10 Best AI Code Review Tools 2026 - PR Review, Bugs, and Cost

Your team is merging more AI-written code than it can comfortably review. The problem is not just reviewer bandwidth. It is the hidden risk: a generated helper that bypasses validation, a refactor that breaks an edge case, a security issue buried in a large pull request, or an AI agent opening changes faster than senior engineers can read them. The best AI code review tools in 2026 help engineering teams catch those problems earlier, but they are not interchangeable. Some behave like PR reviewers, some are code quality platforms with AI layered in, and some are AI coding tools with review features attached.

This guide compares 10 AI code review tools for engineering managers, staff engineers, platform teams, and developer productivity leads who need better pull request coverage without flooding developers with low-value comments. We prioritized tools with clear PR or code review workflows, real Git provider integrations, repo-level context, security or quality checks, public pricing signals, and enough product documentation to evaluate tradeoffs. If you are comparing the broader coding assistant market, start with our best AI coding tools guide; if your main need is static analysis and code security, also review our AI code checker tools category.

How We Selected and Tested

We selected these AI code review tools based on measurable criteria: explicit support for pull request, merge request, diff, commit, or repository-level code review; integration with real developer workflows such as GitHub, GitLab, Bitbucket, Azure DevOps, IDEs, CLI, or CI/CD; evidence of AI-assisted reasoning rather than only traditional linting; and enough pricing or trial information for buyers to estimate cost. Generic coding assistants were included only when their review workflow was specific enough to evaluate as a code review product.

Our research combined ChatGPT deep research, official product pages, pricing pages, documentation, marketplace listings, and public user-feedback signals. We cross-checked the highest-risk facts against current official sources in June 2026, especially pricing and billing models. That mattered because AI developer tools are moving toward credits, usage-based pricing, and bundled plans. A tool that looks cheap at $10 to $30 per seat can still become expensive if every large PR, agent run, or review retry consumes usage.

Evaluation Dimensions: We evaluated each tool across five buyer-centered dimensions:

1. Review Depth - Whether the tool reads full repository context, diffs, PR metadata, rules, tests, security issues, and cross-file dependencies.
2. Workflow Fit - Git provider coverage, IDE or CLI support, ease of installation, and how naturally comments fit human review.
3. Signal Quality - Ability to reduce noise, prioritize meaningful issues, explain reasoning, and avoid linter-style clutter.
4. Cost Predictability - Public pricing, trial availability, included reviews or credits, overage rules, and enterprise packaging clarity.
5. Governance and Security - Self-hosting, no-code-storage claims, SAST integration, policy controls, auditability, and team administration.

Note on Testing Scope: We reviewed publicly available product surfaces and pricing signals rather than running every tool against the same private repository. For products that require a trial or private repository connection to test fully, we relied on official documentation and clearly note price or implementation gaps.

Transparency & Limitations: AI code review quality depends heavily on repository size, language, test quality, review culture, and how much context the tool can access. Treat this ranking as a procurement shortlist, not a replacement for a proof of concept on your own repos. Pricing was checked in June 2026 and may change.

Top 10 AI Code Review Tools Compared

The AI code review market splits into three useful groups. CodeRabbit, Qodo, Greptile, Graphite, Bito, and Sourcery are review-first tools. GitHub Copilot Code Review is strongest for teams already paying for Copilot. DeepSource, Codacy, and CodeAnt AI are broader code quality or security platforms where AI review is part of a larger engineering-quality workflow. The right choice depends on whether your biggest pain is slow PR turnaround, review noise, security coverage, cost predictability, or fitting the tool into an existing Git provider.

Detailed Reviews

CodeRabbit

When senior engineers are spending review time on naming, missed null checks, and repeated explanations, the real bottleneck is not code volume. It is low-signal review work. CodeRabbit is the most focused tool in this list for replacing that repetitive layer with automated PR comments, summaries, rule checks, linters, SAST support, and autofix-style suggestions.

Key Features

• Dedicated PR review workflow: CodeRabbit is built around reviewing pull requests rather than acting as a general coding assistant. That makes it easier to evaluate against review quality, comment relevance, and merge-readiness.
• Broad Git provider support: It supports GitHub, GitLab, Azure DevOps, Bitbucket, CLI, and IDE workflows, which matters for teams that cannot standardize on one code host.
• Rules, linters, and SAST support: CodeRabbit combines AI comments with more deterministic checks, so teams can tune quality gates instead of relying on a black-box reviewer.
• Autofix and finishing touches: Higher plans include features such as docstring generation, autofix, pre-merge checks, and product analytics dashboards.

