Software Development

Full-stack software, engineered to last.

Enterprise-grade software built for reliability, security, and scale — the unglamorous engineering discipline that makes everything else possible.

Clean Architecture

Boundaries that hold up as the system grows.

Tested By Default

Coverage where it matters, not vanity metrics.

Secure By Design

Threat-modelled before the first commit lands.

Built To Scale

Performance budgets enforced in CI, not hoped for.

Start a Build → Explore the Stack

WebMobileBackendCloud

main — all checks passing

ci / pipeline #2847● 3m 12s

Lint & typecheck18s

Unit tests — 1,28446s

Integration suite1m 09s

Security scan22s

Deploy → staging37s

The Stack

Every Layer, Deliberately Chosen

Click through the layers. Each one is a decision with trade-offs we will actually explain to you, rather than a logo wall.

What the user actually touches

The front end is where quality is judged, so it gets the same engineering rigour as the back end — typed end to end, component-tested, and measured against a real performance budget rather than a lighthouse screenshot taken once.

Framework choiceReact, Next.js, Vue, or SvelteKit — picked for the product, not our habits.

Performance budgetBundle size and Core Web Vitals enforced in CI; regressions block the merge.

AccessibilityWCAG 2.2 AA as a baseline, tested with real assistive tech, not just linters.

Design systemTokenised components so the tenth screen costs less than the first.

TypeScriptReactNext.jsVueSvelteKitTailwindStorybookPlaywright

The seam that everything depends on

APIs outlive the clients that call them, so they get versioned contracts, generated types, and backwards-compatibility rules from day one. Breaking a consumer silently is the failure mode we design hardest against.

Contract-firstOpenAPI or GraphQL schema agreed before implementation begins.

Generated typesClients and servers share one source of truth; drift is a build error.

Versioning policyAdditive by default; breaking changes get a deprecation window.

Rate & authScoped tokens, per-consumer limits, and audit logging on every route.

RESTGraphQLgRPCOpenAPItRPCOAuth 2.1JWT

Where the actual rules live

The domain logic is kept deliberately boring and deliberately isolated — no framework code, no database calls buried three layers deep, and no business rule that exists in only one engineer’s memory.

Domain isolationBusiness rules testable without a database, a queue, or a network.

IdempotencyRetries are safe by construction, because distributed systems retry.

Async where it fitsQueues and workers for anything that must not block a request.

Observability built inStructured logs, traces, and metrics emitted from the start.

Node.jsGoPythonJavaKafkaRabbitMQTemporalOpenTelemetry

The part that is hardest to change later

Schema decisions are the most expensive ones to reverse, so they get the most scrutiny up front. Migrations are reversible, tested against production-shaped data, and never run unattended on a Friday.

Schema designNormalised until measurements say otherwise, then denormalised on purpose.

Reversible migrationsEvery migration has a tested down path before it ships.

Backups that restoreRestores are rehearsed on a schedule, not assumed to work.

Read/write separationReplicas and caching introduced when load justifies the complexity.

PostgreSQLMySQLMongoDBRedisClickHouseElasticsearchPrisma

Boring, repeatable, recoverable

Infrastructure is code, reviewed like code. Environments are reproducible from an empty account, deployments are one command, and rolling back is faster than rolling forward when something goes wrong at 2am.

Infrastructure as codeTerraform or Pulumi; no console clicks that nobody can reproduce.

Zero-downtime deploysBlue/green or rolling, with automated rollback on health-check failure.

Cost visibilityPer-service cost attribution so spend is a decision, not a surprise.

Disaster recoveryDocumented RTO and RPO, and a restore drill that has actually been run.

AWSGCPAzureKubernetesDockerTerraformGitHub ActionsGrafana

How We Deliver

Five Stages, No Surprises

Fixed rhythm, visible progress. You see working software early and often rather than a status report that says 60% for three weeks running.

Discover

We map the problem, the constraints, and the definition of done before estimating anything.

Architect

Data model, service boundaries, and the risky parts prototyped before full build begins.

Build

Two-week increments, demoed live. Every increment is deployable, not just committed.

Harden

Load testing, security review, and the failure paths exercised on purpose before launch.

Launch & Run

Phased rollout, monitoring in place, and a support model agreed before go-live.

System architecture

Architecture

Boundaries drawn before the first commit.

Most systems do not collapse under load — they collapse under their own coupling, one shortcut at a time. We spend the first weeks deciding where the seams go, because that is the decision that determines what the next three years cost.

Service boundaries mapped to business capabilities, not team org charts
Every integration point documented with its failure behaviour
The riskiest technical assumption prototyped in week one
Architecture decision records so future engineers know the why

Engineering Practice

The Habits That Compound

None of these are exciting. All of them are why a codebase is still pleasant to work in three years after launch.

Code Review, Properly

Every change reviewed by someone who will have to maintain it. Reviews focus on design and edge cases, not formatting a linter should catch.

Process

Continuous Integration

Main is always deployable. Broken builds get fixed before anything else, because a red pipeline blocks the whole team.

