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AI visibility report

AI visibility report for Greptile in AI Code Review & Code Quality.

Outside the top three on 14 of the 25 prompts buyers actually ask.

CodeRabbit is cited on 7 of those losses.

25 prompts
6 platforms
Updated Aug 16, 2026 - refreshed weekly
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16percent
Presence Rate
Low presence

Still absent from 84% of tracked prompt responses

Top-3 citations across 150 prompt × platform pairs

+0.36
Sentiment
-1.00.0+1.0
Positive
No clearrank

Peer Ranking

#1#11
No clear rankin AI Code Review & Code Quality

Key Metrics

Presence Rate16.0%
Share of Voice18.3%
Avg Position#4.6
Docs Presence1.3%
Blog Presence0.0%
Brand Mentions24.0%

Platform Breakdown

Perplexity
44%11/25 prompts
ChatGPT
24%6/25 prompts
Gemini Search
16%4/25 prompts
Google AI Mode
12%3/25 prompts
Bing Copilot
0%0/25 prompts
Grok
0%0/25 prompts

How to read this. Greptile appears in 16% of tracked prompt responses. Presence is absolute coverage; share of voice is relative citation share; sentiment measures tone only when the brand appears.

Where Greptile is losing

Prompts where competitors are visible and Greptile is not.

These prompt-level losses are the first prompts to track and repair.

Where Greptile is winning4

  • What code quality platforms scale to thousands of PRs per day without degrading analysis quality or response time?

    Avg # 1.0 · 1 platform

  • What code quality platforms have the lowest false positive rate so developers don't spend time dismissing irrelevant warnings?

    Avg # 1.0 · 1 platform

  • Which AI review tools handle very large pull requests with 500+ changed files without timing out or producing incomplete feedback?

    Avg # 1.0 · 1 platform

  • Which AI PR review tools can summarize large diffs and give an overall assessment of a pull request rather than only commenting line by line?

    Avg # 2.0 · 2 platforms

Where Greptile is losing5

  • Which AI code review tools can detect security vulnerabilities and insecure coding patterns across multiple languages in the same repository?

    Competitors on 5 platforms

    Track this prompt
  • I'm evaluating AI pull request review tools for a Python and TypeScript codebase — which ones require the least configuration to get useful feedback from day one?

    Competitors on 3 platforms

    Track this prompt
  • What code analysis platforms have reliable CI integrations that don't cause flaky build failures due to rate limiting or API timeouts?

    Competitors on 2 platforms

    Track this prompt
  • What code review tools work across both cloud-hosted and on-premises version control systems for teams with a hybrid repository strategy?

    Competitors on 2 platforms

    Track this prompt
  • What code quality platforms track technical debt trends over time and show whether the team is paying it down or accumulating more?

    Competitors on 2 platforms

    Track this prompt

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Research dossierCapabilities, use cases, sources, reviews, pricing, and FAQ

Overview

Greptile is an AI code review agent built by Tabnam, Inc., founded in San Francisco in 2023 by Daksh Gupta, Soohoon Choi, and Vaishant Kameshwaran after completing Y Combinator's Winter 2024 cohort. Unlike traditional linters or diff-only reviewers, Greptile constructs a graph index of the entire repository—mapping every file, function, class, and dependency—then deploys a swarm of parallel AI agents to analyze each pull request in the context of the whole codebase. Reviews are posted as inline PR comments in approximately three minutes. The platform learns team preferences from PR reactions and comments over time, reducing noise while enforcing custom coding standards. It supports GitHub and GitLab, offers cloud SaaS and self-hosted (including air-gapped) deployment, and carries SOC 2 Type II certification. Over 9,000 teams are reported as users, including Brex, Zapier, PostHog, and Retool.

Greptile is an AI-native code review agent that integrates with GitHub and GitLab to automatically review every pull request using full codebase context. It builds a language-agnostic dependency graph of the entire repository, runs a swarm of parallel agents to assess cross-file impact, posts findings in ~3 minutes, and learns team coding standards over time to reduce noise and enforce custom rules. Enterprise and self-hosted deployments support air-gapped environments and bring-your-own-LLM configurations.

