Hey Product Hunt! I'm Prashant, the developer behind JVM CodeLens.
I built this because I kept running into the same problem: a JVM goes sideways in production, someone captures a heap dump and a GC log, and then the team spends hours manually analyzing them. The worst part? Even after all that analysis, the answer is usually "some code somewhere is allocating too much." Not helpful at 3 AM.
JVM CodeLens takes a different approach: real parsers extract the data, AI does the reasoning. Most "AI debugging" tools feed raw dumps into ChatGPT and hope for the best. That's fragile and inaccurate. We use proper parsers (Eclipse MAT's engine for heaps, Microsoft GCToolkit patterns for GC, JavaParser for AST indexing) to extract structured data, then send that to an LLM for root cause analysis.
The result: instead of "your heap is high," you get "SessionCache.java:142 has an unbounded HashMap growing at 2MB/min because the eviction policy was removed in commit f8a2c1d."
A few things I'm particularly proud of: Remote JFR capture over JMX — Capture Java Flight Recorder data from a remote JVM without filesystem access. Nobody else does this. 7 automated leak detectors — Not simple threshold alerts. Statistical analysis that detects growing trends, class loader leaks, and thread growth patterns. Holt-Winters forecasting — Predicts when your JVM will OOM, with confidence intervals. Real time-series algorithms, not heuristics. Fully offline — Run with Ollama for air-gapped environments. Your source code never leaves your machine.
The Community tier is free forever — no trial, no credit card. I'd love your feedback on what to build next!
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About JVM CodeLens on Product Hunt
“AI finds the exact line of code crashing your JVM”
JVM CodeLens was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #76 on the daily leaderboard. Free desktop JVM profiler that connects heap dumps, GC logs, thread dumps & JFR to your source code. AI pinpoints the exact line causing memory leaks, GC pauses & crashes. 7 leak detectors, predictive forecasting, fully offline with Ollama. macOS/Win/Linux.
JVM CodeLens was featured in Analytics (171.4k followers), Developer Tools (511k followers) and Artificial Intelligence (466.2k followers) on Product Hunt. Together, these topics include over 166.3k products, making this a competitive space to launch in.
Who hunted JVM CodeLens?
JVM CodeLens was hunted by Prashant Gupta. 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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Prashant Gupta
Hey Product Hunt! I'm Prashant, the developer behind JVM CodeLens.
I built this because I kept running into the same problem: a JVM goes sideways in production, someone captures a heap dump and a GC log, and then the team spends hours manually analyzing them. The worst part? Even after all that analysis, the answer is usually "some code somewhere is allocating too much." Not helpful at 3 AM.
JVM CodeLens takes a different approach: real parsers extract the data, AI does the reasoning. Most "AI debugging" tools feed raw dumps into ChatGPT and hope for the best. That's fragile and inaccurate. We use proper parsers (Eclipse MAT's engine for heaps, Microsoft GCToolkit patterns for GC, JavaParser for AST indexing) to extract structured data, then send that to an LLM for root cause analysis.
The result: instead of "your heap is high," you get "SessionCache.java:142 has an unbounded HashMap growing at 2MB/min because the eviction policy was removed in commit f8a2c1d."
A few things I'm particularly proud of:
Remote JFR capture over JMX — Capture Java Flight Recorder data from a remote JVM without filesystem access. Nobody else does this.
7 automated leak detectors — Not simple threshold alerts. Statistical analysis that detects growing trends, class loader leaks, and thread growth patterns.
Holt-Winters forecasting — Predicts when your JVM will OOM, with confidence intervals. Real time-series algorithms, not heuristics.
Fully offline — Run with Ollama for air-gapped environments. Your source code never leaves your machine.
The Community tier is free forever — no trial, no credit card. I'd love your feedback on what to build next!