Make it work.
We'll make it faster.
Numerical code optimisation, as a service.
We analyse your numerical Python codebase, identify performance bottlenecks, and deliver optimised code, verified end-to-end inside secure containers before anything touches your repository.
Tailored for engineering, scientific computing, and quantitative finance teams.
Optimisation guided by your priorities
Different codebases have different goals. DeltaCode can target specific optimisation objectives depending on your use case, from reducing runtime and memory consumption to improving readability and maintainability.
Built around your workflow
Every optimisation is validated inside secure cloud containers configured for your specific application. Runtime environments, dependencies, entry points and verification workflows are tailored to each client, ensuring results reflect real-world execution rather than synthetic benchmarks.
Controlled LLMs, verified results
DeltaCode uses a deterministic optimisation workflow with tightly controlled LLM involvement. Original code is benchmarked first, candidate replacements are generated only at the final code-swap step, and every result is iterated until outputs match the original implementation.
