LakBud/Applera
Live in productionAn AI-powered job application platform that streamlines the job search process with automated CV parsing, application generation, and interview preparation.
AI-powered job application platform. Upload your CV, paste a job listing, and get a tailored cover letter, match score, and application email in seconds.
- TypeScript97.3%
- CSS1.5%
- HTML0.8%
- Dockerfile0.3%
- JavaScript0.1%
1 Review
Applera is a well-structured full-stack job application platform with a practical user flow. It turns a CV and job listing into a match analysis, tailored cover letter, email draft, CV advice, and interview preparation materials. The pnpm and Turborepo setup keeps the React client, Express API, and shared Zod schemas organized without duplicating contracts. The backend shows careful engineering around sensitive career data. Protected database queries include user ownership checks, PDFs use authenticated Cloudinary storage, Clerk webhooks receive signature verification, and AI routes include quotas, timeouts, rate limits, idempotency controls, and request validation. Helmet, restricted CORS, CSRF handling, file magic-byte checks, MongoDB sanitization, masked audit logs, and signed guest identifiers provide useful layers of protection. The privacy policy also clearly identifies Groq, Clerk, Cloudinary, MongoDB, Redis, and Cloudflare as data processors instead of presenting the AI workflow as entirely private.
The biggest improvement area is automated verification. The repository defines unit, integration, and coverage scripts for both applications, but there appear to be no files matching the configured .int.test patterns and little or no frontend component coverage. Because the scripts use --passWithNoTests, CI can report success even when a test category is empty. Existing tests focus mainly on small server utilities rather than authentication, ownership enforcement, file uploads, Clerk account deletion, AI quota refunds, Cloudinary cleanup, or the complete CV-to-application flow. Adding API integration tests with MongoDB Memory Server, frontend workflow tests with MSW, and at least one end-to-end browser test would protect the product’s most important promises. CI currently runs linting, type checking, and tests, but it should also build both production applications and enforce coverage thresholds. Documentation needs a small licensing correction too. The repository contains LICENSE.md, while the README and in-app terms link to LICENSE, producing broken links. Overall, Applera is a thoughtful and security-aware application with more production detail than most portfolio projects. Broader tests and tighter CI would make its reliability match the strength of its architecture.
