RapidDoc AI

🏆 DT&A Digithon 2026 – Runner Up

A native code-to-text engine that turns raw codebases into structured technical docs, inside CI/CD, always in sync.

An asynchronous multi-agent pipeline with parallel fan-out routing that ingests large monolithic codebases, reverse-engineers architecture into instant HLDs, and generates Developer & User guides in Markdown, wired directly into CI/CD.

Manual documentation constantly lagged behind code, creating stale docs, slow onboarding and accumulating documentation debt.

• Engineered a native code-to-text translation engine that transforms raw codebases into structured technical documents.
• Architected an automated Code-to-HLD pipeline that reverse-engineers system architecture into instant design blueprints.
• Integrated into CI/CD to auto-generate Developer and User guides in Markdown on every change.
• Built deterministic Python static-analysis skills and programmatic Mermaid sequence-diagram synthesis.
• Designed an asynchronous multi-agent pipeline with parallel fan-out routing for large monolithic codebases.

1. 01

   Fanned work out across asynchronous agents instead of one sequential pass.

   A linear pipeline times out on large monorepos. Parallel fan-out by module trades orchestration complexity for the ability to document a big codebase in a single run: the only way the tool stays usable at real repo sizes.

2. 02

   Grounded generation in deterministic static analysis, not the model alone.

   Imports, call graphs and signatures are extracted with Python AST parsing and diagrams synthesised programmatically. The LLM writes prose over verified structure, so docs describe the real system rather than a plausible-sounding one.

3. 03

   Wired generation into CI/CD rather than a manual 'generate docs' step.

   Documentation drifts the moment it is manual. Running on every change is the only mechanism that holds 100% sync between code and docs: the actual problem, not just faster authoring.

Source is HPE-internal and cannot be published — architecture and trade-offs walked through on request.