A Minimum Viable Product is not a half-finished app — it is the smallest set of features that delivers real value and tells you whether your hypothesis holds. We build MVPs for founders, scale-ups and corporate innovation teams who want to know quickly whether an idea will work in the market.
The term comes from Eric Ries's Lean Startup and means: the smallest product with which you simultaneously deliver value to a first group of users and learn whether your assumption about the market holds. It is therefore not "a stripped-down version of the end goal", but a complete core function that acts as a hypothesis test.
The difference from an ordinary "first version" lies in the purpose. A first version of software is built because the scope is already fixed and you want to move towards production. An MVP is built because the scope is still uncertain and you want to learn first. That difference shapes everything that follows: the chosen technology, the way you measure, the architecture, the pace and, not least, how you as the client handle scope discussions.
In practice we see three persistent misconceptions. One: an MVP is not a prototype. A prototype is there to demonstrate something internally or to designers, whereas an MVP goes to real users and measures real behaviour. Two: an MVP is not a "half-finished app". If the core function doesn't work, you learn nothing. Three: an MVP doesn't need to be production-perfect, but it must be good enough to bring users back and not put them off at the first glitch. We guide you through that trade-off, deciding what does and doesn't belong in this version, and then build quickly and pragmatically.
An MVP is a tool, not an end goal. That is why our approach works with sharp hypotheses, a MoSCoW list (see the MoSCoW tool for the framework we use) and clear success criteria before we start building. What must be true at the end to justify carrying on? What would make us decide to pivot? These questions are on the table before the first sprint begins, not after.
You have a hypothesis about a product or service, but no evidence yet that customers will pay for it, return, or choose it over alternatives. An MVP delivers that evidence with real users, rather than modelling it for months beforehand in spreadsheets and business cases.
The budget doesn't stretch to a full rollout. You want to show yourself, your board or your co-founders that the first version gains traction, and only then invest further. An MVP takes that first, measurable step without committing to a large budget.
Investors no longer want to see Figma files; they want a working product with early users and data on behaviour and retention. An MVP takes you from pitch deck to pitch with evidence, and structurally increases the chance that a term sheet actually follows.
You operate in a market where timing matters: new regulation, an opening in the value chain, an AI trend or a gap an incumbent has left. An MVP gets you live sooner than a full product would, giving you time to claim a position before others see the opportunity.
We start with a MoSCoW session: Must, Should, Could and Won't. We formulate the core hypothesis, define success criteria and jointly determine which metric decides whether the MVP wins or loses. This is the phase where most time is saved; a sharp Won't list prevents sprints of waste later.
A clickable Figma showing the core flow. Not all screens, but the essential path your user will take. We test the concept with a handful of future users before writing a single line of code, and adjust the design based on what they understand, miss or skip.
We build in sprints and demonstrate working software every two weeks. No big-bang delivery: you see progress, can adjust scope, and remain in control of priorities. Sprint demos are a natural moment to ask "do we really need this?" before it's too late.
We put the MVP live for a defined group of real users, typically starting with a handful and then growing to a few dozen. We measure behaviour, conduct short interviews and test the hypothesis against hard data. Opinions are welcome; behaviour is what counts.
Based on the lessons learned, you can build on towards v1.0, change direction, or honestly conclude that the hypothesis doesn't hold. All three are valid outcomes. We tell it like it is, even when that runs against the sense of ownership that inevitably develops during the build.
If the MVP succeeds, we guide the transition to a full-fledged product: scaling the architecture, expanding the team, go-to-market decisions and, where needed, a review of the stack. We're also available after the MVP phase if you want us to be, or you can take it in-house, which is equally fine. Read our page on our process to see how we think about that transition.
An MVP stack needs to be quick to deploy, well understood by the team and not hold you back as the product grows. No microservices, no Kubernetes; those don't belong in an MVP.
React, Vue or Astro. Pragmatic, widely adopted and easy to hand over.
Node.js, Django or FastAPI. Solid, readable and backed by large ecosystems.
PostgreSQL for relational data, MongoDB where a document store is a better fit.
Vercel, Netlify or Hetzner: quick to deploy and transparent in cost.
