AI visibility report
Sourcegraph ranks #5 in AI Code Review & Code Quality AI search.
Outside the top three on 11 of the 25 prompts buyers actually ask.
Greptile is cited on 5 of those losses.
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Start free trial#5 among 11 vendors · still absent from 91.3% of tracked prompt responses
Top-3 citations across 150 prompt × platform pairs
Peer Ranking
Key Metrics
Platform Breakdown
Gemini Search
Google AI Mode
Bing Copilot
ChatGPT
Perplexity
GrokVisible, but narrative can improve. Sourcegraph ranks #5 on presence but #9 on sentiment. The brand appears relatively often, but competitors may be getting more favorable language when they appear.
Where Sourcegraph is losing
Prompts where competitors are visible and Sourcegraph is not.
These prompt-level losses are the first prompts to track and repair.
Where Sourcegraph is winning5
What AI code review tools have the smoothest version control platform integration so reviews appear inline on diffs automatically on every PR?
Avg # 1.0 · 1 platform
What AI code review tools integrate with IDE plugins so developers get the same automated feedback locally before pushing a pull request?
Avg # 1.0 · 1 platform
What code quality platforms scale to thousands of PRs per day without degrading analysis quality or response time?
Avg # 1.5 · 2 platforms
What code analysis platforms have reliable CI integrations that don't cause flaky build failures due to rate limiting or API timeouts?
Avg # 2.0 · 1 platform
Which AI code review tools complete their analysis fast enough to not delay a PR workflow — which ones consistently finish within 2 minutes?
Avg # 2.0 · 1 platform
Where Sourcegraph is losing5
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?
Competitors on 2 platforms
Track this promptWhich AI code review tools can detect security vulnerabilities and insecure coding patterns across multiple languages in the same repository?
Competitors on 2 platforms
Track this promptWhat AI code review tools can analyze infrastructure-as-code files alongside application code for a full-stack security posture review?
Competitors on 2 platforms
Track this promptI'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 2 platforms
Track this promptWhich AI review tools handle very large pull requests with 500+ changed files without timing out or producing incomplete feedback?
Competitors on 2 platforms
Track this prompt
Track Sourcegraph daily before the next report refresh.
Track these gapsResearch dossierCapabilities, use cases, sources, reviews, pricing, and FAQ
Overview
Sourcegraph Inc. is a San Francisco-based developer tools company founded in 2013 by Quinn Slack and Beyang Liu. It offers a code intelligence platform built around a proprietary SCIP-powered semantic code graph that indexes large, complex enterprise codebases across all repositories and code hosts. Its core products include Code Search (cross-repository exact and structural search), Cody (an AI coding assistant with full-codebase context), Batch Changes (automated large-scale code edits), Code Insights (engineering metrics tracking), and Amp (an agentic AI coding tool). The platform serves 200+ enterprise engineering teams and has indexed more than 54 billion lines of code. Customers include Palo Alto Networks, Stripe, Reddit, Coinbase, and Dropbox. Sourcegraph is backed by Andreessen Horowitz and Sequoia Capital with $223M in total funding.
Sourcegraph is an enterprise code intelligence platform that semantically indexes entire codebases—across every repository, code host, and language—to give developers and AI agents complete, accurate context. Its platform includes Code Search for exact and structural queries, Cody for context-aware AI coding assistance, Batch Changes for automating cross-repository code modifications at scale, Code Insights for tracking engineering trends, and an MCP server that exposes the code graph to external AI agents. Targeting large engineering organizations managing 'Big Code,' Sourcegraph emphasizes whole-codebase comprehension, enterprise security, and agentic AI interoperability.
