Launching today
LiveReview
Free, Risk-Aware Code Review: Auto Approve Low-Risk Changes
39 followers
Free, Risk-Aware Code Review: Auto Approve Low-Risk Changes
39 followers
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.
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Promoted
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
curious how it handles a tiny diff in a scary file, like a one line change to auth config. that's the kind of pr i'd never want auto approved
@gevorgarakelyann It has a huge list of signals feeding into it. File size is only one of the parameters. We build a graph analysis of the entire code base -- for example if many other parts of code depend on auth module -- the risk profile will reflect that. We also have traditional ML, plus LLM semantic analysis. And the thing learns over time, so it gets better as you use it.
@shrsv the dependency graph part makes sense, small change + lots of things depending on it = high risk. thanks for explaining
@lucasjpols Thank you, Lucas, for the support!
cool launch, congrats!! if a one-line config change hits the payments path, does LiveReview flag it from the code graph or could it get auto approved as low risk?
@igorblink thanks for engaging. For things such as auth, security and payments -- it'll catch things as high risk and flag it for humans for review.
Each organization can also define it's risk appetite as a percentile, so a regulated enterprise can have a conservative setting whereas a startup can take more aggressive risks and our tool helps each org set the risk threshold they wish to take on.
There are also individual sliders for various risk dimensions in correctness, compliance, security, performance, scaling, cloud costs, etc.