Heavy data processing
Large file imports, batch computation, stream transformation: work where an interpreted version would take minutes.
BACKEND
Rust
C-level speed without the memory bugs.
Rust is a compiled language built for workloads where speed and reliability genuinely matter. Its distinguishing trait: the compiler proves, before the program even exists, that no memory access is invalid. A whole family of bugs — random crashes, data leaks, corruption — becomes impossible by construction, without a garbage collector slowing execution down.
What it makes possible
- Processing large volumes without memory use drifting upward over time
- Steady response times, free of garbage-collection pauses
- A smaller hosting bill: the same load fits on smaller machines
- Structurally ruling out memory flaws, still one of the main sources of vulnerabilities
Where we reach for it
High-traffic services
A component called thousands of times a minute, where every millisecond and megabyte shows up on the infrastructure bill.
Real-time processing
Telemetry, geolocation, continuous event streams: cases where a slowdown is immediately visible to the user.
When we do not propose it
Rust takes longer to write and the expertise is scarcer, so hiring and maintenance cost more. For a brochure site, a form or a routine back office it is a bad trade — we use TypeScript there instead. We only bring Rust out when a performance or reliability need justifies it with numbers.
Where we stand
We use Rust surgically, on the components where it genuinely changes the outcome, alongside a TypeScript core. Mixing the two in the right places beats writing everything in one language on principle.
How we validate technical adoption
A technology is not selected for popularity. We build a small proof around the primary risk, then verify that the team can operate it. The decision accounts for the existing product, available skills, security, hosting, migration and maintenance cost over several years. We also examine the maturity of the ecosystem, upgrade paths, observability, licensing and the availability of reliable documentation. Before committing, the prototype is tested against a representative workflow and a realistic data volume. The resulting recommendation records both the reasons to adopt the component and the conditions under which it should be reconsidered. It also names the operational owner and the evidence needed for the first post-launch review.
Compatibility
The component must fit existing data, tools, languages and deployment constraints.
Maintainability
Another person must be able to understand, test and evolve the solution without relying on one author.
Measurement
Performance, errors, delivery time and operating cost are compared with a known baseline.
Exit
The strategy explains how to migrate data, replace the dependency or roll back when the context changes.
A process that is too slow or too expensive?
Describe the bottleneck. We will tell you honestly whether Rust is the answer, or whether the problem lies elsewhere.
Have a bottleneck analysedOther pieces of the stack