Key Facts
- Founded
- 2013
- HQ
- San Francisco, CA, USA
- Founders
- Quinn Slack, Beyang Liu
- Employees
- 150-250
- Funding
- $223M
- ARR
- ~$50M
- Customers
- 200+ enterprise engineering teams
- Valuation
- $2.625B (July 2021)
- Status
- Private
Target users
Key Capabilities10
- SCIP-powered semantic code graph indexing across all repositories
- Cross-repository exact, regex, and structural code search
- Deep Search: natural-language agentic search with cited answers
- Cody AI coding assistant with full codebase context (chat, autocomplete, inline edits)
- Batch Changes: automated large-scale code changes across 100s of repositories
- Code Insights: historical trend tracking for migrations, adoption, and risk
- Code Monitoring: real-time alerts on code pattern changes
- MCP server exposing code graph to external AI agents
- LLM flexibility: supports Anthropic Claude, OpenAI GPT, Google Gemini, and bring-your-own-LLM
- Enterprise security: single-tenant cloud, zero data retention, RBAC, SSO
Key Use Cases8
- Cross-repository vulnerability search and remediation (e.g., Log4j, CVE patching)
- Large-scale codebase migrations and dependency updates via Batch Changes
- Developer onboarding and code comprehension in complex monorepos
- Providing full codebase context to AI coding agents via MCP
- Tracking engineering initiatives and code health metrics over time
- Security compliance reviews and code pattern enforcement
- Monolith-to-microservices refactoring across distributed repositories
- Agentic coding workflows requiring accurate, repo-wide context retrieval
Sourcegraph customer outcomes
80% reduction in time for large-scale code changes
Workiva's Client Platform Team replaced their internal tooling with Sourcegraph Batch Changes to propagate dependency updates across 70+ repositories. The switch eliminated ongoing maintenance burden and dramatically accelerated large-scale code change cycles.
4 days to full Log4j remediation across all repositories
Nutanix used Sourcegraph to identify every instance of the Log4j vulnerability across a sprawling multi-repo codebase with 100% confidence, and delivered customer patches within four days of the vulnerability's disclosure.
Up to 40% productivity improvement for 2,000 developers
Palo Alto Networks deployed Sourcegraph with AWS and Anthropic to boost developer productivity for 2,000 engineers while maintaining enterprise-grade security controls.
Recent Trend
How AI describes Sourcegraph3
Sourcegraph * CI Mechanics: It does not rely on sending your code to a remote cloud to be analyzed mid-build.
What code analysis platforms have reliable CI integrations that don't cause flaky build failures due to rate limiting or API timeouts?
Sourcegraph \+ 1 * The Architecture Pivot: It handles the low-level noise so completely that humans only need to jump in for architectural reviews.
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?
Sourcegraph \+ 1 * The Catch: Because it digs so deep, it can be slower and pricier than surface-level diff reviewers.
Which AI code review tools give feedback that engineers actually find useful — not just style nitpicks but real logic and security issues?
Most cited sources1
Alternatives in AI Code Review & Code Quality6
Sourcegraph positions itself as the enterprise-grade 'Big Code' intelligence platform—differentiating on whole-codebase context (SCIP-powered code graph), cross-repository search depth, and AI agent interoperability (MCP server) rather than individual developer autocomplete.
- Its primary pitch is that AI agents and developers operating without full codebase context miss critical cross-cutting changes; Sourcegraph supplies that context layer.
- Unlike point-solution AI code review tools (CodeRabbit, Qodo) or static-analysis-first tools (SonarSource, Semgrep), Sourcegraph leads with search and comprehension before quality enforcement, targeting teams managing millions of lines of code across hundreds of repositories.
Reviews
Praised
- Deep full-codebase context awareness
- Flexibility to choose and switch LLM models
- Non-intrusive IDE integration
- Powerful cross-repository code search
- Rapid product updates tracking latest LLMs
- Strong enterprise security and compliance controls
- Effective for large monorepo navigation and onboarding
- Prompt Library for reusable team workflows
Criticized
- Struggles with complex multi-step or multi-dependency logic
- Frequent strategy pivots and product discontinuations
- Cody Free/Pro removal reduces accessibility for small teams
- Occasional AI hallucinations requiring human validation
- Source code closed in 2024, removing open-source option
- Cost-prohibitive for startups or individual developers
- Integration with third-party tools still maturing
Sourcegraph's AI assistant (reviewed under Cody and now Amp on G2) holds a 4.5/5 rating from 91 reviews. Users consistently praise the deep codebase context awareness that distinguishes it from generic autocomplete tools, flexibility to choose among multiple LLMs, and the non-intrusive IDE plugin experience. The platform is particularly valued by teams managing large monorepos or complex multi-repository architectures. Criticisms center on struggles with complex multi-step logic, occasional AI hallucinations, and a perception that the product is overkill or cost-prohibitive for smaller teams. Employee and customer reviews also reflect concern over frequent strategic pivots—including the Cody-to-Amp transition and discontinuation of self-serve plans.
