One platform. Every language in your codebase.

Enterprise codebases aren't monolingual.
The Lossless Semantic Tree (LST) changes that. Every supported language builds the same compiler-accurate structural model — enabling the same recipe-driven workflow, the same governed pull request process, and the same enterprise-scale orchestration regardless of what's in the file header.
Deep support across the enterprise stack

Automated Code Changes at Scale
One engine under every language
An LST is a compiler-accurate structural model of source code: it preserves comments, formatting, and whitespace while capturing full type and symbol information. Every supported language generates an LST, and every recipe operates against that model — making transformations deterministic, format-preserving, and safe across your entire codebase.
What enterprise modernization requires — across every language
7,000+
Thousands
Fortune 500
Moderne vs. language-specific tools
Thousands of recipes.Every language.
Every recipe in the catalog operates against the LST — meaning it works with the full semantic model of the code, not just its text representation. This is what makes recipes safe to run at scale without manual review of every change.



Modernize your entire codebase. Every language. One platform.
Frequently asked questions
Moderne and OpenRewrite currently provide production recipe coverage for Java (JVM), Spring Boot, C# / .NET, and Python. Kotlin, Groovy, YAML, and HCL have varying levels of support and are on the active roadmap. The full language catalog is available in the OpenRewrite docs.
Yes. Every supported language builds a Lossless Semantic Tree — a compiler-accurate structural model that preserves formatting, comments, and whitespace while capturing full type and symbol information. Recipes operate against this model, making transformations deterministic and format-preserving regardless of language.
Yes. Moderne orchestrates recipe execution across your entire repository estate in a single coordinated run — regardless of language mix. A security remediation recipe can execute across Java, Python, and C# repositories simultaneously, with a unified view of progress and impact.
Language-specific tools create fragmentation — different workflows, different governance, and no cross-language visibility. Moderne's LST engine provides a consistent execution model, consistent pull request workflow, and consistent progress tracking across every language your organization uses. You maintain one platform instead of four.
Yes. Moderne parses every supported file type in a repository and builds the appropriate LST per language. In a monorepo with Java services and Python ML pipelines, each file is analyzed with full semantic understanding — and recipes apply selectively based on the language of each file.
Every language supported by Moderne is represented in the LST — giving coding agents a semantic model of your codebase that goes far beyond what fits in a context window. Agents can reason over type relationships, dependency graphs, and cross-file patterns across all supported languages. Recipes then provide the governed execution layer that applies agent-proposed changes safely at scale.
