DevSwat Code Analysis is a code intelligence platform that turns large codebases into interactive maps, dependency graphs, and governance reports. Unlike traditional static analyzers, it combines scan, compare, trace, and agent workflows so teams can understand architecture, review changes, and act on issues in one place. It also supports GitHub scans, uploads, saved analyses, and AI-assisted governance, making it useful for both local exploration and team-scale code review.
So while using AI for coding I relays that the context window are getting up so fast if I have big code base which cost burn of the tokens and hallucination so I create the GPS navigation for AI Agent to get fast acess to the code base and navigate through which eliminate hallucination, token consuming and code drift.
The scan/compare/trace-in-one-place framing beats yet another static analyzer that dumps a graph and leaves you to interpret it. Since it does GitHub scans plus direct uploads and AI-assisted governance, does my source get sent to a hosted model or your servers to build the maps, or can the analysis run locally so a private codebase never leaves my machine? And is the dependency graph built from real static analysis, or inferred by the LLM in a way that can hallucinate an edge that is not actually in the code?
Finally got around to poking at DevSwat, and the observability hooks feel genuinely useful for catching flaky model behavior. Nice to see someone focused on making AI dependable instead of just flashy.
Have you considered adding a visual debugging dashboard that shows model decision paths in real time? It would be super useful for spotting exactly where the AI drifts or fails in production without digging through logs.
Have you considered adding a built-in cost-tracking dashboard that breaks down token spend and latency per request? Would make it way easier to justify the bill to stakeholders and spot which workflows are quietly eating budget.
Love the idea of making complex codebases easier to understand visually. Interactive maps and governance can save teams a lot of time when onboarding or maintaining large systems, especially as AI-generated code becomes more common.
Curious...does DevSwat integrate with GitHub and support tracking architectural changes over time?
one thing that would be super helpful is a built-in dashboard for tracking model drift and confidence scores over time, so teams can see at a glance when something is going sideways in production without digging through logs
About DevSwat AST- visualizer with analyzer on Product Hunt
“Turn codebases into interactive maps, graphs, and governance”
DevSwat AST- visualizer with analyzer launched on Product Hunt on July 16th, 2026 and earned 86 upvotes and 15 comments, placing #26 on the daily leaderboard. DevSwat Code Analysis is a code intelligence platform that turns large codebases into interactive maps, dependency graphs, and governance reports. Unlike traditional static analyzers, it combines scan, compare, trace, and agent workflows so teams can understand architecture, review changes, and act on issues in one place. It also supports GitHub scans, uploads, saved analyses, and AI-assisted governance, making it useful for both local exploration and team-scale code review.
DevSwat AST- visualizer with analyzer was featured in Developer Tools (515.9k followers) and GitHub (41.3k followers) on Product Hunt. Together, these topics include over 100.9k products, making this a competitive space to launch in.
Who hunted DevSwat AST- visualizer with analyzer ?
DevSwat AST- visualizer with analyzer was hunted by Liubov Nemesh. 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.
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Liubov Nemesh