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AI visibility report

AI visibility report for JetBrains in IDEs & Code Editors.

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

Cursor is cited on 5 of those losses.

25 prompts
6 platforms
Updated Aug 17, 2026 - refreshed weekly
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JetBrains appears in 2 other verticals

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4percent
Presence Rate
Low presence

Still absent from 96% of tracked prompt responses

Top-3 citations across 150 prompt × platform pairs

+0.58
Sentiment
-1.00.0+1.0
Very positive
No clearrank

Peer Ranking

#1#11
No clear rankin IDEs & Code Editors

Key Metrics

Presence Rate4.0%
Share of Voice12.4%
Avg Position#5.4
Docs Presence2.0%
Blog Presence2.0%
Brand Mentions28.7%

Platform Breakdown

ChatGPT
12%3/25 prompts
Bing Copilot
8%2/25 prompts
Perplexity
4%1/25 prompts
Google AI Mode
0%0/25 prompts
Gemini Search
0%0/25 prompts
Grok
0%0/25 prompts

How to read this. JetBrains appears in 4% of tracked prompt responses. Presence is absolute coverage; share of voice is relative citation share; sentiment measures tone only when the brand appears.

Where JetBrains is losing

Prompts where competitors are visible and JetBrains is not.

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

Where JetBrains is winning2

  • What AI code editors handle indexing and search best for very large repositories with millions of lines of code?

    Avg # 2.0 · 1 platform

  • Which AI coding assistants have the best compatibility with existing language servers and IDE extensions teams already rely on?

    Avg # 2.0 · 1 platform

Where JetBrains is losing5

  • Which browser-based IDEs handle compiled languages like Rust, Go, or C++ best compared to a local setup?

    Competitors on 2 platforms

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  • Which browser-based code editors handle first-time setup best for full-stack projects with multiple services running in parallel?

    Competitors on 2 platforms

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  • Which AI coding assistants degrade most gracefully when their backend model service has an outage — does the editor still work?

    Competitors on 2 platforms

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  • What tools are best for standardizing the development environment across a team of 20 engineers on different machines?

    Competitors on 2 platforms

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  • Which cloud IDEs handle large TypeScript monorepos well — with solid type checking and IntelliSense at scale?

    Competitors on 2 platforms

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

Overview

JetBrains, founded in 2000 and headquartered in Amsterdam, is a bootstrapped private software company developing professional tools for software developers and teams. Its portfolio includes 12+ language-specific IDEs—IntelliJ IDEA (Java/Kotlin), PyCharm (Python), WebStorm (JavaScript/TypeScript), Rider (.NET), CLion (C/C++), GoLand (Go), and others—alongside team tools including the TeamCity CI/CD server, YouTrack issue tracker, and Qodana code quality platform. JetBrains created the Kotlin programming language, Google's preferred language for Android development. In 2025, it launched Junie, an autonomous AI coding agent, and released Mellum, an open-source 4B-parameter LLM for code completion. The company reports 11.4 million recurring active users, counts 88 of the Fortune Global Top 100 among customers, and generates approximately $252 million in annual revenue with no external funding.

JetBrains offers a broad ecosystem of language-specific professional IDEs built on the IntelliJ platform, complemented by CI/CD (TeamCity), issue tracking (YouTrack), code quality (Qodana), and AI-assisted development tools (AI Assistant, Junie agent, Mellum LLM). The company also created and maintains the Kotlin programming language and Kotlin Multiplatform. Products are available individually or bundled in the All Products Pack subscription.

Key Facts

Founded
2000
HQ
Amsterdam, Netherlands
Founders
Sergey Dmitriev, Valentin Kipyatkov, Eugene Belyaev
Employees
2000-3000
Customers
11.4M recurring active users; 88 of Fort
Status
Private

Target users

Professional Java, Kotlin, and JVM developersPython developers and data scientistsWeb and full-stack JavaScript/TypeScript engineersEnterprise software engineering teams (mid-market to Fortune 500).NET developers and Unity game developersDevOps engineers and platform engineering teams

Key Capabilities10

  • Language-specific IDEs for Java, Kotlin, Python, JavaScript/TypeScript, Go, PHP, Rust, Ruby, C/C++, and .NET
  • Deep code intelligence: smart completion, static analysis, and safe refactoring
  • AI-powered coding with AI Assistant (inline), Junie autonomous agent, and open-source Mellum 4B LLM
  • Integrated debugging, profiling, and testing tools built into every IDE
  • Native VCS integration (Git, GitHub, GitLab, SVN, Mercurial, Perforce)
  • 8,860-plugin Marketplace ecosystem for extensibility
  • TeamCity CI/CD server for continuous integration and delivery
  • Qodana code quality platform with 60+ language support and CI pipeline integration
  • Remote and cloud development via JetBrains Gateway and Google Cloud Workstations integration
  • Kotlin Multiplatform for shared code across Android, iOS, desktop, web, and server

