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Tecifo

Lovable to production: an MVP that holds up with paying customers

We audit the generated code, keep what works and rebuild the parts that fail under real users: auth, Supabase row-level security, the data model, AI costs, tests and deployment. The product stays live throughout.

Book a free architecture callSend my brief, get questions back

Free 30-minute call. You leave with a written summary of the approach and a sensible first step. No deck, no pitch.

Discovery sprint from $2,500, builds from $6,000

Stack

  • Next.js
  • React
  • TypeScript
  • Supabase
  • PostgreSQL
  • Redis
  • Docker
  • GitHub Actions
  • Vercel
  • AWS
Starling MXEnterprise AI knowledge platform

Sound familiar?

  • The MVP breaks as users arrive

    Generated code that worked for the demo fails on edge cases, concurrent users and real data.

  • Security and data access were an afterthought

    Row-level security, permissions and tenant isolation have to be in place before you onboard paying customers.

  • Nobody can change the code safely

    Without structure, tests or CI, every fix risks breaking a screen nobody checked.

What you get

  • A code and architecture audit with a written keep, fix or rebuild verdict per part
  • Auth, row-level security and a multi-tenant data model
  • A production AI layer: streaming, prompt caching and a context budget
  • Background jobs for slow work such as file processing
  • Tests on the paths money flows through, and CI/CD with GitHub Actions
  • Deployment on Vercel or AWS with monitoring

How it works

  1. 01

    Audit the prototype

    We read the code, run it against real cases and write a plan that says what stays, what gets fixed and what gets rebuilt, with the reasons.

  2. 02

    Fix the foundations

    Auth, data model, AI layer and tests, in small increments, while the product keeps running for your users.

  3. 03

    Launch for real users

    We deploy with CI/CD and monitoring, and hand over a codebase your team can extend.

What "production ready" means for a Lovable or Bolt app

A Lovable or Bolt app is production ready when a second user cannot see the first user's data, no service-role key or secret reaches the browser, slow work runs in background jobs, AI costs have caching and a budget, the paths money flows through have tests, and deploys run through CI with monitoring on the other side.

Generated code is good at the first version of a screen and weak at the things no screen shows: row-level security on every table, tenant isolation in the data model, idempotent webhooks, and a job queue. Those are the items that fail when the second paying customer arrives, and they are what the audit looks for first.

The audit: how we decide what to keep, fix or rebuild

The audit reads the code, runs it against real cases and produces a written verdict per part: keep, fix or rebuild, with the reason. Most of a generated MVP is kept. Auth, the data model and anything that touches money or secrets are usually fixed. A full rebuild is rare and we say so when it is not needed.

The audit is the discovery sprint for this service, from $2,500, and the document you get is useful even if you never hire us for the build: a prioritised list, with each item's risk and effort, that any engineer can work from.

Fixing the foundations while the product keeps running

Foundations are fixed in small increments on the live product: row-level security and auth first, then the multi-tenant data model, then background jobs for slow work, then a cached and budgeted AI layer, then tests and CI. Each increment ships behind your normal release, so users keep working and you review real progress every week.

This is the path an enterprise knowledge platform took with us: it started as a live proof of concept and, over six months and 1,145 hours, gained background PDF, DOCX and PPTX conversion, prompt caching, context-window budgeting, multi-tenant workspaces on Supabase RLS and a human approval step before AI edits. The proof of concept never went offline.

What taking a Lovable app to production costs and how long it takes

Taking a Lovable or Bolt app to production at Tecifo starts with the audit, a discovery sprint from $2,500 that typically takes about a week, followed by a fixed-scope build from $6,000. For an illustrative MVP the foundations take three to five weeks to fix, with launch, CI and monitoring in the week or two after.

The price moves with how many tenants and roles the data model needs, whether payments and webhooks are involved, how much AI the product calls, and how much of the generated code the audit says to keep. Each line is in the audit document before the build is quoted.

When to leave your MVP alone

Leave the MVP alone if you are still testing whether anyone wants the product. Generated code is the right tool for that stage, and hardening it before you have paying users spends money on problems you may never have. Call us when the first customers are real and the failures have started.

Lovable MVP vs production build

What the audit usually finds in a generated app, and what the build leaves behind. The audit tells you which rows apply to yours.

  • Data access

    As generated
    Row-level security off or partial; one user can often read another's rows
    After the production build
    Row-level security on every table, tested with a second account

  • Secrets

    As generated
    Service-role key or API keys in the browser bundle
    After the production build
    Secrets server-side only, in your deployment's secret store

  • Slow work

    As generated
    File processing and AI calls inside the request
    After the production build
    Background jobs behind a queue, with retries

  • AI costs

    As generated
    Full prompt every call, one model for everything
    After the production build
    Prompt caching, a context budget, a model per task

  • Changes

    As generated
    Every fix risks another screen
    After the production build
    Tests on the money paths, CI on every pull request

  • Deploy

    As generated
    Click to publish
    After the production build
    CI/CD to Vercel or AWS with monitoring and rollbacks

Most apps need three or four of these rows, rarely all six. The audit says which, with the effort for each.

Questions, including cost and timeline

Tell us what you're building.

Free 30-minute call. You leave with a written summary of the approach and a sensible first step. Prefer writing? Send a brief and we reply by email with questions.

Book a free architecture callSend my brief, get questions back

Discovery sprint from $2,500, builds from $6,000

Or email info@tecifo.com with a few times that suit you.

Not ready to talk? Take the checklist.

Fifteen checks we run before real users and real data hit an AI product: prompt caching, context budgets, approval steps, row-level security, agent state, traces. We email you the link.

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