Pricing & Plans

CodeRabbit has a Free plan for PR summarization and IDE/CLI reviews with lower limits, an Open Source tier for public OSS projects, Pro at $30 per developer monthly or $24 annually, Pro+ at $60 monthly or $48 annually, and Enterprise on custom pricing. Pro includes PR reviews, linters and SAST support, analytics, docstrings, autofix, and usage-based add-on access. Pro+ adds higher limits and pre/post-review actions such as issue planning, unit test generation, merge-conflict resolution, and simplify actions. The buying risk is not only seat cost: CodeRabbit now enforces per-developer hourly review limits, so busy teams should check review volume, automatic incremental reviews, and whether the usage-based add-on is enabled.

Pros & Cons

Pros: CodeRabbit is highly focused on pull request review, supports major Git providers, and combines AI comments with linters, SAST, analytics, docstrings, and autofix workflows.

Cons: Teams must tune rules and comment expectations to avoid bot noise, Pro and Pro+ review limits need monitoring, and CodeRabbit will not replace architectural review, product judgment, or domain-specific reasoning about user behavior. Teams should also decide whether AI comments block merges, only inform reviewers, or trigger human follow-up. Without that policy, automated comments can create review fatigue.

Best For

CodeRabbit is the best first shortlist pick for teams that want a dedicated AI code review tool across multiple Git providers. Not the right fit if your primary need is a broader AI coding assistant, a self-hosted-only architecture, or security scanning as the central buying driver.

Get started with CodeRabbit

Qodo

Many teams do not just need comments after a pull request opens. They need problems caught before the PR, rules enforced consistently, and review logic that understands the intent of the change. Qodo is strong here because it frames code review as an agentic quality workflow, not just a bot that adds comments after the fact.

Key Features

• Agentic PR code review: Qodo emphasizes agentic review, rule execution, pre-PR checks, dashboarding, and Git plus IDE integrations.
• Rules system: Teams can encode review expectations so the tool checks against internal standards instead of generic advice only.
• Credit-based review planning: Qodo's pricing page maps plans to credits and approximate review volume, which helps teams estimate usage before rollout.
• Developer workflow coverage: Qodo fits teams that want review tied to IDE work, Git workflows, and engineering dashboards.

Pricing & Plans

Qodo lists a 14-day free trial with no credit card, then Pro Team starting at $30 with shared workspace credits and Enterprise on custom pricing. Qodo does not offer a permanent free tier for standard commercial teams, although qualified open-source projects can apply for free access. Usage is workspace-based rather than seat-based: reviews draw from a shared credit pool, unused credits expire each month, and overage continues at the same per-credit rate subject to a customer-set monthly cap. Buyers should model PR size and review frequency before rollout.

Pros & Cons

Pros: Qodo supports agentic PR review, no-limit rules, Git and IDE integrations, pre-PR review skills, dashboards, and strict data retention.

Cons: Qodo is more process-heavy than a lightweight PR bot. That is useful for teams with review rules, but smaller teams may not need the dashboard and governance layer immediately. Also verify exact Git provider support, credit consumption, and whether your team needs Qodo's broader coding features or only review.

Best For

Qodo fits engineering teams that want AI code review tied to rules, pre-PR feedback, and team quality workflows. Not the right fit if you only want a low-cost bot for occasional small pull requests.

Get started with Qodo

Greptile

The hardest PRs to review are not always the biggest ones. They are the changes where one small diff depends on patterns scattered across the repository. Greptile is built around that full-codebase context problem, with a code review bot that can use repository memory, GitHub or GitLab integration, self-hosting, and bring-your-own LLM options.

Key Features

• Full repository context: Greptile's main differentiator is context-aware review that looks beyond the visible diff.
• Self-hosting and BYO LLM: Security-sensitive teams can evaluate self-hosted deployment and custom model-provider options.
• Usage transparency: Greptile publicly states its code review pricing model, including included reviews and overage cost.
• Startup and open-source signals: Greptile offers free usage for qualified open-source projects and discounts for some startups.

