Your app has
paying users.
Can it survive them?
We take AI-generated SaaS to production: real tenant isolation, auth, data integrity and scale. Audit in five days, fixes shipped in three weeks, every claim backed by a number. If the audit finds nothing critical or high, it costs you nothing. Built in Brazil, on US working hours.
AI made building easy. Shipping is still hard. Fabership exists to close that gap, with proof instead of promises.
Fixed scope, fixed price
No hourly billing and no custom quote before you know the number. Start at the audit, move up only if the report says you should.
Production readiness audit
A 13-point review of tenant isolation, object-level authorization, exposed keys, auth and 2FA, migrations, backups, rate limiting, privacy law and behaviour under load. You get a report ranked by risk, with evidence, effort and the order to fix. If nothing critical or high turns up, you get your money back.
Production hardening sprint
Real row-level tenant isolation, auth and 2FA, role permissions, versioned migrations, tested backups, CI, monitoring and a load test with before-and-after numbers. Done means live in production with the test to prove it, not a pull request handed over.
Fractional CTO
Architecture decisions, code and security review, incident response and production metrics for founders without a technical co-founder. Offered after a sprint, never before, because you should see the work first.
Safety Assistant
Our own multi-tenant compliance SaaS, built end to end and used as the proving ground for everything we sell: workplace-safety documents, government e-filing and an AI assistant grounded on 33,000+ regulation chunks.
- Success rate under load taken from 11% to 100%: 874 requests served, zero timeouts
- Multi-tenant PostgreSQL with row-level security isolating every client's data
- AI assistant grounded on 33,000+ regulation chunks, citing the exact legal source on every answer
- 400+ pull requests merged, 1,548 automated tests passing, 167 tables under row-level security
Faber OS
The AI operations platform we run our own agency on: an MCP server with 6 tools giving agents governed access to client context and performance data, retrieval over our knowledge base, running 24/7, and weekly content pipelines that draft, compliance-check and publish client work automatically. We sell what we operate daily.
Six digital products live in production today
Four of them client platforms: a beverage-delivery marketplace load-tested to 200 concurrent users, the traffic of thousands of daily customers, with zero errors across 15,462 requests (p95 292 ms), an auto-parts delivery operation with fiscal e-invoicing, and a field-services platform with 142 versioned migrations and automated QA sweeping 28 screens. Fifteen production integrations across them: marketplace OAuth, PIX and live card payments, HMAC-signed webhooks, WhatsApp Cloud API. Case studies with names, on a call.
Built to ship, not to bill hours
Your prototype was never the problem
Lovable, Bolt and v0 are very good at getting you to first customer. They are not built to answer whether customer A can read customer B's data. That question arrives with your first serious buyer, and it arrives as a security questionnaire.
We fix the class, not the symptom
Plenty of services will debug the screen that broke, by the hour. We take the whole app to production: isolation, auth, data integrity, load. The measure is whether it survives real users, not whether the error went away.
Every claim comes with a number
On our own SaaS we found 22 places where the app blocked its own event loop. We took it from 11% success under load to 100%, with 874 requests and zero timeouts, at a sustained concurrency that maps to hundreds of daily active users. We report the before and the after, always.
Nearshore, same working hours
Based in Brazil, one hour ahead of New York. Real-time calls and same-day iteration, none of the overnight lag you get from the other side of the world.
Lucas Augusto
I built my own multi-tenant SaaS end to end: the row-level security, the load tests, the incident calls at 2 a.m. That is where I learned what separates a demo from a product people trust with their data. Fabership exists because AI collapsed the cost of building, but shipping something that survives real users is still engineering. Every claim we make comes with a number, and every fix ships with the test that proves it. When you hire Fabership, you talk to me.
Talk to LucasFrom call to production
Self-check, free
Run our 13-point readiness checklist on your own app. No access, no scan, nothing to install. Most founders already know their answer by point four.
Run the free 13-point self-check →Audit, US$1,500
With your written authorization we go deep and hand back a report ranked by risk, with evidence, effort and the order to fix. A fixed-price proposal comes attached.
Sprint, then live
Three to four weeks to ship the fixes, with a load test proving the before and after. Then you either run it yourself or keep us on monthly.
Find out before your biggest customer does.
One call to scope it. If we are not the right team, you hear it on the call, for free, not after an invoice.
Book a call