Stop guessing at code quality from resumes. We run automated security scans, performance analysis, and pattern detection on their GitHub repos. Browse verified portfolios with Lighthouse scores. Interview smarter, not longer.
Multiple currencies, tax forms, compliance headaches. Glopay handles it all in one platform.
We're not claiming magic AI that perfectly judges developers. We run real static analysis tools, security scanners, and performance audits. The code tells the story - we just organize it so you can quickly spot quality signals.
Automated scanning catches security mistakes junior developers make
Identifies developers who care about speed, not just features
Objective quality indicators reduce subjective guesswork
Reveals how they think about organizing code at scale
Here's what our automated analysis actually looks like. Specific, actionable findings - not vague AI summaries.
Found `const API_KEY = 'sk-abc123...'` in src/utils/api.ts line 4
Impact: Immediate red flag - shows lack of security awareness
348KB bundle size, no dynamic imports detected. All routes loaded upfront.
Impact: User experience suffers - worth discussing optimization approach
Jest tests for components, edge cases handled, error scenarios tested
Impact: Strong positive indicator - developer thinks about reliability
tsconfig.json with strict: true, no any types, proper interfaces
Impact: Indicates attention to type safety and maintainability
Similar API call patterns repeated in 8 components without abstraction
Impact: Suggests early-career or needs mentorship on DRY principles
Deployed site loads in 1.2s, optimized images, good Core Web Vitals
Impact: Proves they care about user experience, not just building features
Every finding links to the specific file and line number. Nothing vague like "good code quality" - concrete issues you can discuss in interviews or verify yourself. ESLint rules, security scanners, and complexity calculators don't lie.
Think of this as intelligent pre-screening: we help you spend 30 minutes reviewing strong candidates instead of 3 hours with everyone who applied.
We don't claim to perfectly determine if someone is "senior" - that's subjective and context-dependent. But we can objectively identify patterns that correlate with experience level. You make the final judgment.
| Signal | Junior Pattern | Senior Pattern | Automatable |
|---|---|---|---|
| Test Coverage | No tests or only happy path | Edge cases covered, integration tests, E2E for critical flows | ✓ Yes |
| Error Handling | Uncaught promises, no loading/error states | Proper error boundaries, user-friendly messages, retry logic | ✓ Yes |
| Performance Awareness | No code splitting, large bundles, unnecessary re-renders | Dynamic imports, memoization, optimized images, web vitals monitoring | ✓ Yes |
| Security Practices | API keys in code, unsafe HTML rendering, no input validation | Environment variables, sanitized inputs, CSP headers, auth patterns | ✓ Yes |
| Code Organization | 500+ line components, duplicated logic, inconsistent structure | Reusable components, DRY principles, clear separation of concerns | ⚠ Partially |
| TypeScript Usage | any types everywhere or no TypeScript | Strict mode, proper typing, discriminated unions, type guards | ✓ Yes |
A developer with 90% test coverage, strict TypeScript, proper error handling, and optimized performance is likely more experienced than someone with none of those. But context matters - maybe they're junior on an excellent team, or senior but working on side projects. Our analysis gives you data points for better interview questions and faster screening decisions.
Without automated code analysis, you're either spending hours reviewing every repo manually or interviewing developers blindly.
""5 years React experience" could mean anything from expert to barely functional"
Automated Solution: Automated analysis reveals: TypeScript usage, test coverage, modern patterns, security awareness
"You can't read every candidate's GitHub - so you interview blindly and waste time"
Automated Solution: Pre-screening analysis flags quality issues and highlights strong candidates automatically
"Hardcoded secrets, unsafe HTML, missing validation - you won't spot these in interviews"
Automated Solution: Automated security scanning catches dangerous patterns before they join your team
"They say they optimize performance, but do they actually use code splitting, lazy loading, memoization?"
Automated Solution: Analyze deployed sites with Lighthouse, check for optimization patterns in code
We run ESLint, security scanners, duplicate code detection, and complexity analysis on every repository. Objective metrics you can trust.
