Built a dashboard with Trae?
We'll make it production-ready.
Dashboards aggregate and display your most important business data — revenue metrics, user analytics, operational KPIs. They need to load fast, display accurate numbers, and restrict access to authorized users. AI tools build visually impressive charts quickly, but the underlying data queries are often slow, insecure, or return incorrect aggregations.
Dashboard challenges in Trae apps
Building a dashboard with Trae is a great start — but these challenges need attention before launch.
Query performance at scale
AI-generated dashboards run raw database queries on every page load. With thousands of rows, these queries take seconds or minutes instead of milliseconds. You need materialized views, pre-aggregated data, proper indexing, and caching to keep dashboards responsive.
Data accuracy
A dashboard that shows wrong numbers is worse than no dashboard at all. AI tools generate SQL aggregations that look correct but miss edge cases — timezone handling, duplicate records, null values, and off-by-one errors in date ranges produce silently incorrect metrics.
Access control and data exposure
Dashboards display sensitive business data. AI tools often skip role-based access, meaning anyone with the URL can see revenue figures, customer data, or operational metrics. Different team members need different data visibility levels.
Real-time vs. cached data
Some metrics need to be live (active users, system status), while others can be cached (monthly revenue, historical trends). AI tools either make everything real-time (slow, expensive) or everything static (stale). You need a thoughtful caching strategy.
Chart and visualization bugs
AI-generated charts often have subtle issues — wrong axis scales, misleading truncated Y-axes, color schemes that are indistinguishable for colorblind users, and tooltips that show raw data instead of formatted values. These issues erode trust in the data.
Filter and drill-down interactions
Users need to filter by date range, segment, region, or other dimensions and drill into the details behind any number. AI tools build static charts but not the interactive filtering and drill-down that makes dashboards actually useful for decision-making.
Export and reporting
Stakeholders need to export data to CSV, generate PDF reports, or schedule automated email summaries. AI tools rarely implement data export, and when they do, the output format often breaks in Excel or includes raw technical field names.
What we check in your Trae dashboard
Common Trae issues we fix
Beyond dashboard-specific issues, these are Trae patterns we commonly fix.
Chinese-language comments and variable names in generated code
Trae occasionally generates inline comments or even variable names in Chinese, particularly for UI-related code, which creates readability issues for teams that operate in English and can complicate code review.
Missing authentication on generated API routes and backend endpoints
Like many AI code generators, Trae creates backend routes without authentication middleware, leaving all endpoints publicly accessible. This is a critical issue for any app handling user data.
Inconsistent coding style across components in the same project
Trae may switch between different state management patterns (useState vs. Pinia vs. Vuex), component styles, or file organization conventions across files in the same generation session, requiring normalization before merging.
Error handling in generated code is immature compared to more established tools
As a newer tool, Trae's error handling patterns are less consistent than Cursor or Copilot — generated code often omits catch blocks on async operations and lacks UI feedback for error states.
Start with a self-serve audit
Get a professional review of your Trae dashboard 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 dashboard with Trae?
Trae is a great starting point for a dashboard. It handles the initial scaffolding well, but dashboards have specific requirements — query performance at scale and data accuracy — that need professional attention before launch.
What issues does Trae leave in dashboards?
Common issues include: chinese-language comments and variable names in generated code, missing authentication on generated api routes and backend endpoints, inconsistent coding style across components in the same project. For a dashboard specifically, these issues are compounded by the need for query performance at scale.
How do I make my Trae dashboard production-ready?
Start with our code audit ($19) to get a clear picture of what needs fixing. For most Trae-built dashboards, 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 Trae-built dashboard?
Our code audit is $19 and gives you a complete report of issues. Fixes start at $199 with our Fix & Ship plan. For larger dashboard projects, we provide a custom fixed quote after the audit — no hourly billing.
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