Key Facts

Founded
2023
HQ
San Francisco, CA
Founders
Daksh Gupta, Soohoon Choi, Vaishant Kameshwaran
Funding
$29.1M
Customers
9,000+ teams (self-reported)
Valuation
~$180M (Series A, 2025)
Status
Private

Target users

Software engineering teams at B2B SaaS and technology companiesCTOs and engineering managers overseeing large or legacy codebasesEnterprise engineering orgs in regulated industries (fintech, healthcare, defense)Teams with agentic coding workflows (Devin, Cursor, Claude Code) needing a validation layerYC-backed and high-growth startups scaling their engineering practiceOpen-source project maintainers (discounted access program)

Key Capabilities10

  • Full-codebase graph indexing (functions, classes, dependencies) vs. diff-only analysis
  • Automated PR review in ~3 minutes via parallel agent swarm
  • Multi-file and cross-repository bug and logic-error detection
  • Custom rules enforcement written in plain English
  • Learning system that adapts from team PR comments and emoji reactions over time
  • Mermaid sequence diagrams and confidence scores per PR
  • One-click 'Fix with Agent' routing to Claude Code, Cursor, Devin, Codex
  • MCP server for AI agent and IDE integration
  • TREX autonomous test generation for every PR (early access)
  • Self-hosted / air-gapped deployment with bring-your-own-LLM; SOC 2 Type II certified

Key Use Cases7

  • Automated pull request review for engineering teams on GitHub or GitLab
  • Bug and logic-error detection in large or legacy monorepos
  • Enforcing team coding standards and best practices at scale
  • Validation layer for AI-generated code from agents like Devin or Cursor
  • Security and edge-case detection (sandbox escapes, retry amplification, data leaks)
  • Enterprise code review with compliance requirements (air-gapped, SOC 2)
  • Reducing senior-engineer review burden on routine pull requests

Greptile customer outcomes

Brex

2,576 issues caught per month; 30% faster shipping

Greptile reviews 100% of code across Brex's 8-year-old monorepo with 400+ engineers. The CTO credited Greptile with outperforming all previously evaluated code review tools and enabling faster merges on straightforward changes while flagging high-risk ones.

Recent Trend

Visibility+0.8 pts
Avg position-1.04
Sentiment-0.03

How AI describes Greptile3

Greptile builds a graph index of the entire codebase (functions, files, and cross-service dependencies).

What AI code review tools can analyze infrastructure-as-code files alongside application code for a full-stack security posture review?

google-ai-modeDirect Greptile mention
Greptile * How it handles large PRs: Greptile approaches code review differently by maintaining a persistent graph index of the entire codebase.

Which AI code review tools complete their analysis fast enough to not delay a PR workflow — which ones consistently finish within 2 minutes?

google-ai-modeDirect Greptile mention
Greptile — Uniquely builds a comprehensive code graph by indexing the entire repository across multiple languages.

Which AI code review tools give feedback that engineers actually find useful — not just style nitpicks but real logic and security issues?

google-ai-modeDirect Greptile mention

Alternatives in AI Code Review & Code Quality6

Greptile differentiates on full-codebase graph context rather than diff-only analysis, positioning itself as the 'central validation layer' for all code changes—including AI-generated code.

  • At $30/seat/month it is priced higher than pure-play rivals such as CodeRabbit ($12–15/seat), but targets teams that need deeper, cross-file bug detection in large or legacy codebases.
  • Its bring-your-own-LLM self-hosting option and SOC 2 Type II compliance give it a foothold in regulated industries (fintech, healthcare, defense) that cannot send source code to third-party clouds.
  • The MCP server and one-click IDE fix integrations (Claude Code, Cursor, Devin, Codex) position Greptile as an orchestration hub rather than a standalone linter, competing with Sourcegraph on codebase intelligence and with CodeRabbit/Qodo on automated PR review.
View category comparison hub

Reviews

Praised

  • Full codebase context catches bugs diff-only tools miss
  • Senior-level, non-noisy review comments
  • Fast setup (5 minutes to first review)
  • Adapts to team standards over time
  • Useful for large and legacy monorepos
  • Mermaid diagrams and confidence scores aid triage
  • One-click fix integration with IDEs and coding agents

Criticized

  • Higher price point than alternatives like CodeRabbit
  • No free tier; discounts require eligibility review
  • Struggles with very large or poorly documented repos
  • Platform dependent on GitHub/GitLab; no Bitbucket support documented
  • Founder's publicized 'no work-life balance' culture drew scrutiny

No verified third-party review platform scores (e.g., G2, Gartner Peer Insights) with sufficient published reviews were found for Greptile as of the research date. Named customer testimonials on Greptile's own site are consistently positive, highlighting context-aware feedback quality and senior-level suggestions as standout attributes. Developer community discussion on Hacker News and Slashdot emphasizes Greptile's strength in understanding complex, multi-repo codebases and finding deeply buried issues via semantic search, though the demanding internal work culture has drawn public scrutiny.

Pricing

Cloud plan: $30/seat/month, with 50 code reviews included per seat and $1 per additional review. Unlimited repositories and users. Enterprise plan: custom pricing with self-hosting, SSO/SAML, custom DPA, dedicated Slack support, forward-deployed engineers, GitHub Enterprise support, and bring-your-own-LLM capability. Discounts are available for qualified open-source projects and pre-Series A startups. Annual and multi-year contract discounts available on request. Free trial offered; no credit card required to start.

