AI MVP Studio & Prototype Scale-Up
Ship AI-powered MVPs fast—without painting yourself into a technical corner.
The AI MVP Studio helps you do two things: launch new AI products quickly and upgrade the MVPs you already hacked together with no-code tools, AI assistants, or "weekend projects". We use the same engineering principles for both—so your MVP can survive real users, traction, and version 2, 3, and beyond.
MVPs that can survive success.
Whether you're starting from zero or already have a scrappy prototype, our goal is the same: get you to a working AI product that's good enough to test in the real world—and solid enough that you don't have to throw it away when it works.
From idea to first AI MVP
Assistants, copilots, dashboards, internal tools—whatever best validates your hypothesis.
We help you define the core use case, strip away noise, and ship the smallest feature set that proves whether your AI product deserves more investment.
From vibe-coded prototype to real product
Started with a no-code tool, auto-generated code, or a few scripts around an LLM?
We take those fragile prototypes and rebuild the parts that matter: proper backend, data models, authentication, logging, and deployment. You keep the value and UX your users like, but gain the reliability your team needs.
Clickable demos + functional backends
More than mockups—actual working software.
Your MVP includes a real backend, persistence, and integrations where necessary, so you can demo to investors, onboard early customers, or use it internally without fear of it breaking on day three.
Production-minded foundations
Auth, persistence, logging—ready for real users.
We put in just enough structure (tests, error handling, monitoring) to keep the system debuggable and extendable, without over-engineering it for a future that doesn't exist yet.
Scalable patterns ready for v2/v3
Build on what works instead of starting over.
We choose patterns, libraries, and architectures that make it straightforward to add features, introduce roles and permissions, support more data, and eventually evolve into a full product.
How it works
Clarify the core loop
Define what users do, what the AI does, and what success looks like—for a brand-new MVP or for the prototype you already have. We cut everything that doesn't support that core loop.
Design the user experience
Create an interface that makes the value obvious from the first interaction. We focus on fast feedback: users should understand what the AI can do, what it can't, and how to recover when it's unsure.
Build a slim but real backend
We implement the minimum backend and infrastructure needed to support real usage: databases, APIs, jobs, and integration points. When upgrading an existing MVP, we replace brittle glue with a clean architecture behind the same (or improved) UX.
Wire in AI correctly
Prompts, retrieval, tools, and models configured for reliability and cost control. We choose the right approach—simple API calls, RAG, or lightweight agents—and put guardrails around it so you can debug behaviour later.
Launch, learn, iterate
We get the MVP in front of users, add instrumentation to see what they actually do, and refine quickly. When it's working, we already have the foundation to turn it into a fully-fledged product rather than rebuilding from scratch.
Who this is for
Founders testing new AI product ideas who need something real, not just slides
Teams needing internal AI tools or demos fast, with a path to production
Agencies needing technical muscle behind their AI concepts and prototypes
Companies that started with no-code / vibe-coded AI MVPs and now need a stable, testable version
Product and engineering leaders who want to de-risk AI work with solid architecture from day one