Process

Security Reviews

Threat modelling at design time, dependency scanning in CI, and penetration testing before anything touches production data.

Security

Documentation That Lives

Architecture decision records, runbooks, and onboarding docs kept in the repo where they get updated with the code.

Knowledge

Performance Budgets

Latency and bundle-size ceilings enforced automatically. A regression fails the build rather than being noticed in production.

Performance

Observability First

Structured logging, distributed tracing, and dashboards built during development, not bolted on after the first incident.

Operations

Least Privilege

Scoped credentials, short-lived tokens, and no shared logins — including for us during the engagement.

Security

Knowledge Transfer

Pairing, walkthroughs, and handover docs so your team owns the system rather than depending on ours.

Handover

Dependency Hygiene

Upgrades applied continuously in small batches, rather than a terrifying big-bang migration every two years.

Maintenance

Track Record

Numbers From Delivered Work

Measured across the engagements where we owned delivery end to end.

99.95%Median uptime

Across production systems we built and continue to support.

<15minDeploy to production

From merged pull request to live, fully automated.

84%Test coverage

On domain logic specifically, where regressions actually hurt.

0Critical breaches

Across every system we have shipped and operated to date.

Engineering quality

Quality

Tests that catch real regressions.

Coverage percentage is a vanity metric. What matters is whether the suite fails when the behaviour breaks, and whether it stays green when the code is merely refactored. We write tests for the second property as hard as the first.

Fast unit tests on domain logic, run on every save
Integration tests against real databases, not mocks that lie
End-to-end coverage on the paths that generate revenue
Flaky tests treated as bugs and fixed, never re-run until green

Engagement Models

How Teams Usually Work With Us

Three shapes, depending on whether you need a system built, a team extended, or an existing codebase rescued.

	Project Build	Team Extension	Codebase Rescue
Fixed scope and timeline
Embedded in your standups
Architecture owned by us
Works on your existing code
Includes discovery phase
Knowledge transfer built in
Typical duration	3-9 months	Ongoing	6-14 weeks

Software is only finished when it is retired. Everything before that is maintenance — so we optimise for the engineer who inherits it, not the one who ships it.

Our engineering principle

Full-Stack Engineering

Frontend, backend, and infrastructure handled by one accountable team, not three disconnected vendors.

Frontend, backend, and infra under one roof
Modern, maintainable, well-documented code
Built by engineers who own it long-term

60+Platforms shipped

Reliability & Testing

Real test coverage and monitoring from day one, not an afterthought bolted on after the first outage.

Automated testing across critical paths
Monitoring and alerting from day one
Incident response built into the process

99.9%Avg. uptime

Scalable Architecture

Built for the business you'll be in two years, not just the version you need to demo next week.

Architecture built to handle real growth
No painful rewrite when you hit scale
Documented for the team that inherits it

0Critical incidents shipped

Technology

Tools We Reach For

Chosen per project on merit. If your team already runs something well, we work in that rather than rewriting it for our comfort.

TypeScriptGoPythonRustJavaKotlinC#Node.jsTypeScriptGoPythonRustJavaKotlinC#Node.js

ReactNext.jsVueSvelteKitReact NativeFlutterSwiftDjangoReactNext.jsVueSvelteKitReact NativeFlutterSwiftDjango

PostgreSQLRedisKafkaKubernetesTerraformAWSGrafanaClickHousePostgreSQLRedisKafkaKubernetesTerraformAWSGrafanaClickHouse

Questions

What Clients Ask Before Signing

The commercial and practical questions, answered directly.

We estimate after discovery, never before, and we give ranges rather than single numbers. Our estimates land within the stated range roughly four times in five; when they do not, it is almost always because a dependency outside the build — a third-party API, a data migration, an approval — behaved differently than everyone expected. We flag those as risks explicitly at the start rather than absorbing them quietly and blowing the date.

You do, from the first commit. Work happens in your repository under your organisation where practical, and the licence to everything we write transfers to you outright. There is no proprietary framework you are quietly locked into and no ongoing licence fee for code we wrote for you.

That is a good outcome and we plan for it. Knowledge transfer is part of every engagement, not an upsell: pairing sessions, architecture walkthroughs, and runbooks written for someone who was not in the room. Several clients have moved to fully in-house teams and we consider those the successful ones.

Yes, and it is a large part of what we do. The first step is an honest assessment — sometimes the right answer is incremental improvement, sometimes it is a strangler-fig migration, and occasionally it genuinely is a rewrite. We will tell you which one we think it is and why, including when the answer is cheaper than you expected.

Scope changes are normal; unmanaged ones are the problem. Each increment ends with a demo and a re-prioritisation, so changes get traded against remaining scope openly rather than absorbed until the timeline quietly slips. If a change genuinely needs more time or budget, you hear that when it is raised, not at the end.

Yes, on a defined support agreement with agreed response times — but it is optional, and we build so that it is optional. If your team is ready to run it, we would rather hand over cleanly than create a dependency neither of us needs.

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