Limitations

  • At $30/seat/month, Greptile is priced higher than direct competitors such as CodeRabbit ($12–15/seat).
  • There is no free tier; discounts require application (open-source projects, pre-Series A startups).
  • The platform is dependent entirely on GitHub and GitLab marketplaces for distribution, creating platform concentration risk.
  • Third-party reporting notes the tool can face challenges processing particularly large or poorly documented repositories.
  • Self-hosting requires enterprise contract negotiation and customer-managed infrastructure.
  • No Bitbucket or Azure DevOps integration is publicly documented.

Frequently asked questions

Topic coverageCoverage by buyer topic

Topic Coverage

Capability3/5DevEx4/5Integrations &Ecosystem2/5Performance &Reliability4/5Setup & First Run3/5

Prompt-Level Results

Brand citedCompetitor citedNot cited
PromptBing CopilotChatGPTGoogle AI ModeGemini SearchPerplexityGrok
Capability3/5 cited (60%)

What AI code review tools can analyze infrastructure-as-code files alongside application code for a full-stack security posture review?

Which AI PR review tools can summarize large diffs and give an overall assessment of a pull request rather than only commenting line by line?

I need a code quality tool that enforces quality gates in CI and blocks merges when coverage drops or critical issues are introduced — which platforms do this well?

What code quality platforms track technical debt trends over time and show whether the team is paying it down or accumulating more?

Which AI code review tools can detect security vulnerabilities and insecure coding patterns across multiple languages in the same repository?

Developer Experience4/5 cited (80%)

What AI code review platforms are popular with engineering leads who want to spend less time on repetitive PR feedback and more on architectural comments?

Which AI code review tools give feedback that engineers actually find useful — not just style nitpicks but real logic and security issues?

Looking for an AI PR review tool that learns from the codebase and past review decisions so feedback improves over time — what are my options?

What code quality platforms have the lowest false positive rate so developers don't spend time dismissing irrelevant warnings?

Which code quality tools let teams define custom rules and guardrails specific to their architecture so the tool enforces their own conventions?

Integrations & Ecosystem2/5 cited (40%)

What code review tools work across both cloud-hosted and on-premises version control systems for teams with a hybrid repository strategy?

Looking for a code quality tool that feeds results into a security dashboard for CISO-level reporting — which platforms have strong SIEM and security integrations?

Which code quality platforms integrate with issue trackers to automatically create tickets for critical issues found during code review?

Which AI PR review platforms support self-hosted deployments that keep code on-premises and don't send source code to third-party models?

What AI code review tools integrate with IDE plugins so developers get the same automated feedback locally before pushing a pull request?

Performance & Reliability4/5 cited (80%)

What code analysis platforms have reliable CI integrations that don't cause flaky build failures due to rate limiting or API timeouts?

What code quality platforms scale to thousands of PRs per day without degrading analysis quality or response time?

Which AI review tools handle very large pull requests with 500+ changed files without timing out or producing incomplete feedback?

Which AI code review tools complete their analysis fast enough to not delay a PR workflow — which ones consistently finish within 2 minutes?

Which AI code review tools maintain consistent review quality across a polyglot repository with Go, Python, and TypeScript services?

Setup & First Run3/5 cited (60%)

Which code quality platforms can analyze a 500k-line legacy codebase and give a prioritized technical debt report without manual configuration?

Which AI code review tools can be added to a pull request workflow in under 30 minutes with no changes to existing CI pipelines?

I'm evaluating AI pull request review tools for a Python and TypeScript codebase — which ones require the least configuration to get useful feedback from day one?

What AI code review tools have the smoothest version control platform integration so reviews appear inline on diffs automatically on every PR?

What are the best automated code quality tools for a team of 15 engineers that wants to enforce standards without a dedicated security engineer?

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Vertical Ranking

#BrandPres.SoVDocsBlogMent.PosSentiment
1Sourcegraph16.0%16.8%0.0%16.0%0.0%#4.2+0.20
2Greptile16.0%18.3%1.3%0.0%24.0%#4.6+0.36
3Qodo14.7%16.2%3.3%9.3%35.3%#5.3+0.46
4CodeRabbit11.3%14.1%6.7%0.7%40.0%#3.3+0.56
5SonarSource10.0%13.6%4.0%1.3%8.0%#3.2+0.43
6DeepSource5.3%5.2%0.0%0.0%14.0%#3.8+0.45
7Snyk5.3%5.2%2.0%0.7%22.0%#4.5+0.51
8Semgrep4.0%6.3%0.0%1.3%0.0%#5.5+0.75
9Codacy1.3%2.6%0.7%0.7%13.3%#3.0+0.35
10Code Climate1.3%1.0%0.0%0.0%4.0%#4.5+0.60
11Graphite0.7%0.5%0.0%0.7%0.0%#2.0+0.00

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