Alternatives
Products that do what We create visual codebase maps that scale (static analysis and LLMs) does
Hi all, I'm Ivan, and together with Alex, we're building a diagram visualization tool for codebases. Alex and I are devs, and we've noticed that recently we've been super productive at writing code (prompting :D). But when it comes to understanding big systems, prompting doesn't work that well — for that, diagrams are best imo. Most tools out there don't scale to big projects (e.g. PyTorch), so we're building CodeBoarding — a recursive visualizer for codebases. It starts from the highest level of abstractions and lets you dive deeper. We use static analysis and LLM agents. The control-flow…
- 1CV
I worked as a software engineer at Amazon, SAP, and on open source. In all 3 places I have struggled with the friction of understanding codebases before I can make a contribution. I think this brain-fatiguing process can be improved. I am trying to solve it with a tool I built over the last 4 years called CodeCanvas: https://docs.code-canvas.com CodeCanvas visualizes codebases through interactive diagrams linked directly to source code. Users can record 'simulations' to demonstrate data flow and business logic. I’ve also recently added an LLM chat where it takes only the relevant…
2025 · pie-crepe-38f.notion.site
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2020 · codemap.app
- 3VA
I explored an alternative way to view codebases to the typical folder/file list, showing a bird's-eye-view of its structure. https://octo.github.com/projects/repo-visualization
2021 · octo.github.com
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2020 · github.com
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Turn codebases into interactive maps, graphs, and governance
Jul 2026 · dev-swat.com
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2020 · usecodeflow.com
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2021 · github.com
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As a former CIO who managed teams working with millions of lines of legacy code (Visual Basic, Sybase, Oracle Forms, and worse), I feel the pain of maintaining and onboarding developers to legacy systems. Believing that LLM-enabled tools can play a role in solving this, I've built a tool that automatically generates documentation for legacy codebases using the Model Context Protocol (MCP) & Claude Sonnet. At first glance, I think this approach has merit. Some samples are in the README. I welcome your thoughts. The Problem: - Legacy codebases are notoriously difficult to understand and…
2025 · github.com
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2021 · gleek.io
- 15CA
Hey there HN! We're Vivek and Si-Yan from Cartograph (https://cartograph.app). We've built an AI-powered code documentation platform that automatically generates reference documentation and creates a visual interactive map of the codebase that serves as both high level architecture diagram and allows you to zoom in to specific implementations. How it works: We use static analysis to read a codebase and get its symbols and their dependencies, creating a complete map that includes function calls. We use LLMs (Gemini + Claude) to add metadata to this map, as well as augment it in…
2024 · cartograph.app
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I built a CLI tool that turns codebases and PRs into diagrams so you can quickly understand how things fit together. Originally made it because I couldn't follow my own AI-generated repos. Just shipped a big update: - Switched from D2 to Mermaid for rendering - Tree-sitter AST parsing + agentic flow instead of raw LLM calls. ~50x faster. - Works on any GitHub repo or PR, not just local - Dropped the web frontend, it's just a CLI now - Published as a pip package Still a ton to improve and I'm building fast. Feedback, issues, PRs all welcome.
Feb 2026 · github.com
- 17IB
After years of struggling with onboarding to new projects, I got tired of spending weeks just trying to grasp the basics of a codebase. The README rarely tells the whole story, and "just read the code" isn't practical for large repos. I built RepoIQ to create personalized learning paths through any GitHub repository. It analyzes the codebase structure, identifies key components, and creates a step-by-step guide tailored to your learning needs.
2025 · repoiq.be
- 18CM
For years, I’ve been obsessed with mapping code visually — originally by copy-pasting snippets into FreeMind to untangle large code bases in big complex projects. It worked, but it was clunky. Now, I’ve built a VS Code/Visual Studio extension to do this natively: Code Mind Map. You can use it to add selected pieces of code to a mind map as nodes and then click to jump to the code from the map. Developers say it’s especially useful for: Untangling legacy code Onboarding into large codebases Debugging tangled workflows Please try it out and let me know what you think!
2025 · github.com
- 19GM
Hi HN, I built Repomap, a tool that generates interactive architecture diagrams from any GitHub repository. It uses a Rust + tree-sitter engine to analyze the codebase and produces a D3-based graph UI with clustering, zoom/pan, and live progress updates
Feb 2026 · github.com
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Hi HN, I built ast-visualizer.com because I wanted a way to visualize the architecture/structure of a Python repo before dived into the code. Most tools tell you what the code does; I wanted to see how it's built. The Problem: Onboarding onto a large codebase is a nightmare. LLMs help with single functions, but they struggle to show you the "God Objects," circular dependencies, or high-complexity hotspots across 50+ files. What it does: Dependency Graph: Visualizes imports and file complexity to find architectural bottlenecks. Radial AST Heatmaps: Maps individual files and color-codes…
Feb 2026 · ast-visualizer.com
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A friend and I spent a month throwing together a visual rule engine product– wanted to share it with HN today. I've been building automation tooling for a few years at prefix.app and one of the messier things both to support and to teach users was around encoding logic in their automations– most folks get a hold of the basic concepts quite easily, but every (visual) automation tool out there seems to have their own way of actually pulling it all together. For small decisions those work great! But for bigger decisions and more complex logic we don’t think it makes much sense to be embedding…
2022 · rulebricks.com
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Hello HN, I am building a devtool to understand existing codebases. The idea originates from my time at big tech as well as various attempts to get involved in open source projects. When I was in college I wanted to improve my coding skills by contributing to opensource projects. I would pickup a bug or feature request but I always found myself stuck at the very first step. I did not understood where and how to begin contributing. I once submitted a patch in firefox which was labeled "Good first issue" but that was still very handheld. The assigner told me exactly which files I need to…
2024 · lucidcode.ai
- 23CM
I've been vibe-coding tools to automate chunks of my consulting work, fell down a rabbit hole, and started building actual products. Suddenly I'm in a world of unknown-unknowns and known-unknowns. One of the bigger things to solve was understanding code the LLM generated that I didn't fully grasp. What does it touch? What reads and writes where? Is the auth path where I think it is? So I built codeflowmap. Point it at a repo and it maps the dependency and call graph, then surfaces the read / write / auth paths between files and functions. Connect a local model (Ollama) or any…
Jun 2026 · github.com
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Hey HN, We’re excited to share PySpur, an open-source tool that provides a graph-based interface for building, debugging, and evaluating LLM workflows. Why we built this: Before this, we built several LLM-powered applications that collectively served thousands of users. The biggest challenge we faced was ensuring reliability: making sure the workflows were robust enough to handle edge cases and deliver consistent results. In practice, achieving this reliability meant repeatedly: 1. Breaking down complex goals into simpler steps: Composing prompts, tool calls, parsing steps, and branching…
2024 · github.com
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