This product was not featured by Product Hunt yet.
It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).

Product upvotes vs the next 3

Waiting for data. Loading

Product comments vs the next 3

Waiting for data. Loading

Product upvote speed vs the next 3

Waiting for data. Loading

Product upvotes and comments

Waiting for data. Loading

Product vs the next 3

Loading

Trace

Local repository intelligence engine

Local Repository Intelligence. Contribute to tarangminds/Trace development by creating an account on GitHub.Understand any codebase with AI, 100% locally on your machine. Trace connects to GitHub repos, builds complex knowledge graphs, and answers architecture questions offline using Ollama. No cloud leaks, no token bills, optimized for Apple Silicon. πŸš€

Top comment

Hey Product Hunt community! πŸ‘‹I’m Tarang, the creator of Trace.As developers, we’ve all been there: you drop into a massive, unfamiliar codebase with hundreds of files, and onboarding takes days. While cloud AI tools can help, copying and pasting internal or proprietary codebases into third-party cloud APIs is a massive security compliance risk for most companies and indie hackers.I built Trace to fix this. It brings deep codebase intelligence directly to your local machine with absolute privacy. Zero data ever leaves your device.How Trace helps you master codebases:πŸ“Š Auto-Constructed Knowledge Graphs: It maps out your source files into a strict relational graph with 15 node types and 17 edge types to chart how modules connect.πŸ” Downstream Impact Analysis: Want to change an export? Trace traces the graph to show you exactly which files will be affected before you commit.🧠 100% Offline AI Chat: Powered by Ollama (defaulting to qwen2.5-coder), you can query your repository's routing, architecture, and bugs on a flight without Wi-Fi.πŸ’» Hardware-Aware Optimizer: Trace automatically scans your Mac's RAM and GPU to recommend the most efficient model size your machine can handle smoothly.It’s open-source, runs natively on macOS (Apple Silicon), and sets up via a few quick terminal commands using pnpm and Ollama.I would love to hear your thoughts, feature requests, and feedback! Are there specific codebases or languages you want to see mapped next?Check out our repository here: github.comThank you for the support! ✨

About Trace on Product Hunt

β€œLocal repository intelligence engine”

Trace was submitted on Product Hunt and earned 3 upvotes and 1 comments, placing #157 on the daily leaderboard. Local Repository Intelligence. Contribute to tarangminds/Trace development by creating an account on GitHub.Understand any codebase with AI, 100% locally on your machine. Trace connects to GitHub repos, builds complex knowledge graphs, and answers architecture questions offline using Ollama. No cloud leaks, no token bills, optimized for Apple Silicon. πŸš€

On the analytics side, Trace competes within Open Source, Developer Tools and GitHub β€” topics that collectively have 627.5k followers on Product Hunt. The dashboard above tracks how Trace performed against the three products that launched closest to it on the same day.

Who hunted Trace?

Trace was hunted by Tarang Kanakamedala. A β€œhunter” on Product Hunt is the community member who submits a product to the platform β€” uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.

For a complete overview of Trace including community comment highlights and product details, visit the product overview.