Where C++ fits

We use C++ when the problem is latency, determinism, or long-lived native code — telecom stacks, performance services, integration with vendor SDKs, and systems that must survive years of production abuse.

• Real-time and near–real-time services — audio/video, signalling, device or exchange-adjacent logic.
• Thin abstraction — you need control over memory, threading, and build flags, not a thick runtime.
• Cross-platform native bases that later gain UIs (including Qt/QML when the product needs a serious desktop surface).

New systems vs extending an existing codebase

Greenfield C++ costs more at the start: build system, coding standards, threading model, logging, crash reporting, and first production release. Maintenance and extension is usually a stable monthly rhythm: triage, patch releases, refactors behind feature flags, and dependency upgrades — as long as technical debt is kept visible.

Junior vs senior on native code

C++ mistakes are expensive. We staff senior engineers for architecture, concurrency, and build/release, and use mid-level engineers for bounded features with mandatory review. Juniors contribute best on tests, tooling, and smaller modules once patterns are established — not on unguarded core paths.

Representative delivery (on-page summary)

For Qt/QML-heavy desktop surfaces, the same governance model applies with more UI-specialised staffing.

Cost expectations

Software work is milestone-scoped. Workforce costs for employed engineers follow Staff Salary + Management Fee (5%, 10%, or 15% of gross payroll by tier). Native programmes often land in mid five-figures USD and up when you include hardening, packaging, and multi-release roadmaps — we split work into phases so spend tracks risk.