Pricing
Sourcegraph currently offers a single publicly listed plan: Enterprise Search at $49/user/month (single-tenant cloud), which includes Deep Search, Code Search, Batch Changes, Code Insights, Code Navigation, and Code Monitoring with 24×5 support. Cody Enterprise (AI coding assistant) is separately priced at $59/user/month and includes all enterprise security and LLM flexibility features. Cody Free, Cody Pro, and Enterprise Starter plans were discontinued effective July 23, 2025. The Amp agentic coding tool operates on a credit-based pricing model. Custom enterprise contracts are available via sales.
Limitations
- Sourcegraph closed its source code in 2024 (repository made private), removing the open-source option for self-hosted deployments.
- Cody Free and Pro plans were discontinued in July 2025, leaving only Cody Enterprise and the new Amp agent—reducing accessibility for small teams and individual developers.
- The Enterprise Search plan starts at $49/user/month, making it cost-prohibitive for startups or small engineering organizations.
- Reviewers note the AI assistant (Cody/Amp) can struggle with complex multi-step logic and long dependency chains, and occasional hallucinations require careful human validation.
- The company has undergone multiple product strategy pivots (Cody rebranding to Amp, Cody Free/Pro discontinuation), which has created customer uncertainty and internal churn according to employee reviews.
Frequently asked questions
Topic coverageCoverage by buyer topic
Topic Coverage
Prompt-Level Results
| Prompt | Google AI Mode | Bing Copilot | Perplexity | ChatGPT | Gemini Search | Grok |
|---|---|---|---|---|---|---|
Capability2/5 cited (40%) | ||||||
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 code review tools can detect security vulnerabilities and insecure coding patterns across multiple languages in the same repository? | ||||||
What AI code review tools can analyze infrastructure-as-code files alongside application code for a full-stack security posture review? | ||||||
What code quality platforms track technical debt trends over time and show whether the team is paying it down or accumulating more? | ||||||
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? | ||||||
Developer Experience3/5 cited (60%) | ||||||
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 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 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 & Ecosystem1/5 cited (20%) | ||||||
What code review tools work across both cloud-hosted and on-premises version control systems for teams with a hybrid repository strategy? | ||||||
Which AI PR review platforms support self-hosted deployments that keep code on-premises and don't send source code to third-party models? | ||||||
Which code quality platforms integrate with issue trackers to automatically create tickets for critical issues found during code review? | ||||||
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? | ||||||
What AI code review tools integrate with IDE plugins so developers get the same automated feedback locally before pushing a pull request? | ||||||
Performance & Reliability3/5 cited (60%) | ||||||
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? | ||||||
Which AI review tools handle very large pull requests with 500+ changed files without timing out or producing incomplete feedback? | ||||||
What code quality platforms scale to thousands of PRs per day without degrading analysis quality or response time? | ||||||
Setup & First Run2/5 cited (40%) | ||||||
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? | ||||||
Turn this matrix into daily prompt monitoring.
Track prompt changesVertical Ranking
| # | Brand | PresencePres. | Share of VoiceSoV | DocsDocs | BlogBlog | MentionsMent. | Avg PosPos | Sentiment |
|---|---|---|---|---|---|---|---|---|
| 1 | Qodo | 14.0% | 18.3% | 0.7% | 8.0% | 12.7% | #8.9 | +0.42 |
| 2 | CodeRabbit | 11.3% | 13.1% | 4.0% | 1.3% | 9.3% | #9.1 | +0.39 |
| 3 | SonarSource | 10.7% | 14.7% | 1.3% | 1.3% | 8.7% | #8.3 | +0.39 |
| 4 | Greptile | 10.0% | 11.5% | 0.0% | 0.0% | 8.7% | #7.8 | +0.49 |
| 5 | Sourcegraph | 8.7% | 8.4% | 0.0% | 8.7% | 8.7% | #3.8 | +0.38 |
| 6 | Graphite | 8.0% | 8.9% | 0.0% | 7.3% | 6.0% | #6.6 | +0.47 |
| 7 | Snyk | 6.7% | 7.9% | 0.7% | 0.0% | 6.0% | #10.9 | +0.40 |
| 8 | DeepSource | 4.7% | 4.7% | 0.0% | 0.7% | 4.0% | #7.9 | +0.36 |
| 9 | Codacy | 4.0% | 6.3% | 0.7% | 0.7% | 4.0% | #8.7 | +0.10 |
| 10 | Semgrep | 3.3% | 3.1% | 0.7% | 0.0% | 3.3% | #18.5 | +0.48 |
| 11 | Code Climate | 1.3% | 3.1% | 0.0% | 0.7% | 0.7% | #6.7 | +0.45 |
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