Backend Engineering
Services that carry transactional load, expose stable contracts and remain debuggable under pressure.
- Go
- Python
- TypeScript / Node.js
- gRPC
- REST
- GraphQL
- Domain-driven design
Capabilities
A deliberatelynarrow stack,operated properly.
We work with technologies we can run in production and debug at three in the morning. Breadth is easy to claim and expensive to maintain; this list is what we will actually stand behind.
Capability groups
Frontend Engineering
Application interfaces for operational work — dense, accessible and fast on the hardware people actually use.
- Angular
- TypeScript
- SCSS
- Web Components
- Accessibility (WCAG 2.2)
- Design systems
Mobile
Applications for field and customer use, built for unreliable networks and managed devices.
- Swift
- Kotlin
- Offline-first sync
- Push & background processing
- MDM distribution
Data Platforms
Operational and analytical data systems where lineage, quality and access control are part of the design.
- Palantir Foundry
- PostgreSQL
- MongoDB
- Elasticsearch
- dbt
- Airflow
- PySpark
Cloud & Infrastructure
Reproducible environments with reliability targets that are measured rather than asserted.
- Kubernetes
- Docker
- Terraform
- Helm
- ArgoCD
- AWS
- Azure
- Google Cloud
Security
Threat modelling, identity architecture and secure delivery practice applied during design.
- HashiCorp Vault
- OpenID Connect
- OAuth 2.1
- OPA
- Semgrep
- Trivy
- Threat modelling
Integration
Explicit contracts between systems, with the patterns matched to the timeliness the business needs.
- Kafka
- NATS
- RabbitMQ
- Debezium
- Change data capture
- API gateways
Observability
Systems that explain their own behaviour, so incidents are diagnosed rather than guessed at.
- OpenTelemetry
- Prometheus
- Grafana
- Structured logging
- Distributed tracing
- SLO design
DevOps
Release engineering that makes deployment routine, reversible and independent of any one person.
- CI/CD pipelines
- GitOps
- Progressive delivery
- Automated testing
- Release management
Enterprise Architecture
The decisions above the code: boundaries, ownership, sequencing and the trade-offs behind them.
- Architecture decision records
- Modernisation planning
- Build-vs-buy analysis
- Technical due diligence
- Governance design
02How we choose
Technology decisions we are willing to defend.
- 01
Boring where boring is correct
A relational database, a queue and a well-factored service solve most problems that get proposed as distributed systems. We reach for complexity when the requirement earns it, and we say so when it does not.
- 02
Operability outranks elegance
A design that is beautiful and undebuggable at 3am is a bad design. We weight observability, failure modes and the on-call experience as heavily as the architecture diagram.
- 03
Lock-in is a cost, not a taboo
Managed services often earn their price. We name the lock-in explicitly, quantify what leaving would cost, and let you make the trade knowingly rather than discovering it later.
- 04
The team that inherits it matters
The right stack depends partly on who maintains it afterwards. We will recommend the technology your team can own over the one we would personally enjoy more.
- 05
Every dependency is a decision
Each library and SDK is a supply-chain, licensing and data-processing commitment. We keep the dependency surface small and review what we add.
- 06
Measure before optimising
Performance work starts with profiling against realistic load. Optimisations chosen without measurement usually move cost somewhere less visible.
Working insomething else?
We assess and build in existing estates — Java, .NET, PHP, on-premise, hybrid — as often as we start from a blank repository. A different stack is not a reason to stop talking.