Pricing & Plans

Greptile prices code reviews at $30 per active developer per month, with 50 completed reviews included per active developer and additional completed reviews at $1 each. An active developer is a PR author with at least one completed review in the billing period. Overages are per author rather than pooled across the team, and reviews can be triggered by opening a PR, manual review requests, or automatic reviews on new commits if enabled. Greptile also offers free usage for qualified non-commercial OSS projects and startup discounts for eligible early-stage startups.

Pros & Cons

Pros: Greptile is strong for full-repository context, GitHub and GitLab review, self-hosting, BYO LLM options, and transparent per-review pricing.

Cons: Greptile's value depends on whether full-repository context produces comments your reviewers trust. If developers see only generic suggestions, the $1-per-extra-review model can feel expensive. Teams should run a proof of concept on a representative monorepo and measure actionable comments per PR, not just "issues found."

Best For

Greptile is a strong fit for teams with complex repositories, security constraints, or self-hosting needs. Not the right fit if your PR volume is unpredictable and you cannot tolerate usage-based overages.

Get started with Greptile

Graphite

Some teams lose more time coordinating reviews than finding bugs. Stacked PRs, dependent branches, review assignment, and merge readiness all add overhead. Graphite approaches AI code review inside a broader code review workflow, which makes it especially relevant for GitHub teams already trying to speed up PR operations.

Key Features

• AI code review inside PR workflow: Graphite positions itself as an AI code review platform where teams ship higher quality code faster.
• Stacked PR support: Graphite's broader product is known for stacked changes, which is useful when review flow is as important as review comments.
• Developer workflow integrations: GitHub sync, CLI, and VS Code support make Graphite more than a single-purpose comment bot.
• Trial-first evaluation: Graphite promotes a free first 30 days without a credit card, making it easy to test fit before procurement.

Pricing & Plans

Graphite's public homepage highlights a 30-day free trial with no credit card, but detailed self-serve pricing is less visible than tools such as CodeRabbit, Greptile, Sourcery, Bito, or Codacy. Buyers should confirm exact Starter, Team, AI review, merge queue, stacked PR, automation, and enterprise security packaging before rollout. This is especially important because Graphite is valuable as a broader GitHub review workflow, not only as an AI comment bot.

Pros & Cons

Pros: Graphite combines AI review with stacked PRs, GitHub workflow improvements, CLI, VS Code support, merge queue, PR inbox, and developer metrics.

Cons: Graphite is most compelling if your team already wants its broader GitHub review workflow. If you only need a review bot, a more focused tool may be simpler. The other risk is workflow adoption: stacked PR discipline and Graphite habits need team buy-in, not just installation.

Best For

Graphite fits GitHub teams that want AI review plus a cleaner PR workflow. Not the right fit if your organization is split across Git providers or only needs a narrow review bot.

Get started with Graphite

GitHub Copilot Code Review

If your developers already live in GitHub and Copilot, adding another code review vendor may feel like unnecessary procurement. GitHub Copilot Code Review is attractive because it works where the PR already lives and connects to the broader Copilot ecosystem across GitHub, VS Code, Visual Studio, JetBrains, Xcode, and Azure DevOps public-preview workflows. Teams comparing Copilot with terminal-first coding agents should also review our Claude Code review before standardizing.

Key Features

• Native GitHub experience: Copilot can review code in GitHub workflows without forcing teams into another dashboard.
• IDE and platform coverage: Copilot's broader ecosystem spans major IDEs and GitHub surfaces, which lowers adoption friction.
• Agent and code review convergence: Review, chat, agent mode, CLI, and other Copilot features are increasingly packaged under the same usage model.
• Enterprise controls: Business and Enterprise plans support administrative controls that many organizations already use.

Pricing & Plans

GitHub Copilot uses plan pricing plus GitHub AI Credits. Copilot Free is limited, Copilot Pro is $10/month, Pro+ is $39/month, Max is $100/month, Business is $19 per granted seat/month, and Enterprise is $39 per granted seat/month. Since June 1, 2026, usage-based billing has replaced premium request units with AI Credits based on token usage. Copilot code review consumes GitHub AI Credits and also GitHub Actions minutes. Azure Repos support is in technical preview and bills through GitHub AI Credits rather than drawing from included Copilot plan credits.

Pros & Cons

Pros: GitHub Copilot Code Review is native to GitHub, available across the broader Copilot ecosystem, and now has an Azure Repos technical preview for Azure DevOps teams.

