# CodeRabbit vs Entelligence: AI Code Review Benchmark

> Entelligence vs CodeRabbit on 67 real production PRs: 47.2% F1 vs 33.0%, 50.0% precision vs 24.8%, and reviews in 10-30s instead of 1-3 min.

Source: https://entelligence.ai/vs/coderabbit.ai

**CodeRabbit vs Entelligence** Head-to-head PR review comparison

We benchmarked both tools on 67 real production pull requests across 5 major open-source repositories using F1 score, precision, and review speed.

## At a glance

- F1 Score: 47.2% (vs CodeRabbit 33.0%)
- Precision: 50.0% (vs CodeRabbit 24.8%)
- Review Speed: 10-30s (vs CodeRabbit 1-3 min)
- Docs Always in Sync: 100% (vs PR summaries only)

## On PR Review Quality

We ran a head-to-head benchmark across real-world pull requests using F1 score, the standard measure that balances precision and recall.

- F1 Score: Entelligence 47.2% vs CodeRabbit 33.0%
- Recall: Entelligence 44.8% vs CodeRabbit 49.2%
- Precision: Entelligence 50.0% vs CodeRabbit 24.8%
- Golden Comments Found: Entelligence 30 / 67 vs CodeRabbit 32 / 65

CodeRabbit finds a slightly higher number of golden comments, which shows its recall is genuinely solid. But at 24.8% precision, the ratio of useful to non-useful comments is a real challenge at scale. Entelligence sits at 50.0% precision, meaning engineers spend less time sorting through feedback and more time acting on it.

## What Makes Teams Look Beyond CodeRabbit

- **Precision over volume.** CodeRabbit’s recall is strong, meaning it catches a wide range of issues. But with a precision of 24.8% in our benchmarks, a significant portion of its comments don’t land as actionable.
- **No engineering visibility.** CodeRabbit focuses on the PR. Once code is merged, there’s no view into team velocity, code health trends, or how individual engineers or squads are performing.
- **No AI ROI tracking.** Most engineering teams today are running Cursor, Copilot, or Claude alongside their review tools. CodeRabbit doesn’t measure whether those tools are actually moving the needle.
- **Limited to PR workflows.** There’s no Slack integration, no leadership dashboard, and no way to get a quick status update on your team without opening another tab.

## Beyond the PR

- **Team and velocity metrics.** Output per engineer and team, review turnaround times, and performance trends — all in one dashboard.
- **Code churn and risk.** See which repos and files are accumulating risk before they become incidents. Codebase-wide health, not just the current diff.
- **AI ROI tracking.** LOC multiplier, cost efficiency, acceptance rates, and dollar-value savings — hard numbers for when leadership asks what the AI budget is returning.
- **Ask Ellie, AI in Slack.** An AI agent inside Slack that gives engineering leaders instant answers about team health, velocity, and blockers.

## Which Tool Fits Your Team

| Feature | CodeRabbit | Entelligence |
| --- | --- | --- |
| Deep PR Review | full | full |
| Precision Comments | partial | full |
| Multi-repo Support | full | full |
| Learns from Incidents | none | full |
| Team Velocity Tracking | none | full |
| AI ROI Measurement | none | full |
| Engineering Leadership Dashboard | none | full |

## The Bottom Line

CodeRabbit is solid for teams that want fast PR review out of the box. Entelligence adds the engineering visibility layer — team health, AI ROI, and risk — that leaders need on top of code review.

_This comparison is published by the Entelligence team using data from an independent open-source benchmark. If anything here is inaccurate, let us know and we’ll update it._

All comparisons: [Compare Entelligence](https://entelligence.ai/vs.md)