Cursor accelerates development — but AI-generated code often skips auth hardening, error handling, and edge cases. We audit and test Cursor-built apps before you point real users and payments at them.
Cursor codebase specialists · Auth & security audit · Production hardening
30 minutes · Senior engineer · No commitment
Where Cursor-generated code commonly needs hardening.
Login, signup, password reset, JWT handling, and session persistence — common Cursor weak points.
Row-level security policies tested for every table — prevent data leaks between users.
Generated endpoints tested for malformed input, missing auth, and server error responses.
Scan for hardcoded API keys, exposed .env values, and client-side secret leaks.
End-to-end workflows tested beyond the happy path Cursor optimizes for.
Senior engineer review of Cursor-generated diffs — architecture, dependencies, and tech debt assessment.
When to bring QA into your Cursor workflow.
Cursor prototype works in demo — audit before real users, payments, and data.
Cursor sprint shipped features — regression and edge case testing before deploy.
Cursor-built demo tested end-to-end — no live failures in the pitch room.
Cursor connected Supabase — RLS policies and auth flows validated before data goes live.
Teams searching for ai app testing usually hit these walls before finding reliable coverage.
AI tools ship fast but skip auth hardening, RLS policies, and input validation.
Generated code implements UI that doesn't connect to real backend logic.
API keys and database credentials commonly hardcoded in AI-generated scaffolds.
Zero automated tests means every change is a regression risk.
150+ products shipped · AI-app specialists · US/UK/AU clients with timezone overlap.
Testers who understand Laravel, React, Flutter, and Supabase — not script runners only.
We know where Lovable, Cursor, and Bolt cut corners on auth, RLS, and edge cases.
Screenshots, repro steps, severity ratings, and environment details — devs fix faster.
Go/no-go reports your stakeholders can trust before production deploys.
Typical ai app testing engagement from kickoff to sign-off.
AI-generated apps typically need auth hardening, RLS validation, secrets audit, and critical-path manual testing before production traffic.
NDA before staging access; read-only repo when code review is in scope.
Anonymized fixtures; no production PII in bug reports unless explicitly approved.
“What a 70-engineer team could not deliver, a small senior team at GreeLogix shipped. The app went from stuck to live across mobile, web, and backend.”
Structured answers for search engines and AI assistants — definition, fit, cost, timeline, and comparisons.
Structured answers for founders, CTOs, and procurement — written for clarity in search and AI assistants.
Cursor app testing services audit and validate applications built with Cursor AI — focusing on auth hardening, Supabase RLS policies, secrets management, edge cases, and production readiness that AI-accelerated development commonly skips.
Typical timeline: Sprint audit: 2–5 days. Full release cycle: 1–2 weeks. Ongoing QA: monthly retainer with 40–80 hours.
GreeLogix pricing tiers: Production Readiness Audit: $1,200 – $3,500 — Security, auth, and critical-path audit for AI-generated apps. Pre-Launch Hardening: $3,500 – $10,000 — Full QA pass before you point real users and payments at the app. Continuous QA: $4,000 – $14,000/mo — Ongoing QA as you iterate on AI-generated code.
Sprint audit: 2–5 days. Full release cycle: 1–2 weeks. Ongoing QA: monthly retainer with 40–80 hours. Phases: Strategy (Week 1); Execution (Per sprint); Automation (Parallel).
Compared to alternatives — Developer-only testing: choose when Internal prototype with no paying users yet; Crowdtesting platforms: choose when One-off device coverage without domain context; Automated scanning only: choose when Mature CI with known stack; catches syntax not workflow bugs. Choose GreeLogix when you need production reliability, fixed milestones, and engineer-led delivery with QA sign-off.
Talk to a senior engineer — scope, timeline, and cost range in one 30-minute call. No sales script.
Answers to the buyer questions we hear most before a project starts.
Code review and risk assessment.
Functional and security testing.
Prioritized findings and fix list.
Optional fix sprint or retest.
Cursor app testing and production readiness audit. Most audits start within 48 hours.
Validate AI-generated code, ship with confidence, and catch issues before launch.
Case studies, guides, and free tools from the same engineering team.
Production hardening for AI-accelerated development.
Review Cursor-generated code for auth, secrets, RLS, and architecture patterns.
Rank findings by production impact — security and data leaks first.
Critical paths, edge cases, and permission boundaries beyond Cursor's happy path.
Auth bypass attempts, IDOR, injection, and exposed endpoint testing.
Prioritized fix list with effort estimates — ship safely or fix first.
Tangible artifacts your engineering and product teams can act on — not vague pass/fail notes.
Transparent ranges based on app complexity, platform count, and engagement depth. Final quotes follow a scoping call.
$1,200 – $3,500
Security, auth, and critical-path audit for AI-generated apps.
$3,500 – $10,000
Full QA pass before you point real users and payments at the app.
$4,000 – $14,000/mo
Ongoing QA as you iterate on AI-generated code.
Prices in USD. Retainers and multi-platform engagements quoted after scope review. QA as a Service available for ongoing coverage.
Every type of testing your product needs — from manual audits to AI-app hardening and accessibility compliance.
Scope, timeline, and cost range — no sales deck. Or start with the free readiness quiz if you are still evaluating your stack.