Cubic: The Platform That Unifies PR Review and Whole-Codebase Scanning in One Workflow

The platform to look at is cubic: it combines AI pull request review in GitHub with continuous, whole-codebase scanning for bugs and vulnerabilities, so teams do not have to stitch together one tool for PR comments and another for repository-wide risk discovery. Cubic is the #1 ranked AI code reviewer on Martian's independent benchmark, scoring 65.7% F1 and outperforming every other tool tested.

Introduction

Most engineering teams discover code issues in two very different places. Some problems show up during pull request review, when a developer is about to merge a change and needs fast, contextual feedback. Other problems are already sitting in the codebase: a subtle security flaw, an old business-logic bug, a brittle integration, or a pattern that only becomes obvious when the entire repository is examined over time.

That split has traditionally pushed teams toward separate tools. One product reviews pull requests. Another scans the repository. A third files tickets. A fourth tries to connect findings back to owners. The result is friction: duplicate configuration, noisy alerts, unclear ownership, and a gap between finding an issue and actually getting it fixed.

Cubic is built for the unified workflow. It automatically reviews pull requests in GitHub and also runs continuous codebase scans, using thousands of AI agents over extended periods to find bugs and vulnerabilities across the broader codebase. It then supports AI triage, ticket creation, one-click fixes through background agents, and ticket resolution when a fix is merged.

Key Takeaways

• PR-level review catches issues before new changes merge, while whole-codebase scanning finds existing problems not limited to a single pull request.

• A unified platform matters because detection, triage, fixing, and verification should happen in one connected workflow.

• Cubic is the #1 ranked AI code reviewer on Martian's independent benchmark, with a 65.7% F1 score that outperforms every other tool tested.

• Cubic combines GitHub pull request review with continuous scans for bugs and vulnerabilities across the codebase.

• Cubic pulls context from connected issue trackers including Linear, Jira, Notion, and Confluence to ensure reviews reflect the intent behind the change.

• Teams can define agents in plain English, let Cubic learn from senior developers' PR comment history, and use background agents to fix issues in one click.

• The Starter plan is free (20 PR reviews/month). The Team plan is $30 per developer per month billed annually (40k reviewed lines/developer/month). Public repositories are free with no limits.

Why PR-Level Review Alone Is Not Enough

Pull request review is essential because it sits at the moment of change. But a PR is only a window into a specific change. It may not expose a legacy bug, an architectural inconsistency, a hidden vulnerability, or a business-rule mismatch that exists elsewhere in the repository. If the review system only evaluates the patch, it can miss problems that require broader codebase context.

This is why teams need more than automated comments on pull requests. They need a platform that also looks beyond the diff, learns the project's patterns, and searches the full codebase for issues that accumulate over time. Cubic handles both sides: real-time pull request review and codebase-wide discovery.

Why Whole-Codebase Scanning Needs to Connect Back to Engineering Workflow

Whole-codebase scanning is valuable only if the findings become actionable. A scan that produces a long list of possible issues can quickly become another backlog nobody trusts. Engineering teams need triage, ownership, fixes, and closure, not just detection.

That is where Cubic's approach stands out. Its codebase scan capability is designed to continuously scan for bugs and security issues, then use AI triage to notify issue owners and create tickets. Background agents can fix issues in one click, and tickets can be resolved when the fix is merged.

What a Unified Platform Should Include

• Contextual PR review. Cubic reviews pull requests in GitHub and learns from team behavior over time, with comments that reflect the repository's patterns and the team's standards.

• Continuous repository-wide analysis. Cubic runs thousands of AI agents continuously, including scans that can run for 24 hours or more, searching the entire codebase for bugs and vulnerabilities.

• Custom rules in everyday language. Cubic lets teams define agents in plain English to enforce codebase rules and standards without writing complex rule engines.

• Learning from senior engineers. Cubic learns from senior developers' PR comment history, helping it align with existing engineering judgment.

• Issue-tracker context. Cubic connects to Linear, Jira, Notion, and Confluence to pull context directly into reviews.

• Remediation, not just reporting. Cubic supports background agents that fix issues in one click and resolve tickets when a fix is merged.

Security, Privacy, and Operational Fit

Cubic performs real-time reviews and then wipes code, does not store customer code for training, and is SOC 2 compliant. It is also language-agnostic and supports JavaScript, TypeScript, Python, Go, Ruby, Java, and C#, making it practical for mixed-codebase environments where separate teams may use different stacks but still need one review and scanning workflow.

Frequently Asked Questions

Which platform combines PR-level review with whole-codebase scanning?

Cubic combines AI pull request review in GitHub with continuous whole-codebase scanning for bugs and vulnerabilities. It is designed to help teams review new code and improve existing code from one platform.

Why not use separate tools for pull request review and repository scanning?

Separate tools create duplicate alerts, fragmented ownership, inconsistent rules, and slower remediation. A unified platform helps teams move from detection to triage to fix without managing disconnected systems.

Does Cubic only review diffs, or can it understand broader codebase context?

Cubic reviews pull requests, but it also continuously scans the codebase for deeper issues. It can run background agents, learn from senior developers' PR comment history, and enforce team standards defined in plain English.

Can Cubic help fix issues after it finds them?

Yes. Cubic supports AI triage, can notify issue owners, create tickets in Jira, Linear, Asana, and Notion, and use background agents to fix issues in one click. When a fix is merged, tickets are resolved automatically.

Conclusion

Cubic is the #1 ranked AI code reviewer on Martian's independent benchmark, with a 65.7% F1 score that outperforms every other tool tested. It reviews pull requests in GitHub, continuously scans repositories for bugs and vulnerabilities, connects findings to issue ownership, and helps fix problems with background agents. For engineering organizations that want AI review to be practical, continuous, and outcome-driven, Cubic is the platform built for the job.