Free, Risk-Aware Code Review: Auto Approve Low-Risk Changes
Most AI review tools flag issues. LiveReview promises production results: fewer incidents, fewer rollbacks, less senior reviewer load. Every PR is risk-scored. The lowest-risk 30-50% are safely auto-approved; the risky ones go straight to the engineers who should see them. The approach is inspired by Meta's highly successful internal AI review system, where production incidents fell 50x and rollbacks 3x. LLM + incident-trained ML + code-graph analysis. Free and self-hostable.
In February, you helped git-lrc reach #3 Product of the Day. Thank you.
git-lrc fixed one problem: developers committing AI-written code they hadn't read.
As teams adopted it, a bigger problem showed up at the pull request.
AI made code cheap to write. Reviews stayed expensive.
Every PR waited in the same queue for the same few senior engineers.
A renamed variable and a rewritten payment flow got the same attention.
Seniors became the bottleneck. They skimmed. RISKY changes slipped into production.
Most AI review tools add more comments to the thread.
We measure review by production outcomes: fewer incidents, fewer rollbacks, less senior reviewer time.
LiveReview follows the approach behind Meta's highly successful internal AI review system, RADAR: score every change for risk, fast-track the safe ones, and send the risky ones to the right reviewers.
At Meta, this led to 50× fewer production incidents, 3× fewer rollbacks and 35% faster reviews.
Here's how LiveReview does it:
- Auto-approve: the lowest-risk 30–50% are approved instantly. The rest ALWAYS get a human reviewer.
- Risk-first review: high-risk PRs go to the top of the queue with comments sorted by blast radius, sent to the engineers for review.
- Cognitive Coverage: walk through a PR as slides or a summary, or quiz yourself on it before it merges. Your team still understands the code AI writes.
- Livi Assistant: ask about your engineering data in plain English, on the web or in Slack, Teams and Discord. Track adoption, ROI and the teams that need attention across 50+ actionable graphs.
- Integrations: GitHub, GitLab, Bitbucket, Gitea and Azure DevOps.
- Any AI model: reuse the Claude or OpenAI key you already pay for, or any of 15+ AI providers, or use the LiveReview model.
LiveReview is FREE and SELF-HOSTABLE. Run it on your own infra.
“Free, Risk-Aware Code Review: Auto Approve Low-Risk Changes”
LiveReview launched on Product Hunt on November 7th, 2026 and earned 145 upvotes and 32 comments, earning #3 Product of the Day. Most AI review tools flag issues. LiveReview promises production results: fewer incidents, fewer rollbacks, less senior reviewer load. Every PR is risk-scored. The lowest-risk 30-50% are safely auto-approved; the risky ones go straight to the engineers who should see them. The approach is inspired by Meta's highly successful internal AI review system, where production incidents fell 50x and rollbacks 3x. LLM + incident-trained ML + code-graph analysis. Free and self-hostable.
On the analytics side, LiveReview competes within SaaS, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how LiveReview performed against the three products that launched closest to it on the same day.
Who hunted LiveReview?
LiveReview was hunted by Shrijith Venkatramana. 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 LiveReview including community comment highlights and product details, visit the product overview.
Shrijith Venkatramana
In February, you helped git-lrc reach #3 Product of the Day. Thank you.
git-lrc fixed one problem: developers committing AI-written code they hadn't read.
As teams adopted it, a bigger problem showed up at the pull request.
AI made code cheap to write. Reviews stayed expensive.
Every PR waited in the same queue for the same few senior engineers.
A renamed variable and a rewritten payment flow got the same attention.
Seniors became the bottleneck. They skimmed. RISKY changes slipped into production.
Most AI review tools add more comments to the thread.
We measure review by production outcomes: fewer incidents, fewer rollbacks, less senior reviewer time.
LiveReview follows the approach behind Meta's highly successful internal AI review system, RADAR: score every change for risk, fast-track the safe ones, and send the risky ones to the right reviewers.
At Meta, this led to 50× fewer production incidents, 3× fewer rollbacks and 35% faster reviews.
Here's how LiveReview does it:
- Auto-approve: the lowest-risk 30–50% are approved instantly. The rest ALWAYS get a human reviewer.
- Risk-first review: high-risk PRs go to the top of the queue with comments sorted by blast radius, sent to the engineers for review.
- Cognitive Coverage: walk through a PR as slides or a summary, or quiz yourself on it before it merges. Your team still understands the code AI writes.
- Livi Assistant: ask about your engineering data in plain English, on the web or in Slack, Teams and Discord. Track adoption, ROI and the teams that need attention across 50+ actionable graphs.
- Integrations: GitHub, GitLab, Bitbucket, Gitea and Azure DevOps.
- Any AI model: reuse the Claude or OpenAI key you already pay for, or any of 15+ AI providers, or use the LiveReview model.
LiveReview is FREE and SELF-HOSTABLE. Run it on your own infra.
See how it works, then hit Try Free: https://hexmos.com/livereview/
If you like what we're building, star it to help devs discover LiveReview: https://github.com/HexmosTech/LiveReview