As the volume of AI-generated code grows, developers lose deep, line-by-line understanding.

Kodou helps developers regain expertise in large-scale codebases.

It safely transforms sprawling repositories, guides developers through structured segments, and strengthens documentation and tests.

Scale Performance and Testing with our multi-language compiler and distributed runtime . The compiler controls the context of its integrated LLM, limiting it to the code of interest.

AI coding tools rely on compilers as guardrails.
For Kodou, compilers leverage AI and are the backbone.

For example, Kodou generates a repository copy containing only the files relevant to the logic or functions of interest.
The AI context is in the pull request.

Software Decoupling: Scaling & AI Context

Leveraging the build process, Kodou’s compiler automatically decouples components and generates asynchronous code.

Instant Async

Decoupling is simplified with the Async Button concept. Kodou’s platform processes repositories to decouple both code and dependencies -- automatically enabling asynchronous behavior.
Performance scaling comes from service deployment.

parallel tests speedup

Software testing is an ever-increasing burden.
Decoupling enables parallel execution and shortens test time by leveraging provisioned infrastructure.

Code Context focus

Focused and curated selections of code create a bounded and semantically relevant context for LLM inferencing.
Decoupling enables this selection and isolation, ensuring the code can run standalone.

Decoupled Code: async code is packaged for deployment. The API mimics the function signature.