This is Part 1 of a three-part series on building an MVP in the UK. Part 2 looks at what actually belongs in an MVP, and Part 3 walks through a real MVP from first conversation to build.
TLDR - how long will it take and how much will it cost? #
Thanks to AI the simple answer is “much less than it did a year ago”. This article looks at what you can expect from an MVP, how much it costs and how long it may take to build.
We’ve been building things for a long time now. Before AI was a thing, a VERY common pattern for getting a startup off the ground was:
- Build an MVP using the cheapest people you can find, typically an agency overseas. These agencies had no long term interest in the quality of the codebase - just get it out the door fast using the cheapest engineers they could find. You get what you pay for.
- Hand what was already a struggling “MVP” to engineers like us to fix and evolve beyond MVP stage. Because of that we only got involved at the last two stages - “Production-ready MVP” and “Complex MVP” - so the last two rows below are an aggregate of our experience, the first two our best guesses when extrapolating back.
Before AI, times and costs looked like this:
| Product type | Indicative budget | Duration | Typical characteristics |
|---|---|---|---|
| Interactive prototype | £5,000–£10,000 | 1-2 months | Demonstrates the idea but has limited or no production functionality |
| Simple web MVP | £10,000–£30,000 | 2-6 months | One main user type and one core workflow |
| Production-ready MVP | £60,000–£90,000 | 6 - 9 months | Authentication, administration, integrations and proper deployment |
| Complex MVP | £150,000–£300,000+ | 9-18 months | Multiple user types, AI, payments, mobile apps or compliance requirements |
You’ve probably noticed the jumps in indicative budget. These numbers are based on the notion that simpler apps need a single developer, a production-ready MVP typically needs 2 developers and a complex MVP 3 developers.
We’ve also excluded any other roles such as Product Managers or Designers, on the assumption the founder is driving everything up to MVP.
After AI, it looks like this:
| Product type | Indicative budget | Duration | Typical characteristics |
|---|---|---|---|
| Interactive prototype | £5,000–£10,000 | 5-10 days | Demonstrates the idea but has limited or no production functionality |
| Simple web MVP | £10,000–£18,000 | 10-18 days | One main user type and one core workflow |
| Production-ready MVP | £18,000–£30,000 | 19-30 days | Authentication, administration, integrations and proper deployment |
| Complex MVP | £45,000–£180,000+ | 30-120 days | Multiple user types, AI, payments, mobile apps or compliance requirements |
You’ll notice the simpler MVPs aren’t much cheaper despite being significantly quicker builds. The logic is that a single senior product engineer is required at a greater daily rate.
The complex MVP shows a bigger leap in cost, since two developers are generally needed for the build phase - though not for the requirements phase.
If you’re wondering what the difference between a Production-ready and a Complex MVP is, we cover that in Part 2.
Controlling costs - reclaim money from HMRC #
If you can demonstrate that you are solving scientific or technological uncertainty you can claim significant returns from HMRC as R&D tax credits.
This isn’t always as onerous as it may seem. For example a recent project we’ve worked on was an insurtech that embedded the ability to insure products in other people’s e-commerce websites. HMRC accepted this as R&D not because no one else offered the service, but because there was no known, reliable way to embed real-time insurance underwriting into someone else’s checkout flow — that gap in existing knowledge is what the relief is designed for.
That said, the e-commerce websites that the system is embedded into would NOT be eligible for tax credits as e-commerce is a well-solved problem.
Note, this isn’t tax advice — always confirm eligibility with a specialist before claiming, such as Forrest Brown.
AI’s unexpected superpower #
AI tools have reinvented the way we build software by writing much of the code that humans would otherwise write, and that’s brought major benefits - though maybe not the ones you’d expect.
Costs have dropped, for sure. But to take advantage of that you need experienced developers who can instruct AI tools on what to build - a skill many coders don’t possess, having spent their careers working out what “good” looks like as they code rather than directing someone else to do it. Developers without that experience either avoid AI tools altogether or “vibe-code” - an AI-assisted way of making it up as you go along, just a bit quicker and burning through ever-more tokens. We’ve never found much value in vibe-coding, and what little there is fades fast as an application grows in complexity.
The real benefit is the speed with which experienced developers can produce a prototype and then iterate as everyone learns what works and what doesn’t. Instead of a founder spending weeks with a Product Manager turning ideas into detailed requirements, we start from minimal input, add years of knowledge and experience, and produce a prototype in days rather than months. The founder gets early access to something real, not imagined, and from there we iterate together until the application is just right.
Next… #
That’s the theory. In Part 2 we go into more detail on what actually belongs in an MVP, and in Part 3 we walk through exactly how this played out on a real project.
Every project is different, so the fastest way to get a real number for yours is to talk to us. We offer a free “does it have legs?” call, no pitch, just an honest read on what you’re building and roughly what it’ll cost. Get in touch.
