Lovable Rescue & Stabilisation

Lovable shipped your UI fast. Production broke elsewhere.

Lovable rescue at Empyreal Infotech stabilizes Supabase auth state drift, hardens RLS rules, and removes unused dependencies before production deployment breaks at scale.

Your React scaffold works. Your design landed pixel-perfect. But Supabase auth state drifts in production, RLS rules silently fail, and your bundle is bloated with unused deps.

For product teams who need production stability after speed-to-market. 48-hour paid audit. $495. Founder-led review.

Book the 48-hour audit — $495 Send your repo URL
Supabase RLS Auth state machine Bundle pruning Founder-led
What Lovable Does Well

Fast UI scaffolding. Design pixel-accuracy. Component velocity.

Lovable's strength is unsupervised frontend velocity. You brief the AI, it produces React components, you get a Vercel preview by lunch. For design teams and founders who need proof-of-concept fast, that workflow is real value.

The pixel fidelity is a second strength. Lovable's design-to-code layer is tighter than most AI tools. Your Figma lands in the browser nearly exact. That precision matters for agency handoffs and client confidence.

Third: you own the source code immediately. No vendor lock. No export friction. You get a repo, you push to your own GitHub, you build on top. That unlocks customization.

Where Lovable Breaks in Production

Five failure modes we see repeatedly.

01

Supabase RLS rules fail silently.

Lovable scaffolds auth with Supabase, but RLS policies are templates. In production, users see data they should not, or auth blocks legitimate requests. The bug lives in policy logic, not code.

02

Auth state drifts between client and server.

Session tokens expire mid-flow. Refresh logic halts. Users get logged out without warning. Lovable does not handle race conditions around token refresh.

03

Bundle bloat from unused dependencies.

Lovable includes component libraries, animation tools, and form builders you never use. Your initial bundle is 400KB. Production is 320KB. That is still 80KB of dead code.

04

No database schema versioning.

Your schema shifts. Lovable does not track migrations. Your next deployment breaks old instances still running old schemas.

05

Edge case handling is untested.

What happens when the internet drops mid-request? When a file upload fails? Lovable generates happy-path code. Edge cases are left to you.

Our Rescue Path

How we stabilise Lovable codebases for production.

01

Audit.

We spend 48 hours reading your Lovable codebase. We identify security risks, architecture debt, and production failure modes. You get a written report naming every risk and its cost.

02

Stabilise.

We fix the critical path: auth logic, RLS rules, database migrations, error handling. No refactor yet. Just make it safe to deploy.

03

Refactor.

We strip unused dependencies, tighten type safety, add tests to the critical path. Bundle shrinks. Code clarity rises.

04

Scale.

We architect for 10x users. Database indexes. Caching strategy. API design. Your Lovable scaffold becomes a production-grade product.

Common Fixes We See

Patterns we fix in every Lovable stabilisation.

Supabase RLS audit

Every RLS policy rewritten. Auth rules tested. Data isolation verified.

Auth state machine

Token refresh logic fixed. Session timeout handled. Client-server sync guaranteed.

Dependency pruning

Unused packages removed. Tree-shaking enabled. Bundle audit done.

Database schema versioning

Migration strategy written. Rollback tested. Schema change documentation.

Error boundary coverage

Network failures handled. File uploads guarded. Fallback UX added.

Performance baseline

Load times measured. Database queries optimised. Monitoring configured.

Next Step

Your Lovable codebase has a production path. Let's talk about it.

Send your repo URL. We spend 72 hours reading your code and ship you back a stability plan and a fixed audit snapshot.

Send your repo URL Email Mohit directly
Questions

Frequently asked questions about rescuing Lovable projects

Direct answers about how this engagement actually works. If your question is not here, ask Mohit directly.

Lovable excels at UI but skips production fundamentals. Supabase RLS policies are templates that leak data in production. Auth state drifts between client and server when tokens refresh. Bundle bloat from unused dependencies. No database migration strategy. Edge cases are unhandled: network failures, file upload errors, auth dropouts. Happy-path code only.
Stabilise. Your React scaffold is solid. Your design landed perfectly. We fix the critical path: RLS rules, auth logic, database migrations, error handling. Then we strip unused dependencies, tighten type safety, and add tests. You keep the UI; we build the foundation underneath.
We read your Lovable codebase and identify security risks (RLS policy flaws), architecture debt (bundle bloat, missing migrations), and production failure modes (auth state drift, error handling gaps). We test auth refresh and session timeout scenarios. You get a detailed risk report with cost-to-fix estimates and a prioritised remediation plan.
Most projects run 120–180 hours. We rewrite RLS policies to isolate user data correctly, implement token refresh logic with race-condition handling, strip unused dependencies (usually 50–80KB bundle savings), create database migration strategy, add error boundaries and timeout handling, and implement monitoring. You launch production-safe in 2–3 weeks.
No. We stabilise in place. Auth stays secure but works the same way users see it. RLS gets tightened but data access logic is unchanged. Bundle gets smaller but features remain the same. Zero downtime migration.
RLS policies isolate user data per row correctly and are tested. Auth state machine handles refresh and expiration without dropping sessions. Bundle is 180–240KB (50% smaller). Database has migrations so schema evolution is safe. Error boundaries catch network failures and API errors. Network timeouts and file upload failures are handled gracefully. Monitoring is live on critical paths.

Have a different question? Email the team or read the full FAQ.