Auth0, Firebase Auth or Supabase. No need to build your own password stack.
React Native or Flutter. Cross-platform is almost always the sensible choice for an MVP.
Claude or GPT API for AI features. RAG, agents and assistants where they make sense.
GitHub Actions, simple CI, a single environment. No Kubernetes for an MVP.
If you're building a quoting tool for accountants, a scheduling system for engineers or a CRM for a well-known target group, the hypothesis question has already been answered. The market exists, the users are there and the pattern is clear. You don't need an MVP, but a well-scoped first version of solid software. Read our page on web development or app development for that route; it calls for a different approach.
If you sell to banks, hospitals or government bodies, you operate in an environment where "MVP quality" is not an option. There, the first release must already meet security requirements, audit trails, single sign-on and SLA commitments. Customers don't expect an experiment; they expect a product. "We'll learn as we go" doesn't fit the procurement cycle of these buyers and usually costs you more than it delivers.
In regulated sectors (medical, financial) or when replacing existing software, requirements apply from day one that rule out an MVP approach. The scope is known, the tolerance for experimentation is low and the risks of a half-working release are high. In that case, a phased custom development approach with release trains and backwards compatibility is the better choice: not a learning loop but a structured rollout path.
Trying to be too complete. The biggest pitfall: "before we launch, we also want X, Y and Z." As soon as that happens, it is no longer an MVP and you lose the whole point of learning. A good Won't-list is just as important as the Must-list: write down what is deliberately left out and hold each other to it.
No user testing. Many MVPs are built on assumptions about what users want. Before you write any code, speak with your target audience; otherwise you'll quickly build the wrong thing.
Over-engineering for scale that doesn't exist yet. Microservices, a bespoke Kubernetes cluster, message queues, custom feature flags: these suit a product with millions of users, but they're fatal for an MVP with ten. Start simple; add complexity when it starts to hurt.
No exit strategy if the hypothesis proves wrong. Decide in advance: what will we do if the pilot disproves the hypothesis? Test another idea? Pivot? Stop? Founders who don't discuss this become attached to their MVP, which is a dangerous position to be in.
No measurement. Without analytics, user interviews or conversion tracking, you know nothing. Build simple instrumentation in from sprint one, otherwise your "learning outcome" is a feeling rather than evidence. See also our page on the cost side of custom software for context on what this type of work typically involves.
No-code is excellent for very simple validations: a landing page, a form, or a manually run "concierge MVP". We work with pro-code: slower to start, but infinitely more scalable and without vendor lock-in on your growth. For genuine software MVPs, that is usually the right choice.
A freelancer is cheaper per hour, but vulnerable: holidays, illness or departure mean a standstill. We offer a small team with overlapping skills, code reviews and continuity. For an MVP that will make or break your business, that is the difference between going live and getting stuck.
Many agencies are execution-focused: you provide a specification, they build. We think in product goals: what is the hypothesis, how do we measure learning, what belongs in this phase and what doesn't? That product mindset matters more for an MVP than the number of people at the table.
Hiring a team for an unproven idea is risky: recruitment takes time, your commitment to people is substantial, and if you pivot you're left with skills that no longer fit. An MVP through an agency gives you flexibility; if it works, you can then develop it further in-house.
We're not a pure executor who simply works through tickets. We ask uncomfortable questions, challenge scope and say where necessary: "this doesn't belong in this MVP". Honest advice, even when it works against our revenue. An MVP that grows too large costs you more and carries more risk for us, and we have no interest in dragging it out.
From day one you hold the full codebase, the repository and the cloud accounts. No vendor lock-in, no hidden cost tricks and no platform you get stuck in as you grow. If you want to take the work in-house or hand it to another team after the MVP phase, you can do so without pain. The code is yours, and so are the decisions.
If your MVP succeeds, we can continue building the full product: expanding the team, working out the architecture, designing the GTM stack and setting up a release discipline. But it's your call; we don't tie anything together and there's no package you're obliged to follow through.
A half-hour introductory call in which we go through which hypothesis you want to test, which core features are minimally needed for that, and how we translate that into an initial sprint plan. Honest advice, even if the outcome is that an MVP is not the right route.
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