Generate full-stack code
from a single semantic graph
Model your software system as a graph. Let AI generate the rest.
The Semantic Graph Compiler generates multiple .txt files—one for each source file you define in the graph. The graph here refers to a mathematical directed graph that models your software system, and can be edited using the Semantic Graph Editor.
Each .txt file contains a set of well-structured, AI-targeted prompts—one for every component in that file—ordered precisely according to the graph’s dependency edges. You can manually copy each prompt into a language model like ChatGPT and paste the generated code back into the corresponding part of your codebase.
This workflow applies across multiple source files and scales seamlessly. The result is a fully runnable full-stack system with minimal effort.
This website may soon support a fully automated workflow for generating production-grade code—eliminating the need for manual copy-paste. Advanced features may require a paid plan in the future.
Why SGC?
Graph-Native
Capture entities and flows as nodes and edges—just like how you think about systems. Here, you can also visualize your software architecture.
Structured Prompt Generation
SGC generates a prompt for each component, enriched with complete background context, so LLMs can efficiently generate accurate code.
Full-Stack Output
From schema to UI—SGC keeps everything in sync without writing glue code.
Ready to build faster—and more structured?
Join early adopters automating all the repetitive and tedious coding tasks, saving hours every day so you can focus on system design