Languages
C++
A high-performance systems language with rich abstractions — used by engineers who run the native systems they ship.
Overview
C++ is a high-performance, multi-paradigm systems language that began as an extension of C — adding object orientation, templates and a standard library — and grew, over four decades, into one of the most powerful and most complicated languages in wide use. Its defining promise is the zero-overhead abstraction: you get C-level performance, direct control over memory and hardware, and none of the runtime or garbage collector that sits between other languages and the machine, yet you can still write in classes, generic algorithms and higher-level constructs. When people say a system is written in C++, they usually mean it needs to be fast in a way that leaves no room for a runtime to get in the way.
The important thing to understand in 2026 is that modern C++ — the C++11, 14, 17, 20 and 23 standards — is a genuinely different language from the “C with classes” many people still picture. Smart pointers (unique_ptr and shared_ptr) express ownership so raw new and delete largely disappear; RAII ties every resource to a scope so files, locks and memory are released deterministically the moment they go out of use; move semantics remove pointless copies; and lambdas, ranges and concepts make generic code both safer and far more readable. Written to a modern standard by people who know it, C++ is enormously more expressive and less error-prone than the language its reputation was built on — though, as we say plainly below, it never becomes memory-safe by construction the way Rust is.
We reach for C++ in two situations. The first is performance-critical native work — components, engines and libraries where every microsecond and every allocation matters, and where the abstractions of a managed language are a cost you cannot pay. The second, and just as common, is modernising legacy C++: large, valuable codebases written to an older standard that need dragging into modern C++, made testable, and made safe enough to keep changing. Both demand senior judgement, because C++ punishes the careless more severely than almost any other mainstream language.
Best for — Performance-critical native systems and components, and the modernisation of existing C++ codebases — where C-level control, rich abstractions and interop with established C++ libraries are the whole point.
Why teams choose C++
C-level performance with real abstractions
The zero-overhead principle means the high-level constructs you write — classes, templates, STL algorithms — compile down to code as tight as if you had written the loops by hand. You get expressiveness and control at the same time, which is exactly why C++ still owns the domains where speed is non-negotiable.
Deterministic resource management
RAII ties every resource — memory, files, sockets, locks — to a scope, so it is released at a precise, predictable moment rather than whenever a garbage collector decides. For real-time and latency-sensitive systems, that determinism is not a nicety; it is the reason the language is chosen at all.
A path out of a legacy codebase
A large old C++ codebase is usually far too valuable to rewrite. Modern C++ lets us modernise it in place — introducing smart pointers, RAII and tests, retiring the worst footguns — so it becomes safe to change and cheaper to maintain without throwing away decades of embedded knowledge.
Why businesses choose C++
- You have an existing C++ system — an engine, a trading platform, a simulation, a device — that needs serious engineering, and you want people who work fluently in modern C++ rather than perpetuating old habits.
- You need genuine, measured performance with rich abstractions, and you have profiled enough to know the language is the bottleneck rather than assuming it.
- You depend on large C++ libraries or vendor SDKs, and interop across a language boundary would cost more than it buys.
- You want senior engineers who will be honest when C++ is the wrong tool — and steer you to Rust, or a managed language, when that genuinely serves you better.
What we build with C++
The capabilities this technology is genuinely strong at — and what we most often build with it.
RAII and deterministic lifetimes
Resource Acquisition Is Initialisation is the idea the whole language is built around: a resource is owned by an object, acquired in its constructor and released in its destructor, so it is cleaned up deterministically when scope ends — even through exceptions. We use RAII as the default for memory, files, locks and handles, which is what makes modern C++ far safer than the raw new/delete style.
Smart pointers and ownership
unique_ptr expresses sole ownership with zero overhead over a raw pointer; shared_ptr handles genuinely shared lifetimes with reference counting. Used properly they make ownership explicit in the type system and remove most manual delete calls — and most leaks and double-frees with them. We reach for raw pointers only as non-owning observers, never as owners.
Templates and generic programming
Templates let us write algorithms and containers once and have the compiler specialise them for each type, with no runtime dispatch cost — the mechanism behind the entire STL. C++20 concepts finally put readable constraints on templates, so generic code gives clear compiler errors instead of the notorious walls of template diagnostics.
The Standard Template Library
The STL gives well-tested containers (vector, map, unordered_map and the rest), iterators and a large body of algorithms that are hard to beat by hand. We build on it rather than reinventing data structures, and we know the performance characteristics — cache behaviour, allocation patterns, iterator invalidation — that decide whether the obvious choice is the right one.
Move semantics and value types
Move semantics let ownership of a resource transfer without copying it, which removes a whole class of needless allocations and copies that used to plague C++. Combined with value-type design, it lets us write code that is both efficient and clear about who owns what, without falling back on pointers everywhere.
