Rust development company
For workloads where latency, memory use, or memory safety decide the outcome, our Rust development services cover async backends on Tokio and Axum, safe FFI bindings to existing C, C++, or Python code, and unsafe blocks kept rare and reviewed.
- Senior engineers · IST + EST overlap
- NDA on day 1
- 24-hour reply
- Projects shipped
- 50+
- Code ownership
- 100%
- Client rating
- 4.8/5
- First reply
- 24h
Where Rust earns its place in your stack
As a Rust development company, Krapton writes backend services, command-line tools, WebAssembly modules, and native libraries in Rust for workloads where a garbage-collected runtime has become the bottleneck or a memory-safety bug would be expensive. Common triggers include tail latency that collector pauses keep pushing up, a C or C++ component with a history of crashes, a Python pipeline that needs a faster core, and CPU-heavy logic that must also run in the browser. Rust is a poor trade for CRUD screens on a deadline, where Go or TypeScript ship faster and the hiring pool is larger. Our async services are structured around Tokio, errors are modeled with thiserror in libraries and anyhow at application edges, and tracing is wired in from the first endpoint. Clippy, cargo-deny, and cargo-audit run on every pull request, and any unsafe block needs a written safety comment plus a second reviewer.
Rust development services
Async backend services
HTTP and gRPC services on Tokio with Axum or tonic, sqlx for compile-time checked queries, structured tracing, and graceful shutdown, shipped as small static binaries in distroless images.
Legacy native code rewrites
Crash-prone native components rewritten module by module behind a C ABI or the cxx bridge, so the surrounding application keeps running while legacy unsafe code shrinks.
Python and Node.js extensions
Hot loops moved out of Python with PyO3 and maturin, or out of Node.js with napi-rs, keeping the existing API so callers notice only the speed difference.
WebAssembly modules
Rust compiled to Wasm with wasm-bindgen for in-browser image, document, or crypto work, or targeted at WASI for plugin systems that run untrusted code inside a Wasmtime sandbox.
CLIs and developer tooling
Cross-platform command-line tools built with clap and cross-compiled into single binaries for Linux, macOS, and Windows, with releases automated in GitHub Actions.
Data pipelines and parsers
Streaming ingestion, log processing, and file parsers built on Tokio, Rayon, and Apache Arrow or Polars, where predictable memory use matters more than quick scripting.
Why teams choose Krapton for Rust
Senior engineers, fixed scope, and code you own — the things agencies promise and rarely deliver.
Unsafe code treated as debt
Every unsafe block carries a SAFETY comment stating its invariants, gets a second reviewer, and runs under Miri in CI where the code allows, so soundness is checked rather than assumed.
Async pitfalls caught early
Reviews look for blocking calls inside async tasks, mutex guards held across await points, and unbounded channels, habits that cause stalls and memory growth under load.
Compile times kept workable
Workspaces are split into focused crates, CI caches builds with sccache or rust-cache, and Docker images use cargo-chef layers, so slow compiles do not quietly drain team velocity.
Interop before rewrites
Rust joins what you already run through FFI, gRPC, or message queues, instead of demanding a full rewrite before it has proven its value in production.
How a Rust project runs with Krapton
01
Profile before rewriting
Flame graphs and load tests on the current system confirm that Rust will fix the real bottleneck, and the report says so plainly when it will not.
02
Boundary and crate design
The interface between Rust and the rest of your stack is defined first, crates are chosen deliberately, and decisions on errors, async runtime, and serialization are recorded.
03
Benchmarked iterations
Each milestone ships with criterion benchmarks and proptest suites, so performance and correctness claims are checked on every pull request rather than at the end.
04
Shadowed production rollout
New Rust components run in shadow mode or behind feature flags first, with traces and metrics compared against the system they replace before traffic moves.
The Rust stack we build with
Rust development: questions answered
When should we hire a Rust development company instead of using Go or Java?
When performance or memory safety is a hard requirement rather than a preference. Rust suits services with strict latency targets, CPU-heavy processing, replacements for C or C++ code, Wasm modules, and libraries that other languages call. Go or Java stay better choices for ordinary business APIs where hiring speed and quick iteration outweigh raw efficiency, and a good partner tells you that before proposing a rewrite.
Is Rust ready for production web backends?
Yes, for most API and service workloads. Tokio, Axum, tonic, sqlx, and the tracing ecosystem are mature and widely deployed, and the AWS SDK for Rust is generally available. The tradeoffs are slower compile times, a steeper learning curve, and fewer ready-made admin or CMS components than Rails or Django offer. For APIs where efficiency and correctness matter, those costs are usually acceptable; for simple back-office CRUD, they often are not.
What is the safest way to move part of a C++ or Python system to Rust?
One boundary at a time. We pick a self-contained component with clear inputs and outputs, reimplement it in Rust behind the same interface, using the cxx bridge for C++ or PyO3 for Python, and run both versions against recorded production inputs until results match. Only then does traffic switch. This strangler approach avoids a big-bang rewrite and produces measured performance data at each step.
How is Rust code tested and secured?
With layers aimed at the risks Rust leaves open. Unit and integration tests run under cargo-nextest, proptest generates edge cases, cargo-fuzz targets parsers and decoders, and Miri checks unsafe code for undefined behavior. For supply chain risk, cargo-audit checks dependencies against the RustSec advisory database and cargo-deny enforces license and source policies. Clippy runs with warnings treated as errors.
Why do Rust project estimates vary so much?
Because the hard part is usually the boundary with your existing systems, not the Rust itself. Effort grows with the amount of C, C++, or Python code that must interoperate, the number of target platforms and CPU architectures, how strict the latency or memory targets are, audit expectations around unsafe code, and the benchmarking evidence you need before rollout. Krapton reviews those factors technically before any estimate is written.
Ready to build? Tell us what you have in mind.
Send a short brief and a senior engineer will reply within one business day with next steps — no sales fluff.