Services
What we do, and how we go about it
Six capabilities, described by the problem each one solves rather than by a list of adjectives. Most engagements combine two or three.
Product Engineering
End-to-end delivery of web and mobile products — architecture, build, release and the iteration after.
- TypeScript
- React
- Next.js
- Node.js
- PostgreSQL
- React Native
The problem
An idea is validated but there is no team to build it, or an existing build has stalled against its own architecture.
Our approach
We start from the domain rather than the framework: model the data, define the boundaries, then choose the stack that fits. Work ships in vertical slices, so something real is running early and every week after.
Typical deliverables
- Technical architecture and data model
- Production web or mobile application
- CI/CD pipeline and environments
- Test suite and documentation
- Handover or ongoing engineering
AI Engineering
Language models, retrieval and automation wired into real systems — scoped to what measurably works.
- Python
- TypeScript
- Claude API
- Vector search
- LangGraph
- FastAPI
The problem
There is a plausible AI use case, but no clear path from demo to something dependable enough to put in front of users.
Our approach
We scope to a task with a measurable success criterion, build an evaluation set before the feature, and keep the model behind an interface we can swap. Where a deterministic system is cheaper and more reliable, we say so.
Typical deliverables
- Use-case scoping and feasibility assessment
- Retrieval and context pipeline
- Evaluation harness and quality baselines
- Production integration with fallbacks
- Cost and latency instrumentation
Platform & Cloud
The infrastructure underneath: deployment, observability, cost control and the ability to change safely.
- Docker
- GitHub Actions
- Terraform
- AWS
- Cloudflare
- PostgreSQL
The problem
Deploys are manual and tense, incidents are diagnosed by guesswork, and nobody can say what the infrastructure actually costs.
Our approach
Infrastructure as code from the first environment, with observability treated as a feature rather than an add-on. We optimise for a team's ability to change things safely, not for a diagram.
Typical deliverables
- Infrastructure as code
- Automated build and deployment pipeline
- Logging, metrics and alerting
- Environment and secrets strategy
- Cost review and right-sizing
Data Engineering
Pipelines, warehouses and interfaces that turn operational data into something a team can act on.
- Python
- SQL
- dbt
- PostgreSQL
- Airflow
- DuckDB
The problem
The data exists across several systems, but answering a question takes days and two people disagree on the number.
Our approach
One definition per metric, versioned with the code that computes it. We build the pipeline to be re-runnable and the model to be explainable before building anything that visualises it.
Typical deliverables
- Ingestion and transformation pipelines
- Warehouse schema and metric definitions
- Data quality checks and monitoring
- Dashboards and reporting interfaces
Interface Design & Engineering
Design systems and front-end implementation held to the same standard as the systems behind them.
- Figma
- React
- Tailwind CSS
- TypeScript
- Storybook
- WCAG 2.2
The problem
The product works but feels unfinished, inconsistent between screens, or unusable for part of its audience.
Our approach
Design decisions become tokens and components rather than static files, so the interface stays consistent as it grows. Accessibility and responsive behaviour are acceptance criteria, not a later pass.
Typical deliverables
- Design tokens and component library
- Responsive interface implementation
- Accessibility audit and remediation
- Interaction and motion specification
Technical Consulting
Architecture review, technology selection and a written path forward when a decision is expensive to reverse.
The problem
A rebuild, a migration or a platform choice is on the table and the cost of getting it wrong is measured in quarters.
Our approach
We review the system and the constraints around it — team, budget, timeline — and produce a written recommendation with the trade-offs stated plainly, including the option of doing nothing.
Typical deliverables
- Architecture and codebase review
- Technology selection with trade-offs
- Migration or remediation plan
- Effort and sequencing estimate
Scoping
Not sure which of these you need?
That is a normal place to start. Describe the situation and we will tell you what the work actually looks like — including if it is smaller than you expected.