Modern standards: ranges, lambdas, concepts
C++11 through 23 reshaped the language: lambdas for inline behaviour, ranges for composable, pipeline-style operations over sequences, structured bindings, and concepts for constrained generics. Writing to a current standard is the single biggest lever on how safe and readable a C++ codebase is, and we default to it on new and modernised code alike.
Use cases
Game engines and real-time 3D
The engines behind games and interactive 3D — rendering, physics, animation — live in C++ because they must hit a frame budget with no room for a garbage collector to stall. Much of this world, through engines like Unreal, is C++ at its core.
Low-latency and high-frequency systems
Trading systems, market-data handlers and other latency-sensitive infrastructure where deterministic resource management and shaving microseconds are the entire competitive edge, and a managed runtime is simply not an option.
Performance-critical libraries and components
The fast native core beneath a higher-level application — a codec, a numerical routine, an image or signal pipeline — often written in C++ and called from Python or another language where the rest of the system lives.
Embedded and systems software
Firmware, device software and systems components running close to the hardware, where C++ gives direct control over memory and timing while still allowing abstraction above the bare-metal C style.
When C++ is the right choice
- Right when you are already inside a C++ ecosystem — a game engine, a trading system, CAD or simulation software, a browser or database internals — where the surrounding code, the libraries and the team are all C++ and there is no realistic argument for anything else.
- Right when you need maximum performance with rich abstractions: C-level speed and control, but with templates, the STL and classes so the code stays expressive rather than collapsing into raw pointers and hand-rolled loops.
- Right when you must interoperate with large, established C++ libraries — physics engines, numerical and graphics libraries, vendor SDKs — where binding across a language boundary would cost more than it saves.
- Wrong for ordinary application and web back-end work. A web service, an internal tool or a typical business system does not need manual memory management or zero-overhead abstraction; C#, Go or Python will be written, shipped and maintained in a fraction of the time, with whole categories of bug simply absent.
- Wrong, increasingly, for greenfield performance-critical work where memory safety is paramount. If you are starting fresh and the system must be both fast and memory-safe — and there is no existing C++ estate pulling you in — Rust is the rational choice, and we will tell you so rather than sell you a C++ project you will spend years hardening.
C++: pros and cons
Strengths
- Unmatched combination of raw performance and high-level abstraction — C-level speed with templates, the STL and object orientation on top.
- Deterministic, RAII-based resource management gives precise control over memory and lifetimes, which managed languages cannot offer.
- A vast, mature ecosystem of battle-tested libraries in graphics, games, numerics, finance and systems, plus direct interop with C.
- Runs everywhere and close to the metal — from embedded microcontrollers to the largest servers — with no runtime or garbage collector in the way.
Trade-offs
- One of the most complex languages in wide use: an enormous feature surface and decades of accumulated, overlapping ways to do the same thing make it genuinely hard to master.
- It retains manual-memory footguns and undefined behaviour — use-after-free, buffer overruns, data races — so memory-safety bugs and the security vulnerabilities they cause remain a real risk. Smart pointers and discipline mitigate this; they do not eliminate it.
- Long compile times on any substantial codebase, especially template-heavy code, which slows the edit-build-test loop and the productivity of the whole team.
- A steep learning curve, and for new memory-safety-critical work Rust now delivers comparable performance with far stronger safety guarantees — a real and growing reason to look elsewhere.
Architecture
We architect C++ systems around ownership first, because in this language ownership is the thing that decides whether a codebase is safe to change. Every resource has one clear owner, expressed through unique_ptr, value types and RAII, with raw pointers and references used only as non-owning observers whose lifetime is guaranteed by the owner outliving them. Getting ownership right up front is what turns C++ from a minefield into an ordinary engineering problem; getting it wrong is the root of most of the crashes and vulnerabilities the language is infamous for.
On top of that we keep interfaces narrow and modular, separating the pure computational core — where performance lives and where we can test in isolation — from the platform and I/O edges. Templates give us compile-time polymorphism with no runtime cost where the types are known, and we reserve virtual dispatch for genuine runtime variation rather than reaching for inheritance by reflex. On a legacy codebase the architecture work is different but just as deliberate: we carve seams into a tangled system so it can be tested and modernised incrementally, rather than attempting a rewrite that would take years and lose hard-won behaviour along the way.
Performance
Performance is usually the reason C++ is on the table at all, and the zero-overhead principle is what delivers it: the abstractions cost nothing at runtime that you would not have paid writing the equivalent by hand. But raw language speed is the easy part. The real performance work in a modern C++ system is about memory — data layout for cache locality, minimising allocations on hot paths, using move semantics and reserved capacity to avoid needless copying, and choosing data structures for how they behave in cache rather than how they read in a textbook.
