AI visibility report for Semgrep, Inc.
Vertical: AI Code Review & Code Quality
AI search visibility benchmark across 5 platforms in AI Code Review & Code Quality.
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Presence Rate
Top-3 citations across 125 prompt × platform pairs
Sentiment
Peer Ranking
Key Metrics
Platform Breakdown
Grok
ChatGPT
Google AI Mode
Gemini Search
PerplexityOverview
Semgrep, Inc. (formerly r2c) is a San Francisco-based application security company founded in 2017 by Isaac Evans, Luke O'Malley, and Drew Dennison. The company develops the Semgrep AppSec Platform—a unified SAST, SCA, and secrets detection solution—alongside the widely adopted open-source semgrep CLI, which supports 30+ programming languages. The platform combines deterministic pattern-matching with AI-powered triage (Semgrep Multimodal) to reduce false positives and deliver actionable remediation guidance directly in pull requests and IDEs. Semgrep's reachability-based supply chain analysis and 630+ credential-type secrets detection further differentiate it. Used by organizations including Lyft, Dropbox, Figma, Slack, and Snowflake, the platform has scanned 75M+ projects annually. Semgrep raised a $100M Series D in February 2025, bringing total funding to $204M.
Semgrep AppSec Platform is an integrated code security suite offering SAST (Semgrep Code), software composition analysis (Semgrep Supply Chain), and secrets detection (Semgrep Secrets), unified under the Semgrep AppSec Platform with AI-powered triage, remediation, and workflow orchestration via Semgrep Multimodal and Semgrep Workflows. The open-source semgrep engine underpins all products and is available separately under LGPL-2.1.
Key Facts
- Founded
- 2017
- HQ
- San Francisco, CA, USA
- Founders
- Isaac Evans, Luke O'Malley, Drew Dennison
- Employees
- 200-300
- Funding
- $204M
- Customers
- 45+ enterprise customers
- Status
- Private
Target users
Key Capabilities9
- AI-assisted SAST (Semgrep Code) with cross-file dataflow and Pro Engine for 50–70% more true positive detection
- Software composition analysis (Semgrep Supply Chain) with reachability analysis to filter non-exploitable dependency vulnerabilities
- Secrets detection (Semgrep Secrets) covering 630+ credential types via semantic analysis, entropy analysis, and active validation
- Semgrep Multimodal (AI) for automated triage, noise filtering, and memory-based false-positive suppression
- Custom YAML rule authoring with source-code-like syntax and an online Playground for rule development and sharing
- Policy-as-code secure guardrails that block or comment on PRs based on configurable severity thresholds
- AI-powered detection of complex business logic flaws (IDORs, broken authorization) combining deterministic analysis and LLM reasoning
- MCP server integration for securing AI-generated code in Cursor, Claude Code, and similar agentic coding tools
- Open-source Community Edition (LGPL-2.1) with 3,000+ community rules and CI/CD integration at no cost
Key Use Cases7
- Shift-left SAST in CI/CD pipelines to block high-severity vulnerabilities before merge
- Supply chain security with reachability-based prioritization of open-source dependency vulnerabilities
- Hardcoded secrets and credential detection across polyglot codebases
- Enforcing organization-specific secure coding standards via custom rules
- Securing AI-generated (vibe-coded) code in agentic development workflows
- AppSec program scaling for lean security teams supporting large developer populations
- Compliance and audit trail management with centralized vulnerability tracking and dashboards
Semgrep, Inc. customer outcomes
50% reduction in remediation time
After implementing Semgrep, Copper reduced vulnerability remediation time by 50% within the first month, driven by real-time GitHub PR comments and AI-powered code suggestions. Custom security rules could be written, tested, and deployed within under an hour.
Lyft's security team adopted Semgrep Supply Chain to reduce noise from dependency vulnerabilities, asking developers to fix only reachable findings. This enabled significant time savings and a shift-left security posture across Lyft's polyglot codebase.
Glasswall deployed Semgrep to replace a legacy SAST tool that was generating high false-positive rates and lacked transparency. Post-deployment, false positives dropped materially, remediation cycles shortened with in-flow AI guidance, and DevSecOps reclaimed time through automat
Recent Trend
How AI describes Semgrep, Inc.