Our analysis identifies modern vs outdated patterns, common anti-patterns, and architectural decisions worth discussing in interviews.
We run Lighthouse audits on live sites, verify they actually work, and measure real-world performance. Not just code - actual user experience.
We analyze commit patterns, code-to-bug ratios, and technical decision quality. Strong signals for seniority, but you make the final call.
We don't just check if they've built e-commerce sites - we verify how they built them. Payment integration quality, cart state management, responsive product grids.
Product grids, checkout flows, shopping cart experiences with payment integration
We check: Payment library usage, cart state management, responsive product grids
Data visualization, complex forms, admin panels, and analytics interfaces
We check: Chart library integration, form validation, table performance
Marketing sites with conversion-focused design and smooth scroll interactions
We check: Lighthouse scores, animation libraries, SEO optimization
Responsive web applications optimized for mobile touch interactions
We check: Touch event handling, PWA setup, mobile performance metrics
Read resumes claiming 'clean code' - schedule interviews hoping it's true
See actual ESLint results, code duplication %, TypeScript strictness before first call
Discover security issues after hiring (hardcoded keys, XSS vulnerabilities)
Automated security scanning flags dangerous patterns in their public repos
Ask hypothetical questions about performance optimization
See Lighthouse scores on their deployed sites + check for code splitting in repos
Wonder if they write tests or just claim to
View actual test coverage, see edge cases they considered, evaluate test quality
Guess if they're mid-level or senior based on years of experience
Review seniority indicators: error handling, security awareness, architecture decisions
Hope their portfolio links still work
Verified deployed projects with automated uptime checks and working demos
We don't replace interviews. Automated analysis catches red flags and highlights strengths, but you still need to assess problem-solving, communication, and culture fit.
We can't judge architectural decisions without context. Maybe they didn't write tests because it's a prototype. Maybe the "bad" pattern was a team standard. Our analysis raises questions, not conclusions.
We can't guarantee side projects reflect work quality. Their personal repos might be experiments or old code. But patterns across multiple projects are meaningful signals.
What we DO promise: Objective technical analysis that saves you hours of manual screening. You interview fewer people, but the ones you talk to have cleared basic quality bars. Better hiring decisions, faster.
We analyze deployed projects with automated Lighthouse audits for performance, accessibility, and SEO. You can test their live sites yourself - check responsiveness on your phone, evaluate visual design, test interactions. We provide the technical metrics, you judge the aesthetic quality.
Absolutely. Every frontend developer profile includes links to live deployed projects, GitHub repositories with demo links, and portfolio websites. You can interact with their actual work - test responsiveness, check loading performance, and evaluate design quality firsthand.
We run ESLint analysis, check for security issues (hardcoded secrets, unsafe HTML), detect code duplication, verify TypeScript usage and strictness, analyze bundle sizes, check for modern patterns like dynamic imports and code splitting, and flag outdated dependencies or framework patterns.
We don't claim to perfectly assess seniority - that requires human judgment. But we provide strong indicators: test coverage, error handling patterns, performance optimization evidence, security awareness, code organization quality, commit patterns, and ratio of features to rewrites. These signals help you focus interviews on the right candidates.
We verify they've used the framework in real projects, analyze their component patterns, check for modern vs outdated approaches (hooks vs classes, composition API vs options), detect common anti-patterns, and measure code quality. The code is there for you to review - we just organize it so you can quickly assess whether it's worth your time.
Partially. We can objectively flag problems: security issues, performance red flags, duplicated code, missing tests, unsafe patterns. We can't judge architectural decisions without context - but we surface patterns worth discussing. Think of it as intelligent filtering: we help you spend time on candidates who clear basic quality bars.
Post your job description. We'll match you with frontend developers whose code has been analyzed for security, performance, and quality. Browse their verified portfolios with Lighthouse scores. Interview with confidence.
18+ automated checks • Security scans • Lighthouse audits • No subscription fees