Cons: The main risk is cost opacity for heavy AI usage. A developer who uses chat, agent mode, code review, and cloud agents may burn through credits faster than expected. Copilot Code Review is also best inside GitHub; teams using GitLab or Bitbucket should look elsewhere.

Best For

GitHub Copilot Code Review fits GitHub-first teams already standardizing on Copilot. Not the right fit if your team needs predictable review-only pricing or first-class support across several Git providers.

Get started with GitHub Copilot Code Review

DeepSource

AI review is more useful when it knows which issues deterministic tools already caught. DeepSource combines static analysis, formatting, security, coverage, and AI review into a broader code quality platform. That makes it less of a pure "AI reviewer" and more of an engineering-quality control layer.

Key Features

• Hybrid static analysis and AI agents: DeepSource combines deterministic code analysis with AI-assisted review, which can reduce low-signal comments.
• Quality, security, complexity, and coverage: The platform covers more than PR comments, including security and maintainability signals.
• Multi-provider integration: DeepSource supports common Git workflows across GitHub, GitLab, Bitbucket, and Azure DevOps.
• Public pricing and trial: DeepSource lists a 14-day free trial and up to $50 in bundled AI Review credits.

Pricing & Plans

DeepSource lists Team at $24 per user/month billed yearly, while its docs describe Team as $30/month per contributor on monthly billing. Team includes unlimited repositories, unlimited pull request reviews, unlimited code formatting, and AI Review and Autofix credits. DeepSource currently lists $100 annual AI Review credit per user on Team, with Standard AI Review at $8 per 10K processed LOC and Advanced at $15 per 10K processed LOC. Enterprise is custom and adds self-hosted deployment, BYOK for AI Review, SSO, SLA-backed support, and a dedicated account manager.

Pros & Cons

Pros: DeepSource combines AI Review with static analysis, code formatting, security checks, coverage, monorepo support, audit logs, APIs, and enterprise deployment options.

Cons: DeepSource is broader than review-only tools. That is good if you want static analysis, formatting, security, coverage, and AI review together. It may be more than you need if your existing code quality stack already covers those areas. Teams should compare overlap with SonarQube, Semgrep, Codacy, Snyk, or in-house linting.

Best For

DeepSource fits teams that want AI code review as part of a broader code quality platform. Not the right fit if you want a lightweight reviewer with minimal process change.

Get started with DeepSource

Sourcery

Not every team needs an enterprise code quality platform. Some teams just need a reviewer that catches practical problems before merge without turning every PR into a governance process. Sourcery is appealing because it is focused, affordable, and available across GitHub, GitLab, and IDE workflows.

Key Features

• Automated code reviews: Sourcery reviews pull requests and provides summaries, high-level feedback, and line-by-line suggestions where relevant.
• Private repository support on paid plans: Sourcery's public docs describe public repository review on free tiers and private repository review on paid plans.
• IDE access: Developers can use Sourcery before opening a PR, which helps catch issues before review bottlenecks.
• Straightforward pricing: Sourcery documentation lists $15 monthly or $12 annual pricing for paid code review access.

Pricing & Plans

Sourcery lists three code review and security tiers: Free, Pro, and Team. Free is designed for open-source projects and supports public repositories only. Pro is $15 per developer/month or $12 annually and adds full code reviews for public and private projects plus limited security reviews. Team is $30 per developer/month or $24 annually and adds in-depth code reviews, security reviews, and repo analytics. Annual subscriptions receive a 20% discount.

Pros & Cons

Pros: Sourcery is comparatively affordable, supports public and private repo review on Pro, offers GitHub/GitLab and IDE workflows, and has a simple Free/Pro/Team structure.

Cons: Sourcery's smaller scope is a feature and a constraint. It is easier to adopt, but it is not trying to be a full engineering intelligence platform. Large organizations should validate admin controls, reporting, policy enforcement, and security requirements before rolling it out widely.

Best For

Sourcery fits small and mid-sized teams that want affordable AI code review without heavy procurement. Not the right fit if you need enterprise governance or deep security workflow coverage.

Get started with Sourcery

Bito AI Code Review Agent

Teams often want AI review in two places: before the developer opens a PR and after the code reaches the shared Git workflow. Bito's AI Code Review Agent covers both sides by positioning itself for on-demand, context-aware reviews in GitHub, GitLab, Bitbucket, and IDE workflows.

