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Code Analysis
AI software docs from interviews, SQL and screens
Turn interviews, SQL and screenshots into connected software documentation. Draft editable PlantUML diagrams, data dictionaries and user manuals with AI, then refine them in project-aware chat. Choose eligible models and review credit estimates before use.
Hi Product Hunt! I’m Alexandre, the maker of Code Analysis.
I built it while analyzing a system implementation. Interviews helped me understand the work, but I needed a way to turn that knowledge into use cases. From there, the product grew into SQL documentation, screen-based documents, and user manuals.
Code Analysis keeps the sources and the work together: • Organize interviews, SQL, and screenshots in a project. • Draft diagrams, data dictionaries, and manuals with AI. • Choose an eligible model and review the credit estimate. • Refine documents in contextual chat and revisit version history.
The library includes 26 configurable diagram types and notations. PlantUML source is editable and exportable.
Plans are individual; AI and metered file transfers share one CodeCredits balance.
If you analyze, implement, or document software, which part of turning scattered knowledge into useful documentation is hardest for you? I’d love your feedback.
About Code Analysis on Product Hunt
“AI software docs from interviews, SQL and screens”
Code Analysis was submitted on Product Hunt and earned 4 upvotes and 1 comments, placing #95 on the daily leaderboard. Turn interviews, SQL and screenshots into connected software documentation. Draft editable PlantUML diagrams, data dictionaries and user manuals with AI, then refine them in project-aware chat. Choose eligible models and review credit estimates before use.
On the analytics side, Code Analysis competes within Productivity, Developer Tools and Artificial Intelligence — topics that collectively have 1.7M followers on Product Hunt. The dashboard above tracks how Code Analysis performed against the three products that launched closest to it on the same day.
Who hunted Code Analysis?
Code Analysis was hunted by Alexandre Monteiro de Mello. A “hunter” on Product Hunt is the community member who submits a product to the platform — 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 Code Analysis including community comment highlights and product details, visit the product overview.
Alexandre Monteiro de Mello
Hi Product Hunt! I’m Alexandre, the maker of Code Analysis.
I built it while analyzing a system implementation. Interviews helped me understand the work, but I needed a way to turn that knowledge into use cases. From there, the product grew into SQL documentation, screen-based documents, and user manuals.
Code Analysis keeps the sources and the work together:
• Organize interviews, SQL, and screenshots in a project.
• Draft diagrams, data dictionaries, and manuals with AI.
• Choose an eligible model and review the credit estimate.
• Refine documents in contextual chat and revisit version history.
The library includes 26 configurable diagram types and notations. PlantUML source is editable and exportable.
Plans are individual; AI and metered file transfers share one CodeCredits balance.
If you analyze, implement, or document software, which part of turning scattered knowledge into useful documentation is hardest for you? I’d love your feedback.