Fourteen disciplines,
one senior team.

Each service is delivered by practitioners who have shipped, operated, and repaired the systems they now design. Engagements are coordinated by a single lead responsible for outcomes.

Warm-lit fiber optic strands glowing against a dark background

01 / Service

Custom Software Development

End-to-end design and delivery of bespoke applications built around a specific operational problem, rather than adapted from a generic template.

Use cases: Internal operations platforms, workflow systems, calculation engines, and specialised tools that off-the-shelf software cannot express.
Approach: Discovery, written architecture, incremental delivery on a stable trunk, continuous integration, and structured handover with runbooks.
Technologies: TypeScript, Python, Go, .NET, PostgreSQL, event-driven messaging, containerised deployment.
Value: A system that fits the way the organization actually works, is documented for the next engineer, and can be extended without archaeology.

02 / Service

Web Application Development

Modern web applications that behave correctly on unreliable networks, on modest devices, and under sustained load.

Use cases: Customer portals, transactional interfaces, back-office tooling, and data-heavy dashboards.
Approach: Typed front-end and back-end, server-rendered where it helps, automated accessibility and performance budgets.
Technologies: React, Next.js, Remix, Vue, Node.js, TypeScript, PostgreSQL, Redis.
Value: Interfaces that stay fast, accessible, and maintainable as the product grows.

03 / Service

Mobile Application Development

Native and cross-platform mobile applications built with the operational realities of mobile — battery, memory, connectivity — treated as first-class concerns.

Use cases: Field applications, consumer products, secure business apps requiring on-device data.
Approach: Native where the requirement demands it, cross-platform where it fits, with rigorous release management.
Technologies: Swift, Kotlin, React Native, offline-first data layers, MDM-friendly configuration.
Value: Applications that pass store review, respect the device, and can be updated safely.

04 / Service

Cloud Solutions

Cloud architectures designed for the actual workload — not for a diagram — with cost, resilience, and operability as design goals.

Use cases: Greenfield cloud environments, multi-region deployments, controlled migrations to a cloud provider.
Approach: Infrastructure as code, multi-account topologies, automated budgets, documented recovery procedures.
Technologies: AWS, Azure, GCP, Terraform, Kubernetes, Nomad, Cloudflare.
Value: A cloud footprint that scales predictably, recovers cleanly, and is understandable to the team operating it.

05 / Service

IT Infrastructure

Design and operation of the underlying infrastructure — compute, storage, networking, identity — for organizations that need reliable foundations.

Use cases: Hybrid environments, private data centres, edge deployments, high-availability requirements.
Approach: Baseline architecture, hardened images, monitoring by default, documented change control.
Technologies: Linux, virtualisation, container orchestration, structured networking, backup and recovery tooling.
Value: Infrastructure that operators trust and auditors can inspect.

06 / Service

Cybersecurity

Security engineering across architecture, identity, application code, infrastructure, and operations.

Use cases: Threat modelling, secure architecture reviews, incident preparation, hardening of existing systems.
Approach: Design for the attacker, minimise trust, centralise identity, treat dependencies as part of the perimeter.
Technologies: OAuth 2.1, OIDC, HashiCorp Vault, SPIFFE, SIEM platforms, dependency and container scanning.
Value: A system whose security properties can be explained, tested, and defended.

07 / Service

Data Analytics

Data platforms that put reliable numbers in front of the people who use them — from ingestion to metric to interface.

Use cases: Operational reporting, product analytics, executive dashboards, data warehouses.
Approach: Modelled warehouses, tested transformations, lineage visible in production, governance from day one.
Technologies: PostgreSQL, ClickHouse, BigQuery, Snowflake, dbt, Kafka, Airflow.
Value: Numbers leadership can trust, and a data platform the analytics team can extend.

08 / Service

Artificial Intelligence Integration

Careful integration of machine learning and language-model capabilities into existing products and workflows.

Use cases: Search and retrieval, classification, summarisation, structured extraction, assistive interfaces.
Approach: Evaluation before deployment, guardrails, human review where the cost of error is high, observable pipelines.
Technologies: Managed and self-hosted models, vector stores, retrieval pipelines, prompt and evaluation tooling.
Value: AI features that behave predictably in production and can be improved without rewriting the product.

09 / Service

API Development & Integration

Well-designed APIs — internal and external — and the integrations that connect a system to the rest of the organization.

Use cases: Public APIs, partner integrations, internal service contracts, third-party system connectors.
Approach: Contract-first design, generated clients, versioning discipline, deep observability.
Technologies: OpenAPI, GraphQL, gRPC, event streaming, webhook infrastructure.
Value: Integrations that don't silently break, and APIs your partners can adopt without a support call.

10 / Service

DevOps & Automation

The delivery pipeline as a product — designed, tested, and improved on the same terms as the software it ships.

Use cases: Continuous integration, deployment automation, environment management, developer platform work.
Approach: Standard pipelines, ephemeral environments, policy-as-code, self-service tooling for engineers.
Technologies: GitHub Actions, GitLab CI, Terraform, Argo, container registries, secret management.
Value: Faster, safer releases and an engineering team that spends its time on the product.

11 / Service

Quality Assurance

Testing treated as an engineering discipline that begins before the first line of code.

Use cases: Building test strategies for complex systems, rescuing test suites, embedding QA into delivery.
Approach: Layered testing — static, unit, integration, end-to-end, performance, resilience — automated in the pipeline.
Technologies: Vitest, Jest, Playwright, k6, JMeter, contract testing, chaos tooling.
Value: Confidence to ship on any given day, and defect rates that trend downward release over release.

12 / Service

Technology Consulting

Written technical advice: architecture reviews, technology selection, delivery diagnosis, and second opinions.

Use cases: Investment decisions, pre-migration reviews, executive briefings, engineering-organisation design.
Approach: Structured interviews, artefact review, written report with defensible recommendations.
Technologies: Method rather than tool — the deliverable is clarity, not code.
Value: A written record you can act on, share, and defend to a board.

13 / Service

Legacy System Modernization

Careful, incremental modernisation of critical legacy systems — without a big-bang rewrite.

Use cases: Aging monoliths, unsupported runtimes, systems whose original authors are unavailable.
Approach: Strangler-fig migration behind stable interfaces, exhaustive characterisation testing, decision logs.
Technologies: Selected per system — the discipline is the point.
Value: A path off the legacy system that the business can actually afford to walk.

14 / Service

Technical Support & Maintenance

Ongoing operation of the systems we build — and, selectively, systems built by others.

Use cases: Monitoring, on-call rotations, incident response, security patching, and controlled evolution of the system.
Approach: Documented runbooks, tested recovery procedures, SLO-based reporting, structured post-incident review.
Technologies: OpenTelemetry, Prometheus, Grafana, Loki, Sentry, PagerDuty-class tooling.
Value: A system that stays healthy without heroics, and a team you can call when it doesn't.