Key Use Cases8

  • Professional Java and JVM language development (IntelliJ IDEA)
  • Python development and data science workflows (PyCharm, DataSpell)
  • Web, JavaScript, and TypeScript development (WebStorm)
  • Android app development (IntelliJ IDEA, co-developed Android Studio)
  • .NET and Unity game development (Rider)
  • CI/CD pipeline management and DevOps automation (TeamCity)
  • Code quality assurance and automated gate enforcement (Qodana)
  • Enterprise-scale multi-language development teams (All Products Pack)

Recent Trend

Visibility+2.4 pts
Avg position+0.78
Sentiment-0.05

How AI describes JetBrains3

Other editors with notable ecosystems include JetBrains IDEs for JVM-heavy teams, and editors like Zed and Neovim for specialized workflows, but they trail VS Code in ecosystem size and breadth.

What code editors have the strongest extension ecosystems for engineering teams to evaluate when switching tools?

perplexityDirect JetBrains mention
VS Code and JetBrains remote development extensions on remote workspaces are commonly recommended for low latency.

Which cloud development environments have the lowest latency editing experience compared to a local IDE setup?

perplexityDirect JetBrains mention
Direct answer: GitHub Copilot and Cursor offer the closest alignment with common IDEs and language servers teams already rely on, with broad editor compatibility including VS Code, JetBrains, Vim/Neovim, and terminal workflows.

Which AI coding assistants have the best compatibility with existing language servers and IDE extensions teams already rely on?

perplexityDirect JetBrains mention

Alternatives in IDEs & Code Editors6

JetBrains positions as the premium, language-specialized IDE vendor for professional and enterprise developers, competing on depth of code intelligence, refactoring tooling, framework support, and a purpose-built IDE per language.

  • It differentiates from free, general-purpose editors like VS Code through deeper language-specific integration, IntelliJ's 25-year platform lineage, and enterprise reliability.
  • Against emerging AI-native IDEs (Cursor, Windsurf), JetBrains leverages its 11.4 million-strong user base and is countering with native AI capabilities—AI Assistant, the Junie autonomous coding agent (GA April 2025), and the open-source Mellum LLM—embedded into its proven IDE environments.
  • Its bootstrapped, profitable model and absence of VC pressure allow long-term platform investment.
  • Primary competitive pressure stems from the VS Code/GitHub Copilot free stack and AI-first IDEs targeting developers who prefer AI-centric workflows over traditional IDE depth.
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Reviews

Praised

  • Intelligent code completion and context-aware suggestions
  • Deep refactoring tools that feel safe to use
  • Seamless Git and VCS integration
  • Strong Spring/Spring Boot and framework support
  • Reliable debugging and error detection
  • Extensive plugin ecosystem
  • AI Assistant integrates naturally into IDE workflow
  • Consistent reliability across long careers

Criticized

  • High memory and CPU resource consumption
  • Slow startup times and indexing delays on large codebases
  • Steep learning curve for new users
  • Expensive pricing, especially for individuals and small teams
  • 2025 commercial license changes eliminated continuity discounts for new buyers
  • Some products discontinued (Fleet, Aqua, Writerside, AppCode)
  • Slow performance with many plugins active
  • AI add-on pricing considered high on top of IDE subscription

JetBrains holds strong ratings across major review platforms—4.5 stars on both G2 (4,989 reviews) and Gartner Peer Insights (~700 IDE Software reviews)—and was named a Gartner Customers' Choice for IDE Software in 2024. Users consistently praise the depth of code intelligence, reliable debugging, seamless Git integration, and language-specific framework support (especially Spring/Boot for Java). The AI Assistant receives positive marks for in-IDE context awareness. Common criticisms center on high resource consumption (RAM/CPU), steep learning curves for new users, and pricing—particularly the 2025 commercial license changes that eliminated continuity discounts for new buyers.

Pricing

JetBrains uses a per-user subscription model with annual and monthly billing. Individual IDE licenses (e.g., IntelliJ IDEA Ultimate) start at approximately $199/user/year following an October 2025 price increase of 10–18%. The All Products Pack (bundling all IDEs and tools) is $299/user/year for individuals and $979/user/year for commercial organizations. List prices for single commercial IDE subscriptions range from $89–$249/user/year in year one. Monthly billing carries a ~20% annual premium. Subscriptions include perpetual fallback licenses after 12 consecutive months. Commercial licenses purchased before January 2, 2025 retain continuity (loyalty) discounts in years two and three; new commercial licenses purchased after that date do not. Free tiers are available for students, educators, open-source contributors, and startups; IntelliJ IDEA's community features are free for all use cases following a December 2025 unified distribution model.