Key Features

• Context-aware reviews: Bito emphasizes full codebase context, pull request review, and suggestions that can use surrounding project information.
• Git and IDE coverage: It supports GitHub, GitLab, Bitbucket, and IDE workflows, which helps teams catch issues earlier than final PR review.
• Team and enterprise packaging: Bito offers Free, Team, Professional, and Enterprise plans, with paid plans built around developer and team usage.
• Self-hosting signal: Bito materials reference self-hosted options for teams with stricter code-security needs.

Pricing & Plans

Bito separates AI Architect pricing from AI Code Reviews pricing. For AI Code Reviews, Team is $15 per seat/month or $12 annually, Professional is $25 per seat/month or $20 annually, and Enterprise is custom. Team and Professional include 5K lines reviewed per seat/month, with $5 per additional 1K lines after that. Professional includes a 14-day free trial with no credit card and adds custom review guidelines, auto-learning from feedback, Jira and Confluence integrations, CI/CD pipeline reviews, and optional self-hosting as a $5/seat/month add-on.

Pros & Cons

Pros: Bito supports AI code reviews in Git, IDE, and CLI workflows, provides codebase-aware feedback, one-click fixes, analytics, and optional self-hosting on higher plans.

Cons: Bito has a clear product story, but public third-party feedback for the review agent is thinner than for GitHub Copilot, CodeRabbit, or established code quality platforms. Treat the trial as a necessary proof point. Measure whether comments catch meaningful defects or mostly restate style rules.

Best For

Bito fits teams that want review both inside Git workflows and earlier in IDE workflows. Not the right fit if your procurement process requires extensive public benchmark data before trial.

Get started with Bito AI Code Review Agent

Codacy AI Reviewer

AI reviewers can be noisy when they operate without deterministic context. Codacy's angle is different: combine rule-based static analysis with context-aware reasoning, then use that hybrid layer to catch security issues, test gaps, complexity concerns, and logic mismatches that human reviewers or scanners may miss.

Key Features

• Hybrid review engine: Codacy combines deterministic code analysis with AI reasoning, which can make review comments more grounded.
• Security and test coverage focus: Codacy AI Reviewer covers security vulnerabilities, intelligent remediation, test coverage, and code quality.
• PR metadata and business intent: Codacy documentation describes using PR metadata and surrounding context to check whether implementation matches intent.
• Trial-first evaluation: Codacy offers a 14-day full-access trial without a credit card, then paid plans for private repositories.

Pricing & Plans

Codacy lists Developer as a free IDE-focused plan, Team starting at $18 per developer/month billed yearly or $21 monthly, and Business as custom pricing. Team supports GitHub, Bitbucket, and GitLab integration, up to 100 private repos, unlimited LOC, AI Reviewer and merge gates for pull requests, coverage reports, malicious package detection, Jira, and Slack. Codacy also offers a 14-day free trial with no credit card, while open-source projects can use Codacy free of charge.

Pros & Cons

Pros: Codacy combines code quality, security scans, AI Reviewer, merge gates, coverage policies, malicious package detection, and GitHub/Bitbucket/GitLab integrations.

Cons: Codacy is a broader code quality and security platform, not a pure AI reviewer. That can be a benefit, but teams already invested in another static analysis platform should check overlap. The other concern is pricing clarity: the trial is easy, but production cost should be confirmed before rollout.

Best For

Codacy AI Reviewer fits teams that want deterministic analysis plus AI reasoning in one code quality workflow. Not the right fit if you need the simplest review-only price comparison.

Get started with Codacy AI Reviewer

CodeAnt AI

AI-generated code often fails in places traditional review queues do not prioritize: secrets, insecure patterns, missing tests, unchecked user input, or subtle quality regressions. CodeAnt AI approaches code review from a code quality and security angle, combining AI code review, SAST, code security, code quality, developer analytics, IDE integration, and CLI workflows.

Key Features

• Full-codebase pull request review: CodeAnt describes reviewing every pull request with full codebase context, not just the diff.
• Security plus quality coverage: It combines AI code review with SAST, quality gates, code security, developer metrics, and offensive security products.
• Multi-platform workflow: CodeAnt supports GitHub, GitLab, Bitbucket, Azure DevOps signals, IDE integration, and CLI usage.
• Trial and marketplace routes: CodeAnt advertises a 14-day free trial and appears in AWS, Microsoft, and developer marketplaces.

