From AI idea to a working MVP in weeks

We help founders and innovation teams test an AI product with real users before committing a full budget. You get a focused, working product that does one valuable thing well, plus the data and plan you need for the next round of investment.

8-week planIllustrative
 
Typical length
About 8 weeks
Outcome
Live, demo-ready MVP
Scope
Fixed after discovery
Next step
Scale-up roadmap
Overview

Prove the value before you scale the build

Many AI ideas look strong in a demo and weaker in daily use.

An MVP tests the parts that matter: whether the AI is accurate enough, whether people use it and whether the economics work. We keep scope tight, build on proven tools and design the code so it can grow rather than be thrown away.

Capabilities

What we build

Each engagement is shaped to your use case. These are the building blocks we combine most often.

Capability

Discovery workshop

A structured session to define the problem, users, success measure and the smallest useful product.

Capability

Rapid AI prototyping

Early tests of models and prompts on your real data to confirm accuracy before building screens.

Capability

MVP design and build

Clean UX and a production-ready web or mobile app with sign-up, core flow and admin.

Capability

Investor-ready demos

A stable product, a demo script and metrics you can show to investors or leadership.

Capability

Usage analytics

Event tracking and feedback loops to show how people use the product and where AI helps.

Capability

Scale-up roadmap

A plan for architecture, costs, team and features once the MVP proves itself.

Use cases

Where teams use it

Work this service handles well. We help you pick the one with the clearest return to start.

Browse use cases by industry
  • A SaaS founder testing an AI-first product idea
  • An enterprise team piloting an internal copilot
  • A vertical AI assistant for one industry
  • A marketplace with AI-based matching
  • A proof of value before a large AI programme
  • A demo for investors or a grant application
Technology

Tools we work with

We pick the stack for your requirements and existing systems. A sample of what we use regularly.

App
Next.jsReactFlutterTailwind CSS
Back end
FastAPINode.jsSupabaseFirebasePostgreSQL
AI
ClaudeGPTGeminiLangChainLlamaIndexvector search
Ship
VercelAWSGoogle CloudPostHog analytics
Process

From first call to production

The same proven path for every project, sized to your scope.

01

Discover

Map the opportunity, the people involved and the outcome we will measure.

Output · Workshop
02

Define

Review data, workflows and systems, then agree architecture and scope.

Output · Plan and estimate
03

Prototype

Test the AI approach on your real data before building the full product.

Output · Working proof
04

Build and integrate

Develop in short sprints and connect to your systems, with demos every sprint.

Output · Production release
05

Launch and improve

Go live, monitor quality and cost, and improve based on real usage.

Output · Ongoing support
FAQ

Common questions

Can't find what you need? Ask us directly and we'll reply within one business day.

Ask a question
How much does an AI MVP cost?

It depends on scope, integrations and the platforms you need. After a short discovery call we give you a fixed-scope estimate with a timeline, so you know the cost before work starts.

What happens after the MVP?

We review the pilot results with you and agree on the next step: extend the product, harden it for scale, or change direction. The MVP code is built to be extended, not rewritten.

Will you sign an NDA?

Yes. We are happy to sign a mutual NDA before you share details of your idea.

Start a conversation

Bring your idea. We will help you shape the smallest version worth building.

Book a free consultation with our AI team. You'll leave with a clear view of feasibility, approach and next steps.