Limitations

  • IDEs are widely reported as resource-intensive, requiring significant RAM and CPU—commonly causing slowdowns on machines with less than 16GB RAM and on large codebases.
  • Startup times and indexing delays are frequently cited criticisms.
  • Subscription pricing is considered expensive relative to free alternatives, especially after the October 2025 price increase (10–18% for individual licenses; All Products Pack commercial rising to $979/user/year).
  • New commercial licenses purchased after January 2, 2025 no longer qualify for continuity (loyalty) discounts, a significant policy change for scaling teams.
  • Several products have been discontinued (Fleet IDE, Aqua test automation IDE, Writerside, AppCode), raising concerns about product longevity.
  • The TeamCity CI/CD server was linked to the 2020–2021 SolarWinds supply chain security incident, though JetBrains denied involvement.
  • Managing multiple projects within a single window can be challenging in some IDEs.

Frequently asked questions

Topic coverageCoverage by buyer topic

Topic Coverage

Capability0/5DevEx0/5Integrations &Ecosystem2/5Performance &Reliability2/5Setup & First Run1/5

Prompt-Level Results

Brand citedCompetitor citedNot cited
PromptChatGPTBing CopilotPerplexityGoogle AI ModeGemini SearchGrok
Capability0/5 cited (0%)

Which browser-based IDEs handle compiled languages like Rust, Go, or C++ best compared to a local setup?

Which AI coding assistants are best at avoiding insecure code suggestions in security-sensitive codebases?

Which AI coding assistants handle multi-file refactoring well, not just single-file completions?

What cloud-based development environments are viable for teams building iOS or Android native apps?

What AI-powered editors offer the best debugging assistance — actually diagnosing runtime errors, not just generating code?

Developer Experience0/5 cited (0%)

Which cloud development environments have the lowest latency editing experience compared to a local IDE setup?

What AI-powered code completion tools have the most evidence behind their productivity impact — any with real study data?

Which cloud IDEs handle large TypeScript monorepos well — with solid type checking and IntelliSense at scale?

What are the most common complaints developers have about AI code editors after daily use — which tools address them best?

Which AI coding assistants are best at understanding full codebase context rather than just completing the current file?

Integrations & Ecosystem2/5 cited (40%)

Which cloud IDEs connect to private git repos and internal package registries without complex network configuration?

What code editors have the strongest extension ecosystems for engineering teams to evaluate when switching tools?

Which AI coding assistants handle code that calls undocumented internal APIs and services most effectively?

What AI coding tools integrate best with internal documentation, wikis, and architecture decision records as context?

Which AI coding assistants have the best compatibility with existing language servers and IDE extensions teams already rely on?

Performance & Reliability2/5 cited (40%)

What AI code editors handle indexing and search best for very large repositories with millions of lines of code?

What cloud IDEs have the best session persistence and work recovery when the underlying compute goes away mid-session?

Which AI code completion tools are the most lightweight in terms of laptop battery and memory impact?

Which AI coding assistants degrade most gracefully when their backend model service has an outage — does the editor still work?

Which remote development environments perform best on slow or unreliable internet connections?

Setup & First Run1/5 cited (20%)

Which AI coding assistants let you configure coding conventions and restrict unwanted suggestion patterns for your team?

Which browser-based code editors handle first-time setup best for full-stack projects with multiple services running in parallel?

What tools are best for standardizing the development environment across a team of 20 engineers on different machines?

What cloud-based IDEs are fastest for onboarding a new developer onto a large existing codebase compared to local setup?

I'm evaluating AI coding assistants for my team — what should a structured pilot look like to get a fair comparison?

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Vertical Ranking

#BrandPres.SoVDocsBlogMent.PosSentiment
1GitHub Copilot14.0%31.4%4.7%2.0%0.0%#5.0+0.44
2VS Code6.7%13.3%5.3%0.0%0.0%#4.6+0.29
3Cursor6.0%14.3%0.0%1.3%0.0%#3.8+0.37
4Gitpod4.0%7.6%4.0%0.0%20.0%#4.4+0.72
5JetBrains4.0%12.4%2.0%2.0%28.7%#5.4+0.58
6StackBlitz2.7%7.6%2.0%0.7%10.7%#4.1+0.63
7Windsurf2.0%4.8%2.0%0.0%21.3%#6.8+0.50
8Zed2.0%6.7%1.3%0.7%0.0%#7.4+0.33
9Replit0.7%1.0%0.0%0.0%10.7%#3.0+0.80
10Tabnine0.7%1.0%0.7%0.0%7.3%#9.0+0.00
11CodeSandbox0.0%0.0%0.0%0.0%3.3%

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