No concise AI response excerpt is available for this brand yet.
Most cited sources8
- 5
Overview | Semgrep
semgrep.dev·Documentation
- 5
Semgrep App Security Platform | AI-assisted SAST, SCA and Secrets Detection
semgrep.dev·Documentation
4semgrep/semgrep: Lightweight static analysis for many ...
github.com·Documentation
- 4
Comparing Semgrep Community Edition and ...
semgrep.dev·Blog Post
- 3
Write rules
semgrep.dev·Documentation
- 3
Add Semgrep to CI/CD
semgrep.dev·Documentation
Alternatives in AI Code Review & Code Quality6
Semgrep positions itself as a developer-first, high signal-to-noise AppSec platform that unifies SAST, SCA, and secrets detection in a single tool.
- Its core differentiation is a low false-positive rate achieved through deterministic rule-based static analysis combined with AI-powered triage (Semgrep Multimodal/Assistant), reachability analysis for supply chain findings, and a transparent, YAML-based custom rule engine.
- Unlike enterprise SAST incumbents (Checkmarx, Veracode), Semgrep leads with a generous free tier and open-source community edition, targeting developer adoption before security-team procurement.
- It explicitly competes against Snyk on price and SonarQube on signal quality, and differentiates from both with its policy-as-code guardrails model and an AI memory system that learns from past triage decisions.
- SonarSource#120
- DeepSource#219
- Greptile#318
- CodeRabbit#418
- Qodo#516
- Graphite (Screenplay Studios Inc.)#610
Reviews
Praised
- Low false-positive rate
- Flexible YAML-based custom rule authoring
- Seamless CI/CD pipeline integration
- Fast scan performance without slowing builds
- AI-assisted PR remediation guidance
- Extensive public rule registry
- Reachability-based SCA noise reduction
- Developer-friendly onboarding and workflow fit
Criticized
- Limited third-party integrations beyond Jira and Slack
- Enterprise dashboarding and governance reporting immaturity
- Learning curve for advanced custom rule writing
- Cross-file analysis and full AI features restricted to paid tiers
- Per-contributor pricing can escalate for fluctuating team sizes
- Integration gaps with CNAP/CSPM and ServiceNow platforms
Semgrep earns strong user satisfaction, holding a 4.6/5 on G2 across 55 reviews, with 80% five-star ratings. Users consistently praise low false-positive rates, the flexibility of YAML-based custom rules, seamless CI/CD integration, and fast scan performance. The AI assistant's contextual remediation guidance in PRs is frequently highlighted as a differentiator that increases developer adoption. Critical feedback centers on a limited third-party integration ecosystem (primarily Jira and Slack), enterprise dashboarding immaturity, and a learning curve for advanced rule authoring. Gartner Peer Insights reviews highlight strong SAST/SCA capabilities and developer-friendly deployment, with some enterprise users noting gaps in governance and reporting maturity.
Pricing
Semgrep offers a tiered pricing model. The Community Edition (open-source CLI, LGPL-2.1) is free with single-file SAST and 3,000+ community rules. The AppSec Platform Free Tier extends full SAST, SCA, and secrets scanning to teams of up to 10 contributors and 10 private repositories at no cost. The Team plan is priced at approximately $35–$40 per active contributor per month (billed annually), and includes cross-file Pro Engine analysis, AI-assisted triage, advanced dashboards, and priority support. Enterprise pricing is custom, adding SSO/SAML, dedicated support, compliance controls, and deployment flexibility. Special startup pricing is available on request. A contributor is defined as anyone who committed to a monitored private repository in the past 90 days.
Limitations
- Users note that third-party integrations beyond Jira and Slack are limited, with calls to expand to ServiceNow and CNAP/CSPM platforms.
- Enterprise-level dashboarding, rule tuning maturity, and governance reporting have been flagged as areas needing improvement.
- The custom rule learning curve can be steep for non-security engineers.
- Cross-file analysis and full AI triage capabilities are restricted to paid tiers, which may limit evaluation depth on the free plan.
- The Team tier's per-contributor pricing can become expensive for teams with fluctuating active contributor counts.