We measure before we optimise, always. We profile under realistic load, find where the time and the allocations actually go, and change those places rather than scattering micro-optimisations on faith. The compiler is a full partner here — modern optimising compilers do extraordinary work when you write clear, idiomatic code and let them, and hand-cleverness often defeats them. Where it is justified we go further, into SIMD, custom allocators and lock-free structures, but only with numbers to show the effort is buying something real.
Security
We will not pretend otherwise: memory safety is the hardest and most consequential part of writing C++ securely. The language permits undefined behaviour — buffer overruns, use-after-free, uninitialised reads, data races — and these are not merely bugs but the direct source of a large share of the serious security vulnerabilities found in native software. Smart pointers, RAII, bounds-checked access and disciplined ownership dramatically reduce the exposure, but they do not make C++ memory-safe by construction the way Rust is, and we would be lying to say they did.
So we lean hard on tooling and process. AddressSanitizer, UndefinedBehaviorSanitizer and ThreadSanitizer run in our build and test pipelines to catch memory and threading faults early; static analysers and compiler warnings turned up to errors catch more before code runs; and fuzzing exercises parsers and other input-handling code against the malformed data attackers actually send. On top of that sit the ordinary disciplines — validate every input at the trust boundary, keep dependencies scanned and patched, never trust the network — but in C++ the memory-safety tooling is not optional, and if a system is truly security-critical and greenfield, our honest advice may be to write it in Rust instead.
Scalability
Scalability in C++ is usually a vertical, single-machine story before it is a horizontal one: the language is chosen precisely because it extracts the most from the hardware it runs on, so a well-written C++ system often serves a load on one node that would need a fleet of instances in a managed language. Concurrency is where the real design effort goes — the C++ memory model, std::thread, atomics and higher-level parallelism let us use every core, but shared mutable state and data races are exactly the territory where C++ is least forgiving, so we prefer clear ownership, message passing and immutable data over sprinkling locks across shared structures.
Where a native component sits inside a larger, distributed system, we treat it as one well-behaved piece of that estate: a fast core exposed through a clean interface — often behind an API, or embedded in a service and deployed as an ordinary Linux container — that scales alongside everything else. The C++ part earns its keep by doing the heavy computation efficiently; the surrounding architecture handles the distribution, and we keep the boundary between the two deliberate and narrow.
C++ integrations & ecosystem
The technologies we most often pair with it — each links to how we work with it.
How we work
We work to a modern C++ standard from the first line, with a strict toolchain doing a great deal of the guarding: warnings treated as errors, static analysis, and the sanitisers (AddressSanitizer, UBSan, ThreadSanitizer) wired into continuous integration so memory and threading faults surface in the build rather than in production. We settle ownership and lifetimes at design time, because retrofitting sound ownership onto code that ignored it is the most expensive kind of C++ work there is. New code is built and tested in small, real slices; legacy code is modernised behind tests, seam by seam, never as a big-bang rewrite.
The engineers who design the system are the ones who write it and keep it running — that is what we mean by operating what we build. In C++ that principle bites harder than in most languages, because the person choosing an ownership model or a threading approach is the person who will debug the crash at 3am if the choice was wrong, so we favour the clearest design that meets the performance goal and resist cleverness for its own sake. You get profiled, sanitiser-clean, modern C++ that your own team can read and extend — not a virtuoso artefact only its author understands.
The service behind it
Delivered throughCustom Software DevelopmentWhat we build with C++
The disciplines this technology most often shows up in — from a first build to taking over and stabilising an existing one.
How we deliver
- 01
Discover
We map the system, the constraints and the business it serves — including the parts nobody documented.
Architecture brief
- 02
Architect
Decisions get made, written down and defended before a line of production code exists.
Decision records
- 03
Build
Short cycles against working software. You see progress in the product, not in a status deck.
Shipping increments
- 04
Operate
Monitoring, incident response and iteration. The system is alive, so the engagement is too.
Runbooks & SLOs
Industries we use C++ in
Domain knowledge changes what gets built. A few of the sectors we know before the first meeting.
Also in Languages
Why teams choose us for C++
Senior engineers only
C++ is unforgiving of inexperience — ownership, lifetimes, undefined behaviour and template subtleties are where projects live or die. The people on your system have made those calls before and lived with the results. No juniors learning memory safety on your production code.
Modern C++, not old habits
We write to a current standard — smart pointers, RAII, move semantics, ranges and concepts — and we modernise legacy code toward it. We are not perpetuating the raw new/delete, pointer-everywhere style that gave C++ its reputation, and we bring the sanitiser-and-static-analysis discipline that makes the language safe to work in.
