Launch an MVP that becomes the product.
Most MVPs are thrown away at the first real customer. Yours starts on a foundation that is already production grade: multi-tenant, roles, subscriptions, security, hosting in France. You test your market in a week, and you do not rebuild afterwards.
- to put a real product in front of real users
- D+7to put a real product in front of real users
- of the source code belongs to you, exportable
- 100%of the source code belongs to you, exportable
- rewrites the day traction arrives
- 0rewrites the day traction arrives
The real cost of an MVP is the second one.
A founder has two contradictory imperatives: move fast to validate a market hypothesis, and build something that will hold if the hypothesis is confirmed. Common practice sacrifices the second: you hack a prototype together in a few weeks, find it some users, then discover everything has to be rewritten (authentication, billing, the data model) at the exact moment you should be serving the customers who are arriving.
That rewrite costs six months, a hire, and often a funding round spent redoing what exists. It also arrives at the worst moment for due diligence: an investor auditing the tech finds generated code nobody understands, keys in the browser, a database with no migrations. It isn't a talent problem; it's a foundations problem.
Kubbler removes the second MVP. The foundation (accounts, organisations and roles, Stripe subscriptions, validated and versioned data, security, deployment) is written once by engineers and shared by every project. The AI interprets your vision to assemble the product layer on top: screens, journeys, business model. What you show your first users is already the product, in readable JavaScript, in a repository that belongs to you.
The prototype and the product. Or just the product.
What a disposable MVP costs over a startup's full cycle, and what changes when you only build one.
What an investor will look at.
The questions always arrive in the same order: does it hold, is it secure, and is it yours. Here is what answers them, from day one.
Ready for traction
Exactly what usually breaks the moment the product finally starts to work.
Roles & organisations
Teams, invitations, permissions, billing per organisation: in place before your first customer.
Stripe subscriptions
Plans, free trials, plan changes, failed payments and reminders: wired and tested.
Validated data
Versioned schemas, validation on input, generated migrations. Technical debt doesn't pile up.
Ready for scrutiny
What you'll be asked to prove, sooner or later, and often at the worst moment.
Security & GDPR
Two-factor authentication, quotas, anti-fraud, security headers, DPA provided. Set at the source.
Your code
Readable, conventional JavaScript, exportable to GitHub. No dependency on us to keep going.
Usage analytics
What your users do, screen by screen, from day one, to decide with numbers.
What you can build with it.
Three product shapes the foundation already carries, precisely the ones we see break elsewhere the moment they start to work.
A B2B SaaS with teams and billing
Organisations, invitations, roles, plans and plan changes: the skeleton an investor expects to see hold, and a first enterprise customer demands. It's already there, tested, before your first line of business logic.
A two-sided marketplace
Suppliers on one side, customers on the other, Stripe payments in the middle, transactional emails and usage analytics to know what converts. You work on supply and demand, not on the plumbing.
A freemium product ready to move upmarket
Free to enter, paid to continue: plans, trial, quotas, moving from one plan to another. The conversion mechanics are already written; you only decide where to place the limit.
How it works, concretely.
Four steps, three actors: you carry the vision, the AI interprets it, and the engineers who wrote the foundation guarantee it holds.
You describe your product
Your market, your users, your business model, the key journeys. A conversation, not a specification: you refine as questions come, the way you would with a CTO.
The AI interprets
It translates your vision into screens, a data model and journeys, composing with 81 interface blocks and 22 existing capabilities. It improvises neither billing nor security: it activates them.
The foundation carries
Organisations, roles and invitations, Stripe subscriptions, validated and migrated data, two-factor authentication, quotas, deployment: code written and reviewed by engineers, already in production for other products.
You test, measure, iterate
You publish on your domain, invite your first users, measure what they do. Every iteration is a sentence or a setting, not a sprint. And when an investor asks for the repo, you open it.
Why Kubbler, for a founder.
Four reasons rooted in how the product is built, that weigh when you raise, when you hire and when you grow.
One object, from prototype to product
What you show your first users is already the final product: same accounts, same database, same billing, same repository. There is no moment where you'd have to "redo it properly". You capitalise on every iteration instead of throwing it away.
Calm due diligence
An investor or CTO auditing you will find readable, conventional JavaScript, a versioned data model with its migrations, security and quotas set at the source, and an exportable repository. Not a generated black box nobody can answer for.
The code and the data are yours
GitHub export at any time, a dedicated database per project, encrypted secrets, payments on your own Stripe account. The day you hire your technical team, they start from what exists and evolve it, with or without us.
Humans behind the foundations
The AI assembles your product layer; the foundations are written, reviewed and operated by a team of engineers who fix them for every project at once. You get a foundation only a senior team could have written, from day one, without hiring it.
The questions we get asked.
Precise answers, because decisions are made on facts, not on promises.
The foundation is multi-tenant, with organisations, roles, invitations and subscription billing already in place, and it's already running in production for other products. Each project has its own database and a dedicated container. Scaling is an infrastructure question, not a rewrite.
Readable, conventional JavaScript (Next.js on the front, a Node.js API on MongoDB), a versioned data model with its migrations, two-factor authentication, quotas and anti-fraud set at the source, and an exportable repository. They will also see a clear line: the AI assembled the product layer, the foundations were written by engineers.
The backend runs on our Scaleway infrastructure in Paris, the frontend is served from Cloudflare's edge. Each project has its own database, encrypted secrets and domain. A data processing agreement (DPA, GDPR article 28) is provided, useful from your first enterprise customer.
Yes, and it's designed for that. The code exports to GitHub at any time; your developers review, version and evolve it in their own workflow, with their continuous integration. They can also keep working inside Kubbler: prompt on Monday, code on Tuesday, on the same project.
Count one afternoon for a first product online, one week for an MVP you dare show paying customers: accounts, journeys, billing, brand, domain. The time doesn't go into plumbing but into what only you can decide: the offer, the positioning, the price.
Free during the beta, no card required. Then cancellable monthly plans (Starter, Pro, Team) that include hosting, certificate, backups and support. No separate infrastructure line, no "set-up" cost: your burn is readable from the first month.
Show a product, not a promise.
Free during the beta. By the end of the week, your demo runs on a real product, with accounts, payments and a repository to open in front of whoever you like.