Built a marketplace with JetBrains AI?
We'll make it production-ready.
Marketplaces are among the hardest apps to build well because they serve two distinct user types (buyers and sellers) with different needs, handle money flowing between users, and require trust systems. AI tools can scaffold the UI quickly, but the critical backend logic — escrow, disputes, ratings, and split payments — needs careful implementation.
Marketplace challenges in JetBrains AI apps
Building a marketplace with JetBrains AI is a great start — but these challenges need attention before launch.
Payment splitting and payouts
Buyers pay, the platform takes a cut, sellers receive the rest. This requires Stripe Connect or similar — significantly more complex than basic checkout. AI tools rarely implement this correctly, leaving you with manual payout processes.
Two-sided authorization
Sellers can manage their listings but not other sellers'. Buyers can view listings but only manage their own orders. Admins can moderate everything. Three distinct permission levels, all enforced server-side.
Trust and safety
Reviews, ratings, dispute resolution, content moderation, and fraud detection. These are complex systems that AI tools don't generate but that make or break a marketplace.
Search and discovery
Users need to find what they're looking for. Basic database queries won't cut it at scale — you need full-text search, filters, sorting, and potentially geolocation. This requires proper indexing or a dedicated search service.
Real-time communication
Buyers and sellers need to communicate. In-app messaging, notifications, and order status updates require real-time capabilities that AI tools often implement superficially.
Data integrity
Inventory counts, order statuses, payment states, and user balances must be consistent. Race conditions (two buyers purchasing the last item simultaneously) require careful database design.
What we check in your JetBrains AI marketplace
Common JetBrains AI issues we fix
Beyond marketplace-specific issues, these are JetBrains AI patterns we commonly fix.
Over-engineered enterprise patterns generated for simple startup use cases
JetBrains AI is trained on enterprise Java and Kotlin patterns, so it tends to generate verbose factory patterns, abstract base classes, and interface hierarchies for problems that could be solved with a simple function in a startup context.
Generated Spring Boot code includes unnecessary security exposure in default configurations
Spring Boot applications generated by JetBrains AI may include actuator endpoints, management ports, or H2 console access enabled in configurations that should be disabled or secured before production deployment.
Verbose boilerplate code increases bundle size and maintenance overhead
Java code generation in particular produces verbose getter/setter patterns, checked exception hierarchies, and XML configuration that modern Kotlin or Lombok-based approaches would handle with a fraction of the code.
Generated unit tests use JUnit 4 patterns in projects that have moved to JUnit 5
JetBrains AI sometimes generates JUnit 4 annotations (@Test from org.junit, @Before, @After) in projects configured for JUnit 5, causing compilation errors and requiring annotation migration.
Start with a self-serve audit
Get a professional review of your JetBrains AI marketplace at a fixed price.
External Security Scan
Black-box review of your public-facing app. No code access needed.
- OWASP Top 10 vulnerability check
- SSL/TLS configuration analysis
- Security header assessment
- Expert review within 24h
Code Audit
In-depth review of your source code for security, quality, and best practices.
- Security vulnerability analysis
- Code quality review
- Dependency audit
- Architecture review
- Expert + AI code analysis
Complete Bundle
Both scans in one package with cross-referenced findings.
- Everything in both products
- Cross-referenced findings
- Unified action plan
100% credited toward any paid service. Start with an audit, then let us fix what we find.
Frequently asked questions
Can I build a marketplace with JetBrains AI?
JetBrains AI is a great starting point for a marketplace. It handles the initial scaffolding well, but marketplace apps have specific requirements — payment splitting and payouts and two-sided authorization — that need professional attention before launch.
What issues does JetBrains AI leave in marketplace apps?
Common issues include: over-engineered enterprise patterns generated for simple startup use cases, generated spring boot code includes unnecessary security exposure in default configurations, verbose boilerplate code increases bundle size and maintenance overhead. For a marketplace specifically, these issues are compounded by the need for payment splitting and payouts.
How do I make my JetBrains AI marketplace production-ready?
Start with our code audit ($19) to get a clear picture of what needs fixing. For most JetBrains AI-built marketplace apps, the critical path is: security review, then fixing core flow reliability, then deployment. We provide a fixed quote after the audit.
How much does it cost to fix a JetBrains AI-built marketplace?
Our code audit is $19 and gives you a complete report of issues. Fixes start at $199 with our Fix & Ship plan. For larger marketplace projects, we provide a custom fixed quote after the audit — no hourly billing.
Get your JetBrains AI marketplace production-ready
Tell us about your project. We'll respond within 24 hours with a clear plan and fixed quote.