MVP cost in 2026: what drives the price

“How much does an MVP cost?” is one of the first questions a founder asks. And it almost always comes with a feature list that no longer fits the word “minimum.” Social login, a dashboard with charts, a mobile app, chat, PDF reports, integration with everything. Each item looks small. Added up, they become a whole product.

In this piece I show what makes up the price of an MVP, where the money usually goes and how to cut scope without removing what makes customers pay. I don't publish a price list, and I explain why at the end.

What an MVP is, in practice

MVP stands for minimum viable product. In practice, it's the smallest version of the product that a real customer can use to solve the main problem, ideally paying for it.

Two words matter here. “Real”: it's not a clickable prototype or a slide deck. It's live software, with login, data and billing. “Main”: one problem, not five. If the MVP tries to solve everything, it stops being minimum and starts costing as much as a full product, with the risk of a full product.

Why MVPs cost more than they should

The biggest waste in an MVP isn't the expensive hour. It's building what nobody will use.

Pendo, a software usage analytics company, measured this. In its 2019 feature adoption report, based on usage data from 615 customer accounts, it concluded that 80% of the features in the average software product are rarely or never used. In the same study, an average of 12% of features generated 80% of daily usage.

The company also estimated that publicly traded cloud software companies invested up to $29.5 billion in research and development of barely used features, according to the press release published on February 5, 2019. These are large companies, with product teams and data. In an MVP, with no usage data at all, the risk of betting wrong is higher.

If you're the one hiring, the math is simple. If most features won't be used, every feature you take out of the first version is money that stays in the bank for the second, which will already be decided with real usage.

What drives the price of an MVP

Two MVPs with “the same screens” can have very different prices. What weighs most almost never shows up in the design. There are six factors.

1. Number of flows

Count flows, not screens. A flow is a complete path: the customer signs up, places an order, pays and gets the confirmation. Each flow brings rules, validation, error messages and tests. It's the item that moves the price most.

2. Required integrations

Payment gateway, invoicing, WhatsApp, ERP, partner APIs. Each integration has its own documentation, test environment and errors that only show up with real use. In the MVP, only the integration the product can't work without goes in. The rest can be manual for a few weeks.

3. User roles

Customer, admin, manager, partner. Each role has its own permissions, screens and tests. An MVP with two roles is very different from one with four.

4. Billing

If the product charges a subscription, billing goes into the MVP. It brings rules for late payments, cancellations, plan changes and refunds. The more payment methods and plans, the more rules to build and test.

5. Security and personal data

Secure login, control over who accesses what, backups and what the LGPD (Brazil's data protection law) requires for your customers' data. This isn't “phase 2.” An MVP with paying customers and exposed data is the kind of savings that ends up costing the most.

6. Mobile: web, app or both

A web MVP that works well on mobile costs less than an app in the stores, which brings developer accounts, Apple and Google review and two platforms to maintain. For many products, the app can wait for the second version.

Did AI make MVPs cheaper?

It made writing code faster. It didn't make getting the product right cheaper.

AI tools generate screens and features in minutes. The problem is what comes next. In the Stack Overflow 2025 developer survey, 84% of respondents said they use or plan to use AI tools. But 46% said they distrust the accuracy of what AI delivers, versus 33% who trust it. The biggest frustration, cited by 66%, was answers that are “almost right, but not quite.” And 45% said fixing AI-generated code takes more time.

For founders, this shows up in a familiar way. An MVP built solo with AI gets to 70% fast. The missing 30% of the MVP, like security, billing, separated data and error handling, is exactly the part that costs. AI helps a lot if you know what you need to build and can review what it delivers. It doesn't replace deciding what goes in and what stays out.

How to cut scope without cutting what sells

Cutting scope isn't doing less out of laziness. It's choosing, with clear criteria, what needs to be live on day one. Here's how:

1. Write the main problem in one sentence. Anything that doesn't help solve that sentence goes on the later list.
2. Map the flow that makes the customer pay. From first visit to payment. That flow is the MVP. The rest is support.
3. Swap features for manual processes. Reports can come from a spreadsheet for a month. You can handle approvals yourself. If volume grows, then it becomes a feature.
4. Keep what protects you. Login, permissions, backups and billing stay. Cutting those isn't cutting scope, it's taking a risk.
5. Write down what was left out. The list of what's out is as important as the list of what's in. It prevents arguments mid-project and becomes the plan for version 2.

We work the opposite way from a traditional quote: instead of estimating everything and seeing if it fits, we cut the scope to fit the date and the budget.

How to compare two MVP proposals

Put the proposals side by side and check whether each one answers:

• Which flows are in and which are out of the first version?
• Which integrations are included, by name?
• Is billing included? With which payment methods?
• What's planned for security and LGPD?
• Is the delivery date in the contract?
• Who owns the code, the domain and the access?
• How much does it cost per month to keep the product live?

The cheapest proposal that doesn't answer these questions usually becomes the most expensive after the first change order.

How we do it at the Studio

We don't publish a price list because an MVP price without discovery is a guess. In discovery, we cut the scope, write down what's in and what's out and only then set the price. The deadline is written into the contract. The code, files and accounts stay in the client's name, and the builders are our in-house dev team, using Claude Code and Figma for design and build.

One example of a deadline that came out of this process: AI Vou Eu, an AI travel SaaS, went live in 4 weeks with the Studio. And every system ships with an AI agent that runs every day, flags failures, suggests improvements and checks that the data makes sense. In an MVP, it helps show early which features are being used and what deserves to go into version 2.

If you have an idea and want to know what the first version costs, with cut scope, fixed price and a written date, the path starts with the discovery for our MVP, SaaS and custom software development service.