We operate what we build
We run the native systems we ship, so we design for the debugging and maintenance reality: clear ownership, sanitiser-clean builds, and code the next engineer can actually reason about. In C++ especially, we optimise for the person debugging it later, not the demo.
Honest about Rust and the alternatives
If your work is greenfield, performance-critical and memory-safety-critical, we will tell you Rust is likely the better choice before you commit to years of hardening C++. And if it is really ordinary application work, we will point you at a managed language rather than sell you a systems project you do not need.
Typical timeline
- 01
Discovery and design
One to two weeks understanding the requirements, the existing code and the performance targets, and settling the ownership model, the module boundaries and the toolchain before code volume grows. On a legacy codebase this is also where we map the risk and find the seams.
- 02
First working slice
Two to four weeks delivering one real capability end to end — building, sanitiser-clean, and measured against the performance goal — so the design is proven against reality rather than a diagram.
- 03
Iterative build or modernisation
Feature-by-feature delivery, or seam-by-seam modernisation of legacy code, in short cycles — each increment tested, profiled where it matters, and kept sanitiser-clean rather than leaving safety and performance as a final scramble.
- 04
Hardening and handover
Profiling under realistic load, a memory-safety and security review with the sanitisers and fuzzing, and documentation so your team can build, run and extend the system on a modern toolchain without us in the room.
How pricing works
- Fixed-scope builds for well-defined native components — a library, an engine module, a performance-critical service — quoted once the requirements, the interfaces and the performance targets are understood.
- Monthly senior engagement for ongoing systems work, where the scope evolves and you want continuity of the people who hold the codebase in their heads rather than a fixed deliverable.
- Legacy modernisation, priced after an assessment: bringing an older codebase up to a modern C++ standard, introducing tests and sanitisers, and retiring the worst safety footguns.
- Audits and performance rescues of existing C++ systems — a memory-safety review, a latency or throughput problem, a crash nobody can pin down — priced by the assessment.
Hire C++ engineers
Need C++ capacity on your own team? We embed named senior engineers into your existing team — reporting to your leads, working in your rituals — so you add capacity without a hiring cycle.
Hire C++ engineersCommon questions
Is modern C++ still as dangerous as its reputation suggests?
Much less so, but not safe by construction. Written to a modern standard — smart pointers for ownership, RAII for resources, bounds-checked access, sanitisers in the build — C++ avoids the great majority of the memory bugs that gave it its reputation, and is a genuinely different experience from the old new/delete style. But the language still permits undefined behaviour and manual-memory mistakes, so the risk is reduced by discipline and tooling, not eliminated. That honest gap is precisely why, for new safety-critical work, we take Rust seriously.
Should we choose C++ or Rust for a new performance-critical system?
If there is no existing C++ estate pulling you in and memory safety matters, Rust is increasingly the rational choice: it delivers comparable performance with memory safety enforced by the compiler rather than by discipline. C++ remains the right answer when you are already inside a C++ ecosystem — a game engine, a trading platform, CAD or simulation — or when you must interoperate with large C++ libraries where a language boundary would cost more than it saves. We will give you the honest recommendation for your specific situation rather than a default.
Can you modernise our existing legacy C++ codebase?
Yes — this is a large part of what we do. An old but valuable C++ codebase is usually far too costly and risky to rewrite, so we modernise it in place: introducing smart pointers and RAII, carving seams so it can be tested, wiring in sanitisers and static analysis to expose latent memory faults, and moving it toward a current standard. We work incrementally behind tests rather than attempting a big-bang rewrite, so the system keeps working and its hard-won behaviour is preserved while it becomes safe to change again.
Why are C++ compile times so long, and does it matter?
It matters, and it is a real cost. C++ compilation is slow on any substantial codebase — the header model recompiles a lot of code repeatedly, and template-heavy code multiplies the work — which lengthens the edit-build-test loop that governs how fast a team moves. We manage it deliberately: keeping headers lean, limiting template bloat, using forward declarations and, on modern standards, C++20 modules and precompiled headers where they help. It rarely disappears entirely, but it can be kept from grinding a project to a halt.
When should we not use C++ at all?
For most application and web back-end work. If you are building a web service, an internal tool or a typical business system, C++ gives you manual memory management and zero-overhead abstraction you do not need, at the price of far slower development and a whole class of bugs other languages simply do not have. C#, Go or Python will get you there faster and safer. C++ earns its place only where performance and control are genuinely the point, or where an existing C++ ecosystem gives you no real alternative — and we will tell you plainly which situation you are in.
Building on C++?
A technical conversation with the engineers who would do the work. If we are not the right fit, we will say so on the call.