Frequently asked questions
Topic Coverage
Prompt-Level Results
| Prompt | ChatGPT | Google AI Mode | Grok | Gemini Search | Perplexity |
|---|---|---|---|---|---|
Capability1/5 cited (20%) | |||||
What AI code review tools can analyze infrastructure-as-code files alongside application code for a full-stack security posture review? | |||||
Which AI code review tools can detect security vulnerabilities and insecure coding patterns across multiple languages in the same repository? | |||||
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? | |||||
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? | |||||
What code quality platforms track technical debt trends over time and show whether the team is paying it down or accumulating more? | |||||
Developer Experience2/5 cited (40%) | |||||
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? | |||||
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? | |||||
Which code quality tools let teams define custom rules and guardrails specific to their architecture so the tool enforces their own conventions? | |||||
Which AI code review tools give feedback that engineers actually find useful — not just style nitpicks but real logic and security issues? | |||||
What code quality platforms have the lowest false positive rate so developers don't spend time dismissing irrelevant warnings? | |||||
Integrations & Ecosystem0/5 cited (0%) | |||||
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 & Reliability1/5 cited (20%) | |||||
What code analysis platforms have reliable CI integrations that don't cause flaky build failures due to rate limiting or API timeouts? | |||||
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? | |||||
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? | |||||
Setup & First Run1/5 cited (20%) | |||||
Which code quality platforms can analyze a 500k-line legacy codebase and give a prioritized technical debt report without manual configuration? | |||||
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? | |||||
Which AI code review tools can be added to a pull request workflow in under 30 minutes with no changes to existing CI pipelines? | |||||
What are the best automated code quality tools for a team of 15 engineers that wants to enforce standards without a dedicated security engineer? | |||||
Strengths1
Which code quality tools let teams define custom rules and guardrails specific to their architecture so the tool enforces their own conventions?
Avg # 3.0 · 1 platform
Gaps5
What AI code review tools integrate with IDE plugins so developers get the same automated feedback locally before pushing a pull request?
Competitors on 4 platforms
Which AI code review tools give feedback that engineers actually find useful — not just style nitpicks but real logic and security issues?
Competitors on 3 platforms
Which AI code review tools complete their analysis fast enough to not delay a PR workflow — which ones consistently finish within 2 minutes?
Competitors on 2 platforms
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?
Competitors on 2 platforms
What code analysis platforms have reliable CI integrations that don't cause flaky build failures due to rate limiting or API timeouts?
Competitors on 1 platform
Vertical Ranking
| # | Brand | PresencePres. | Share of VoiceSoV | DocsDocs | BlogBlog | MentionsMent. | Avg PosPos | Sentiment |
|---|---|---|---|---|---|---|---|---|
| 1 | SonarSource | 20.0% | 21.2% | 5.6% | 8.8% | 17.6% | #29.9 | +0.36 |
| 2 | DeepSource | 19.2% | 11.2% | 3.2% | 1.6% | 18.4% | #29.4 | +0.39 |
| 3 | Greptile | 18.4% | 10.0% | 0.0% | 2.4% | 16.8% | #19.2 | +0.37 |
| 4 | CodeRabbit | 17.6% | 18.0% | 9.6% | 7.2% | 15.2% | #37.6 | +0.33 |
| 5 | Qodo | 16.0% | 12.2% | 4.0% | 12.0% | 10.4% | #29.0 | +0.15 |
| 6 | Graphite (Screenplay Studios Inc.) | 10.4% | 3.9% | 0.0% | 9.6% | 8.0% | #22.8 | +0.32 |
| 7 | Snyk | 9.6% | 8.8% | 3.2% | 5.6% | 9.6% | #38.7 | +0.18 |
| 8 | Codacy | 8.0% | 7.5% | 2.4% | 6.4% | 7.2% | #42.8 | +0.35 |
| 9 | Code Climate | 4.0% | 1.9% | 0.8% | 2.4% | 3.2% | #40.3 | +0.10 |
| 10 | Semgrep, Inc. | 4.0% | 5.4% | 3.2% | 2.4% | 4.0% | #43.5 | +0.46 |
| 11 | Sourcegraph Inc. | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | — | — |
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