Twelve service lines delivered by engineers.

Typical use cases

• —Internal tools that unify data across multiple existing systems
• —Customer-facing products with domain-specific workflows
• —Operational software replacing spreadsheets or manual routines

Expected deliverables

• —Working application with source code and infrastructure definitions
• —Automated tests, deployment pipeline and environment setup
• —Technical documentation and operator handover

Typical use cases

• —Domain services behind a user-facing product
• —Event-driven pipelines processing operational data
• —Business-logic services replacing ageing back-office code

Expected deliverables

• —Service code with defined interfaces and internal documentation
• —Database schema with migrations and seed data
• —Load and integration tests covering realistic scenarios

Typical use cases

• —Setting up new cloud environments for a growing product
• —Migrating an application from on-premise or another provider
• —Introducing infrastructure-as-code to an ad-hoc setup

Expected deliverables

• —Infrastructure-as-code repository covering environments
• —CI/CD pipelines with automated deployments and rollbacks
• —Runbooks for common operational tasks

Typical use cases

• —Applications on end-of-life frameworks or runtimes
• —Codebases that block feature work because of accumulated complexity
• —Systems that need to be split into services or extracted from a monolith

Expected deliverables

• —Modernisation plan with a sequenced roadmap
• —Migration components running alongside the existing system
• —Cut-over plan with rollback procedures

Typical use cases

• —Product approaching a public launch
• —Team introducing automated testing to a codebase that has none
• —Regulated context that requires a documented test approach

Expected deliverables

• —Test strategy tailored to the codebase and risk profile
• —Automated test suites integrated into the delivery pipeline
• —Reports on coverage, flakiness and detected regressions

Typical use cases

• —Web application slower than users expect on typical devices
• —Backend service with rising cost per request
• —Data pipeline that no longer finishes within its window

Expected deliverables

• —Benchmark suite that captures the current baseline
• —Prioritised list of interventions with expected impact
• —Implemented changes with before-and-after measurements