Rust scope and boundary
We define exactly what Rust should own: the hot path, a performance-critical service, a CLI, a WASM module or the piece of a Python system that needs to be fast and safe.
Service · Rust Development
Rust development for fast backends, systems software and low-latency cores.
99 Francs® builds focused Rust for teams that have hit a performance, safety or latency wall: high-throughput backends, systems components, CLIs, WebAssembly modules and Rust cores that replace the hot path of an existing Python or Node service.
150+
shipped projects
$32M+
raised by clients
9,000+
tasks delivered
Direct answer
99 Francs provides Rust development services for the parts of a product that have to be fast, safe and predictable.
The service covers Rust scoping, Axum and Actix backends, systems and CLI work, low-latency execution cores, WebAssembly modules and Python-to-Rust migration of hot paths, with benchmarks, tests and a clean integration boundary.
What you get
Development that keeps the website fast, editable and faithful to the design.
The build should not flatten the design or create a maintenance problem. We keep implementation decisions tied to performance, content ownership, responsive behavior and the launch goal.
Backends and services
We build lean Rust services with Axum or Actix for APIs, workers and data processing where throughput, memory safety and predictable latency matter more than raw iteration speed.
Low-latency and systems work
We implement execution cores, hot loops, CLIs and systems components where microseconds, tight memory use and no garbage-collection pauses are the point.
WebAssembly and migration
We compile Rust to WebAssembly for in-browser compute, and migrate proven Python or Node hot paths into Rust so the rest of the stack keeps its existing language.
Best fit
Use this service when the website has to become a real launch surface, not just a mockup.
The bottleneck is performance, not features
Use Rust when a specific service, loop or job is too slow, too memory-hungry or too latency-sensitive for Python, Node or a scripting layer, and speed is now the product.
Correctness and safety are non-negotiable
Rust's ownership model catches whole classes of memory and concurrency bugs at compile time, which fits execution engines, financial logic and systems code that cannot crash in production.
A Python or Node service needs a fast core
We migrate only the hot path to Rust and keep the rest of the system in place, so a Python quant engine or a Node API can call a Rust core without a full rewrite.
The work targets the browser or the edge
Rust compiled to WebAssembly runs heavy compute in the browser or at the edge at near-native speed while JavaScript keeps driving the interface.
Process
From build scope to live website.
The process keeps design, content, CMS, integrations, QA and launch readiness in one line so the final site is easier to ship and maintain.
Find the hot path
We review the system, profile where time and memory actually go, and identify the smallest Rust boundary that removes the bottleneck without rewriting working code.
Design the Rust interface
We define the crate, the API or FFI boundary, data models, error handling and how Rust talks to the surrounding Python, Node or frontend before implementation starts.
Build the Rust core
We implement the service, execution core, CLI or WASM module with typed contracts, tests, and benchmarks so the gain over the previous implementation is measured, not assumed.
Integrate and hand off
We wire Rust into the existing stack, verify latency, memory and correctness under load, and document build, deployment and the boundary for future engineering.
Related work
A low-latency Rust execution core inside a real trading system.
Our Polymarket trading system is the direct Rust proof point: a Python numpy/scipy quant engine with the performance-critical execution core moved into a Rust sidecar, so the hot path runs with predictable latency while Python keeps the modeling and orchestration.
Rust build
If a service, loop or core has become the bottleneck, give it a Rust layer that is fast, safe and measured.
Rust · Axum · Actix · WebAssembly · Low-latency · Python-to-Rust
Start Rust development→Rust development FAQ
Questions teams ask before moving a hot path to Rust.
99 Francs offers focused Rust development for high-performance backends, systems software, CLIs, WebAssembly modules, low-latency execution cores and Python-to-Rust migration of performance-critical hot paths.
Yes. Rust runs at C-level speed with compile-time memory and concurrency safety, no garbage-collection pauses and mature web frameworks like Axum and Actix, which makes it a strong fit for high-throughput, latency-sensitive production backends.
Use Rust when you need C++-level performance without its memory-safety risk, or when Python and Go can't hit the latency, throughput or memory targets a service requires. Keep the higher-level language for everything that isn't on the hot path.
Yes, and usually only the hot path. We keep the Python system in place and move the performance-critical core to Rust so it can be called from the existing code, which is the approach we used on the Polymarket trading system's execution core.
Yes. Rust's predictable latency, tight memory control and safety make it a practical fit for order execution, market-data processing and other low-latency paths where garbage-collection pauses or crashes are unacceptable.
Yes. Rust compiles cleanly to WebAssembly, so heavy computation such as parsing, simulation or crypto can run in the browser or at the edge at near-native speed while JavaScript continues to handle the interface.