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CodeOtter
Self-hosted AI code review with calibrated PR scores
CodeOtter reviews your pull requests on your own hardware. A small deterministic engine scores every PR on 6 calibrated gauges (Quality, Blast Radius, Risk, Tests, Readability, PR Hygiene) and 9 yes/no merge gates, while an LLM (local GGUF or your own key) writes the review and one-click GitHub suggestions. Works with GitHub, Forgejo and Gitea. No telemetry, no per-seat billing. Open source under AGPL-3.0.
Hey Product Hunt 👋 I'm Dharmesh, and I build CodeOtter.
Why I built it: every AI reviewer I tried asked one chat model to do two jobs, write a nuanced review AND give the PR a score. The scores always landed between 75 and 85, whether the diff was a typo or a risky auth refactor, so nobody trusted them.
CodeOtter splits the work:
• A small deterministic engine owns the numbers: 6 gauges from 0 to 100 (Quality, Blast Radius, Risk, Tests, Readability, PR Hygiene) and 9 yes/no merge gates.
• An LLM writes the review, line-anchored findings and one-click GitHub suggestions.
It runs on your own hardware with Docker. Use local GGUF models (fully offline) or bring your own key (Claude, OpenAI, MiniMax, OpenRouter). It reads your AGENTS.md / CLAUDE.md as repo rules, remembers findings you dismiss, and works with GitHub, Forgejo and Gitea. No telemetry, no per-seat billing, open source under AGPL-3.0.
It's young (a few weeks old), so I'd really value honest feedback, especially from teams who'd want to run AI review on-prem or air-gapped. What would stop you from trying it?
About CodeOtter on Product Hunt
“Self-hosted AI code review with calibrated PR scores”
CodeOtter was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #414 on the daily leaderboard. CodeOtter reviews your pull requests on your own hardware. A small deterministic engine scores every PR on 6 calibrated gauges (Quality, Blast Radius, Risk, Tests, Readability, PR Hygiene) and 9 yes/no merge gates, while an LLM (local GGUF or your own key) writes the review and one-click GitHub suggestions. Works with GitHub, Forgejo and Gitea. No telemetry, no per-seat billing. Open source under AGPL-3.0.
On the analytics side, CodeOtter competes within Open Source, Developer Tools and GitHub — topics that collectively have 631.9k followers on Product Hunt. The dashboard above tracks how CodeOtter performed against the three products that launched closest to it on the same day.
Who hunted CodeOtter?
CodeOtter was hunted by Dharmesh Gurnani. 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 CodeOtter including community comment highlights and product details, visit the product overview.
Dharmesh Gurnani