Services

What we build, and how deep we go

Six practices. Most projects use two or three of them on one team. Below is what each practice actually delivers, not a list of technologies we have heard of.

01

Product engineering

SaaS platforms and web products built to carry real load

Most of our work starts here. A company has a product idea, a struggling MVP or a decade old system that cannot take another feature, and needs a team that can hold the whole thing: data model, API, interface, deployment and the operational reality afterwards.

TypeScriptReact and Next.jsNode.js and NestJSPython and FastAPIGoPostgreSQL
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02

Mobile engineering

iOS and Android apps that hold up outside the demo

Mobile is where optimistic architecture goes to die. Networks drop, devices are five years old, app review takes a week and a crash on launch day reaches your whole user base at once. We build for those conditions from the start.

Swift and SwiftUIKotlin and Jetpack ComposeReact NativeFlutterSQLite and RealmFastlane
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03

Agentic and generative AI

AI features that pass review, not just demo well

There is a wide gap between an AI prototype that impresses a board and an AI feature that runs safely against customer data at volume. The gap is evaluation, guardrails, latency and cost. That gap is most of the work, and it is where we spend our time.

Claude and the Anthropic APIOpenAI APIModel Context ProtocolLangGraphpgvector and QdrantPython
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04

Cloud and platform engineering

Infrastructure your team can operate at three in the morning

Cloud spend is usually the second largest engineering line item and the least examined. We build infrastructure that is defined in code, reproducible from an empty account, observable when it misbehaves and priced deliberately rather than by accident.

AWSAzureGoogle CloudTerraformPulumiKubernetes
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05

Data engineering and analytics

Numbers your leadership team actually trusts

Almost every company we meet has dashboards. Far fewer have dashboards their executives believe. The difference is rarely the visualisation tool. It is lineage, definitions, tests and the discipline to have one place where a metric is defined.

dbtAirflow and DagsterSnowflakeBigQueryPostgreSQLKafka and Debezium
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06

Technology consulting

Straight answers before you spend the budget

Sometimes the most valuable thing an engineering partner can do is tell you not to build something. Our consulting work is deliberately short, independent of any build contract, and it ends in a written document you can hand to your board.

Architecture decision recordsC4 modellingThreat modellingCost modellingLoad and capacity testingStatic analysis
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Not sure which of these you need?

That is a normal place to start. Describe the problem in plain language and we will tell you which practices apply, which ones you can skip, and roughly what it costs.

  • A senior engineer reads every brief
  • NDA signed before you share anything sensitive
  • No sales sequence, no automated follow ups