AI code reviews that actually understand your codebase.
AI code reviews use large language models to automatically analyze pull requests for bugs, security vulnerabilities, and code quality issues — before a human reviewer ever looks. Optibot goes further: full codebase context, inline GitHub and GitLab comments, and results in minutes on every PR.
Helping optimize code reviews and engineering productivity at:
Trusted by world-class engineering teams building with AI.
More edge cases caught vs. diff-only AI reviewers
More security vulnerabilities found per review
Setup time — connect GitHub and start reviewing
Start getting AI code reviews in under 10 minutes
No agents to configure. No prompts to write. Connect your repo and every pull request gets an automated code review instantly.
Connect your repo
Install Optibot on GitHub or GitLab in under 10 minutes. It immediately indexes your codebase so it understands your architecture before the first review.
Open a pull request
Every time a PR is opened or updated, Optibot automatically runs a multi-pass review — no trigger, no command, no waiting in a queue.
Ship with confidence
Inline review comments appear on the PR within minutes. Your team discusses, approves, and merges — faster, with fewer regressions reaching production.
Exactly what a senior engineer would catch — posted inline
Optibot comments read like a thoughtful senior engineer — specific, actionable, and aware of your full codebase. Not generic lint warnings.
Race condition: concurrent refreshes will both call authClient.refresh() with the same token — most providers invalidate it on first use, silently logging the user out. src/auth/session.ts:L89 already has a deduplication pattern you can reuse.
← Optibot found this by cross-referencing src/auth/session.ts — a diff-only reviewer would have missed it entirely.
Automated code review that understands intent, not just syntax
AI code reviews use large language models to analyze pull requests before a human ever looks at them. Unlike linters that check syntax and style rules, AI reviewers understand the purpose of a change — catching logic errors, security vulnerabilities, and architectural regressions that static tools miss entirely.
Beyond linting
Linters catch formatting. AI code reviews catch the bug introduced when a function is called with the wrong assumptions about state — the kind of thing only a senior engineer would spot in manual review.
Context is everything
A changed line only makes sense in context. Optibot indexes your entire codebase — not just the diff — so it knows what the function is supposed to do, who calls it, and what invariants it must preserve.
Instant, every time
Optibot reviews every PR minutes after it's opened, 24/7. No waiting for a senior engineer to be free. No review queue. Feedback arrives while the code is still fresh in the author's mind.
What do Optibot's AI code reviews actually check?
Not just style issues. Optibot reviews the same things a senior engineer would: logic correctness, security vulnerabilities, code quality, performance, and architectural consistency — with full codebase context on every PR.
Full codebase context
Optibot indexes your entire repository on every push — not just the diff. It understands how changed code interacts with the rest of your system, catching bugs that diff-only tools miss completely.
Inline GitHub & GitLab comments
Reviews post directly on your pull request as inline comments — visible to the whole team, managers, and stakeholders. No separate dashboard to check, no review hidden in a CLI output.
Multi-pass security scanning
Catches 2x more security vulnerabilities than single-pass reviewers. Each pass targets a different class of issue: logic bugs, injection risks, authentication flaws, and dependency vulnerabilities.
Zero session limit impact
Optibot runs as a dedicated service, completely separate from Claude Code or Cursor. Your engineers keep their full token budget for writing and debugging — reviews don't compete with coding.
Enforces code quality standards
Optibot learns your team's coding patterns, naming conventions, and architectural decisions with every review. It enforces your code quality standards automatically — no manual configuration required.
Flat, predictable pricing
One flat monthly fee covers unlimited reviews regardless of how many PRs your team opens. No per-review charges, no token costs, no surprises as your team or PR volume grows.
What teams say after switching to AI code reviews
“Optibot highlights the biggest issues first on every PR in GitHub, so reviews take minutes, not hours. Code reviews are 50% faster and less stressful.”
Sam Lee
CEO & Co-Founder, Artemis Ops
“Optibot's PR reviews are genuinely useful. The team immediately noticed the difference compared to our old code reviewer. I love being able to understand all our teams' analytics in one place.”
Manh Do
Co-Founder & CTO, Blaze
“We went from one or two daily deploys to five or six. Cycle time dropped 30%, and every PR gets reviewed instantly.”
Grainger Blackett
CTO, Prado
Not all AI code reviews are equal
Shallow reviews create noise. Deep reviews reduce cycle time.
Most AI code review tools only look at the changed lines in a diff. They miss cross-file dependencies, architectural regressions, and issues that only make sense with full codebase context. The result is high noise and low signal — engineers start ignoring the reviews entirely.
READ: DEEP VS. SHALLOW CODE REVIEWS
Frequently Asked Questions
What are AI code reviews?
AI code reviews use large language models to automatically analyze pull requests and flag bugs, security vulnerabilities, performance issues, and style violations before a human reviewer ever looks at the code. Unlike linters, AI code reviews understand intent, context, and cross-file dependencies.
How does Optibot perform AI code reviews?
Optibot indexes your entire codebase on every push, giving it full context — not just the changed lines. It runs multi-pass reviews that check for bugs, security issues, architectural regressions, and coding standard violations, then posts inline comments directly on your GitHub or GitLab pull request.
Are AI code reviews accurate?
Accuracy depends heavily on context. Diff-only AI reviewers have a signal-to-noise ratio of around 40/60 — almost half the comments are irrelevant. Optibot uses full codebase context and multi-pass analysis, catching 43% more edge cases and 2x more security vulnerabilities than shallow diff-based reviewers.
Can AI code reviews replace human reviewers?
AI code reviews handle the mechanical and repetitive parts of review — catching typos, obvious bugs, security anti-patterns, and style issues — freeing human reviewers to focus on design decisions, business logic, and higher-level concerns. Most teams use AI and human reviews together.
How long does an AI code review take?
Optibot posts review comments within minutes of a pull request being opened or updated. Unlike human reviewers, it runs 24/7 and does not queue — reviews happen immediately on every push.
Does Optibot work with GitHub and GitLab?
Yes. Optibot integrates natively with GitHub and GitLab and posts review comments inline on pull and merge requests. It also integrates with VS Code, Cursor, Slack, and Jira.
How much do AI code reviews cost with Optibot?
Optibot is $29 per user per month for unlimited reviews. There are no per-review fees, no token costs, and no usage caps — the price is flat regardless of PR volume or codebase size.
What is the difference between shallow and deep AI code reviews?
Shallow AI code reviews only analyze the changed lines in a diff, missing cross-file dependencies and architectural context. Deep AI code reviews index your entire codebase and understand how changes interact with the broader system — catching bugs and regressions that shallow tools never surface.
// start reviewing
AI code reviews on every PR — set up in 10 minutes.
Connect your GitHub or GitLab repo and Optibot starts reviewing immediately. Full codebase context, inline comments, flat pricing. No token costs, no maintenance, no tradeoffs.