Pricing & Plans

CodeAnt AI lists a 14-day Free trial with 100 PR reviews, AI Code Review dashboards, Static Analysis and SAST, all premium features unlocked, and unlimited seats during the trial. Its Premium plan is $24 per user/month and includes unlimited PR reviews, AI Code Review dashboards, Static Analysis and SAST on pull requests, Jira and Azure Boards integrations, CI/CD code review integration, dedicated Slack support, white-glove onboarding, audit reports, and Scan Center dashboards. Enterprise is custom and adds custom contracting, SSO and audit logs, on-prem or VPC deployment, dedicated success support, and dedicated staff engineer support.

Pros & Cons

Pros: CodeAnt AI combines AI PR review, SAST, code quality dashboards, CI/CD review integration, Jira/Azure Boards integrations, and enterprise deployment options.

Cons: CodeAnt AI's breadth is both useful and potentially confusing. If your organization wants one platform for code review, quality, security, and pentesting, it deserves a trial. If you only need PR comments, a narrower product may be easier to configure and evaluate.

Best For

CodeAnt AI fits security-conscious engineering teams that want review, code quality, and AppSec signals in one workflow. Not the right fit if you want a minimal AI reviewer with fixed pricing and no broader platform scope.

Get started with CodeAnt AI

Best AI Code Review Tools by Use Case

For teams that need a dedicated PR reviewer fast

If your immediate problem is slow pull request turnaround, start with CodeRabbit, Qodo, or Sourcery. CodeRabbit gives the clearest review-first experience across Git providers. Qodo adds rules, pre-PR checks, and dashboards for teams that want review process control. Sourcery is the lower-cost option when you need practical review coverage without enterprise overhead.

For large repositories and context-heavy reviews

If your reviewers keep saying "this change depends on code outside the diff," prioritize Greptile, Bito, or CodeAnt AI. Greptile is strongest for full-repository context and self-hosting options. Bito is useful when you want context-aware review both in Git and IDE workflows. CodeAnt AI is attractive if context-aware review must also connect to security and quality gates.

For GitHub-native engineering organizations

If your organization already pays for GitHub Copilot, test GitHub Copilot Code Review before adding another vendor. The workflow advantage is obvious: review happens where the PR already lives. Graphite is also a strong GitHub-native option if your team wants better stacked PR workflow and AI review together.

For code quality and security teams

If the buyer is AppSec, platform engineering, or code quality rather than a pure developer productivity team, shortlist DeepSource, Codacy AI Reviewer, and CodeAnt AI. These tools make more sense when AI review is part of a broader quality gate, static analysis, coverage, or security posture program. For runtime, model, and agent protection beyond code review, compare them with our best AI security tools shortlist.

For cost-sensitive teams

Sourcery is the easiest low-cost shortlist candidate. CodeRabbit gives predictable per-seat pricing but costs more. Greptile is transparent but has overage risk. GitHub Copilot may be cost-effective if you already need Copilot broadly, but teams should monitor AI Credits carefully after the 2026 usage-based billing changes.

How to Choose the Right AI Code Review Tools

1. Decide what the reviewer is allowed to do. Some teams want AI comments only. Others want blocking quality gates, autofix, SAST checks, or pre-PR review. Define this before comparing vendors.

2. Map your Git workflow. GitHub-only teams can consider Copilot and Graphite. Multi-provider teams should prioritize CodeRabbit, Greptile, Bito, DeepSource, Sourcery, Codacy, or CodeAnt AI.

3. Run a proof of concept on real pull requests. Use at least 20 historical PRs across small fixes, large refactors, generated code, security-sensitive changes, and test updates. Track actionable comments, false positives, and reviewer time saved.

4. Model review volume, not seat count only. Greptile charges after included reviews. Copilot uses AI Credits. Qodo uses credits. Even fixed-seat tools need limits checked. Your busiest repositories determine cost, not your average developer.

5. Check security posture early. If code cannot leave your environment, prioritize self-hosting, no-code-storage claims, data retention controls, and enterprise agreements. Greptile, Bito, and some enterprise plans deserve closer review here.

6. Keep human ownership clear. AI code review tools should accelerate reviewers, not become silent merge authorities. Require humans to own architecture, product logic, data privacy, and high-risk security decisions.

Frequently Asked Questions