Catalogue — Services

Six practices. One firm. Every engagement is staffed across more than one.

We describe our work in practice areas because it helps with conversation. We rarely deliver it that way. The platforms that hold up across a decade are built by teams that cross practices deliberately and constantly.

1. Practice 01

   Platform engineering

   Landing zones, internal platforms, and the day-two operations that follow.

   We design and operate the platforms your engineers build on. Multi-account, multi-region landing zones; internal developer platforms with golden paths; observability stacks that actually alert humans; and FinOps governance that surfaces unit cost rather than vanity totals.

   Typical deliverables

   • Reference landing zone in Terraform / OpenTofu
   • Internal developer platform on Kubernetes or Nomad
   • Observability stack on OpenTelemetry, Grafana and Sentry
   • FinOps reporting tied to product unit economics

   

2. Practice 02

   Product engineering

   Web and mobile product work, run as a single discipline with design.

   Senior product teams shipping React, TypeScript and native mobile work for products where accessibility, performance and editorial polish are non-negotiable. We integrate with your existing design system or rebuild one from first principles, depending on what the product actually needs.

   Typical deliverables

   • Design system in tokens, with documented usage
   • React or React Native applications shipped to production
   • End-to-end test coverage with Playwright or Maestro
   • Performance budgets enforced at build time

   

3. Practice 03

   Data engineering

   Warehouses, pipelines and the analytics layer your finance team will trust.

   We build event-driven and batch pipelines on Kafka, Airflow and dbt, materialised into ClickHouse, BigQuery or Snowflake. Every transformation is contract-tested. Every dashboard is reproducible from a versioned model. Every metric has an owner.

   Typical deliverables

   • Warehouse architecture and capacity plan
   • Pipelines on dbt with full lineage and contract tests
   • Reverse-ETL into operational systems
   • Self-serve analytics on Lightdash, Metabase or Looker

   

4. Practice 04

   Applied machine learning

   Evaluation, retrieval, fine-tuning and the routing layer between them.

   We treat machine learning as a platform discipline. Retrieval indices on Qdrant, Pinecone or pgvector. Evaluation harnesses that report on cost, latency and quality together. Model-routing services that pick the smallest model that will do the job. No theatre.

   Typical deliverables

   • Evaluation harness with golden datasets
   • Retrieval pipeline with re-ranking and grounded citations
   • Model-routing service across providers
   • Continuous monitoring of drift and regression

   

5. Practice 05

   Security engineering

   Identity, secrets, supply chain and the audit work as code.

   ISO 27001, SOC 2 Type II and PCI-DSS programmes treated as engineering work. Hardware-bound credentials, zero-trust access patterns, signed builds and continuous control monitoring. Evidence for auditors is collected automatically as the platform runs.

   Typical deliverables

   • Threat model and control catalogue
   • SSO and zero-trust access architecture
   • Signed-build supply chain with SBOM
   • Continuous compliance reporting to auditors

   

6. Practice 06

   Reliability engineering

   SLOs, capacity planning, incident response and the post-mortems that follow.

   We operate the platforms we build, twenty-four hours a day, with on-call rotations staffed by engineers who wrote the code. Service-level objectives are defined with the business, not derived from infrastructure. Post-mortems are written, blameless and acted upon.

   Typical deliverables

   • Service-level objective design and error-budget policy
   • On-call rotation and pager-fatigue review
   • Capacity plan and chaos-engineering programme
   • Quarterly architecture review with the executive team