform, an AI initiative or the security of your AI agents, usually one to three weeks, ending with clear findings and a prioritised plan.
- Project delivery
- A defined outcome, such as a new application, a migration or an AI feature, designed and built with your engineers from first design to production.
- Ongoing advisory
- Senior architecture and technical leadership support for a few days a month, for teams that need expert input without a full-time hire.
- Training
- Workshops delivered on site or remotely, adapted to your platform, your use cases and your team’s level.
Not sure where to start?
Describe the problem in a few lines. We will suggest the right kind of engagement, or tell you if we are not the right fit.