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MVP development that tests the idea before you fund the full product.

We help you pick the one hypothesis that matters, cut the first release to what tests it, build it properly and instrument it so the next decision is based on how people actually use it.

Discuss an MVP
What we deliver
  • Hypothesis and success measures
  • Scoped first release
  • Clickable prototype
  • Production-ready MVP
  • Analytics and feedback loop
Tools & platforms
TypeScript, React and Next.jsNode.jsPostgresVercel and managed cloud servicesProduct analytics tools

Where this helps

The first version keeps growing
Every stakeholder adds a must-have feature. Months pass, the budget is spent and the product still has not reached a real user.
A prototype that cannot survive contact with users
A quick demo impressed investors, but it has no authentication, no data model and no way to support the first paying customers.
Launch without learning
The product is live, but nobody defined what success looks like or tracked how people use it, so the next roadmap is built on opinions.

What we deliver

01
Hypothesis and success measures
A written statement of what the MVP is meant to prove, who it is for and which signals will count as evidence.
02
Scoped first release
A prioritized feature list with an explicit list of what is deliberately left out, and why.
03
Clickable prototype
A prototype of the core journey tested with target users before development starts.
04
Production-ready MVP
A working product with real authentication, a sensible data model and deployment — lean, but built to be extended rather than thrown away.
05
Analytics and feedback loop
Event tracking for the core journey and a simple way to collect user feedback, reviewed together after launch.

How it works

  1. 01

    Frame the hypothesis

    We agree on the target user, the problem and the single most important assumption to test.

  2. 02

    Cut the scope

    Features are ranked against the hypothesis. Anything that does not help test it waits.

  3. 03

    Prototype and test

    A prototype of the core flow is put in front of real users and revised.

  4. 04

    Build in short cycles

    The MVP is built in weekly or fortnightly increments, with a usable version available throughout.

  5. 05

    Launch and review

    After launch we review usage and feedback against the success measures and plan the next iteration.

Design decisions we make with you

  • What to leave out

    Admin tooling, edge-case settings and integrations are often replaced by manual processes at first. We document these shortcuts so they are revisited, not forgotten.

  • Buy versus build

    Authentication, payments, email and analytics use established services so the budget goes into what is unique.

  • Technology for the next stage

    We use a stack that can grow into the full product, so a successful MVP does not require a rewrite.

  • AI in the MVP

    If AI is part of the value, we test it with real inputs early, because output quality is often the riskiest assumption.

Applications

New SaaS products
A first version of a subscription product for a defined customer segment.
Internal innovation projects
Testing a new digital service or tool with a pilot group before wider investment.
AI product concepts
A working product that tests whether an AI capability solves a real user problem.
Digital services for customers
A first online channel for a service previously handled by phone, email or in person.

Related capabilities

Services

Questions buyers ask

It depends on the hypothesis and scope. Part of our work is cutting the scope until the first release can reach users quickly, and we give you an estimate after the scoping phase rather than before it.

The goal is that you do not. We keep the MVP lean but build it on a stack and data model that can grow. Some shortcuts are deliberate, and we document them.

We review usage against the success measures with you and decide what to build, change or stop. Many MVPs continue into SaaS development or a broader product build.

Yes. If AI is central to the product, we test it with real inputs early. See AI application development.

Discuss this capability with an engineer.

Tell us about the workflow or product. We reply with questions, a suggested first step and who would work on it.

Discuss an MVP