Architecture & design
Domain modelling, service boundaries, event-driven and CQRS patterns, and ADRs that record why decisions were made.
Service 04 — Complex Software Development
The hard problems, engineered to last.
Distributed systems, high-throughput data pipelines, regulated workloads and legacy modernisation — clean architecture that doesn't need a rewrite at ten times the load.
- 2-wkincrements
- 100%code owned by you
- SLOdriven
Why it matters
Anyone can ship a demo. Surviving real users and real data is the job.
The expensive failures are architectural: a data model that can't evolve, a system that only scales vertically, a monolith nobody dares deploy. We build for the second and third year of a product, with the discipline — tests, observability, documentation — that makes change cheap.
Stack
Opinionated architecture, pragmatic languages.
Languages
- Go
- Rust
- Java / Kotlin
- TypeScript / Node.js
- Python
Data & messaging
- PostgreSQL
- Kafka
- Redis
- ClickHouse
- Elasticsearch
APIs & front end
- gRPC
- GraphQL
- REST / OpenAPI
- React / Next.js
- Flutter
Runtime & delivery
- Kubernetes
- Temporal
- Terraform
- GitHub Actions
- OpenTelemetry
What we build
Engineering capabilities.
High-performance backends
Low-latency APIs and services in Go, Rust, Java or TypeScript, with load-tested capacity and graceful degradation.
Data platforms & streaming
Kafka-based streaming, batch and real-time pipelines, warehouses and lakehouses, analytics and reporting.
Legacy modernisation
Strangler-fig migration off monoliths and legacy stacks, database decomposition and incremental rewrites with zero downtime.
Web, mobile & API products
Production-grade front ends, mobile apps and public APIs with SDKs and documentation.
Quality engineering
Automated test pyramids, contract testing, performance and chaos testing, and CI/CD that makes every merge deployable.
Engineering principles
Rules we don't break.
- 01
Thin slice first
Prove the riskiest path end-to-end before building wide.
- 02
Every merge is deployable
Trunk-based development, feature flags, green pipelines.
- 03
Decisions are written down
ADRs for anything a future engineer will ask 'why?' about.
- 04
Observability is a feature
Traces, metrics and logs ship with the code.
- 05
Load-test before launch
Capacity is measured, not assumed.
- 06
Boring technology wins
Novelty only where it buys something real.
Architecture
Designed around the domain, not the framework.
We start with the business events and invariants, choose boundaries that match team ownership, and pick technology last.
- Domain workshops with your experts
- Service boundaries that match ownership
- Migration paths for the data model
Performance
Fast on purpose.
Throughput and latency targets are agreed up front and verified under load, with graceful degradation designed for the day traffic exceeds them.
- p99 latency budgets
- Backpressure and circuit breakers
- Capacity models per component
How we deliver
Understand, architect, build, harden, evolve.
- 01
Understand
Domain workshops, current-system review and non-functional requirements — throughput, latency, compliance, cost.
Week 1–2 - 02
Architect
Target design, technology choices and a thin vertical slice to prove the risky parts early.
Week 2–4 - 03
Build
Two-week increments with demos, trunk-based development, code review and a definition of done that includes tests and docs.
Sprints - 04
Harden
Load, failure-injection and security testing; observability and runbooks; performance tuning against real traffic patterns.
Pre-launch - 05
Evolve
Handover or ongoing engineering with a roadmap, so the system keeps improving after launch.
Ongoing
Quality bar
Targets we build to.
- Automated test coverage of critical paths≥90%
- Deployment frequency (per week)Daily+
- Lead time for changes< 1 day
- Change failure rate< 10%
BeforeAfter
Typical targets for a production platform — agreed per engagement.
What we've built
Platforms we've shipped.
Payments & ledgers
Double-entry ledgers, settlement engines and reconciliation with strict consistency.
Real-time telemetry
Streaming ingestion and routing for fleets and devices at tens of thousands of events per second.
Marketplaces
Multi-sided platforms with search, pricing, fulfilment and payouts.
Healthcare records
Regulated data platforms with audit trails and fine-grained access.
Analytics warehouses
Lakehouse pipelines with dbt models and self-serve dashboards.
Public APIs
Versioned APIs with SDKs, rate limiting and developer portals.
What clients say
In their words.
“They rebuilt the core without a single customer noticing. That was the whole point.”
“First team we've worked with who wrote down why, not just what.”
“The load test found the problem the previous vendor shipped.”
FAQ
Engineering questions.
Can you take over an existing codebase?
Yes. We start with a technical audit — architecture, tests, deployment, security — and agree what to stabilise first before adding features.
How do you handle scope changes?
Fixed-price per milestone with a visible backlog. Changes are estimated and traded against existing scope, so cost and timeline stay explicit.
Which stack do you recommend?
The one your team can own long-term. We're opinionated about architecture and pragmatic about languages.
Do you work with our in-house engineers?
Usually. Mixed teams with shared code review and pairing are the norm, and knowledge transfer is part of every milestone.
Let's build
Have a hard problem?
Send us the constraints — throughput, latency, compliance, deadline. We'll come back with an approach and a scoped first slice.
Related services
