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Make your AI-built app dependable

Tools like Claude, Codex, Cursor, Lovable or Bolt get a product to a demo remarkably fast. Then real users arrive and logins fail, data goes missing or a deploy takes the site down. We read the code, reproduce the failures, fix what matters first and leave you with tests and a deployment you can trust.

Describe the app problemExplore our work

When this service fits

  • You built an app with AI coding tools and it works on your machine but not reliably in production.
  • Each new feature breaks an old one and nobody can say why.
  • An integration, payment, login or email flow fails intermittently.
  • You need someone to take over maintenance of a codebase that no person fully wrote.

What you receive

  • A read-only diagnosis first: architecture map, risky areas, failing flows reproduced, secrets exposure check.
  • A prioritised repair plan with estimates, so you decide what to fix and in what order.
  • Repairs to the agreed items, each with a test that fails before the fix and passes after.
  • A repeatable deployment with environment configuration kept out of the code.
  • A handover note: how the app is structured, how to run it, how to change it safely.

Scoped separately

  • Security certification or penetration testing (we flag obvious issues; a formal test is a specialist service).
  • New features beyond the repair plan, estimated as a normal build.
  • A complete rebuild, if the diagnosis shows it is cheaper than repair.
Example from our own products

We build our own products this way, with the safety nets in place

We use AI coding tools daily, so we know where they help and where they quietly break things. Our own platforms run hundreds of tests, a search-quality gate that can roll back a release, scheduled jobs that report their own failures, nightly database backups with integrity checks, and written rules for what must never happen (for example, never calling an API a partner has forbidden).

We have not published client rescue stories yet, so we show you the practices instead: how we work and the engineering behind Cumpără cu AI.

Cumpără cu AI · Raftul copiilor

How the work runs

  1. Intake

    You describe what fails and share read access to the repository and logs.

  2. Diagnosis

    We reproduce issues and map risks without changing anything. Written findings within the agreed time.

  3. Repair plan

    Fix, refactor or rebuild, item by item, with an estimate for each.

  4. Repairs with tests

    Agreed items fixed in small, reviewable changes, each with a test.

  5. Handover or care

    Documentation and walkthrough, or a monthly care plan to keep it healthy.

What affects cost and schedule

  • Size of the codebase and number of integrations.
  • Whether production data is involved and must be protected or repaired.
  • Hosting platform and how deployments currently happen.
  • How urgent the fix is and whether the app must stay online during work.

Questions buyers ask

Will you tell us to rebuild everything?

Only if the diagnosis shows it is genuinely cheaper and safer. Most apps are better served by targeted repairs, tests around the fragile parts and a clean deployment.

Can we keep using AI tools after you hand over?

Yes, and we will set the project up so you can do it more safely: tests that catch regressions, clear instructions for the AI tools in the repository, and a deployment that can be rolled back.

Do you sign an NDA?

Yes, before we look at private code.

Related services

Describe the app problem

Tell us what you need in a few sentences. NeedAI Studio answers personally, in English or Romanian.

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