Engineering services · MVPs for startups
AI MVP Development for Startups
Turn a focused idea into a product people can use.
We help shape, design, and build focused first versions that test the core product value without losing sight of the technical foundation needed for the next iteration.
What this service is
Who it's for, and what it fixes.
An MVP, a minimum viable product, is the smallest version of your idea that real users can try, built to answer one question: will people use this, and will they pay for it? It is not a demo and not a cheaper version of the full product. It is an experiment with working software.
We help founders decide what the MVP must prove, cut everything that does not serve that, and build it quickly on foundations that can grow if the answer is yes. Where AI is part of the idea, we build the smallest version that shows whether the AI part actually works for users, measured on real examples rather than a polished demo.
First-time founders
A clear problem and early conversations with customers, and no technical co-founder yet.
Founders with a prototype
A no-code or hacked-together version that proved interest but cannot take real users.
Companies testing a new line
An established business exploring a new product without pulling its own team off their work.
Ideas with an AI component
A product where a language model does part of the job, and you need to know it is good enough.
Problems it solves
- A long feature list and no agreement on what the first version must do
- Months spent building before a single user has tried anything
- A prototype that impressed investors but breaks with real data
- An AI demo that works on chosen examples and fails on real ones
- No way to measure whether users are getting value
What's included
The deliverables.
What a typical engagement produces. Discovery decides which of these your first release needs.
MVP definition
The question the MVP must answer, the one or two journeys that answer it, what is deliberately left out, and how success will be measured.
Clickable prototype
The core journeys as clickable screens you can put in front of users in the first weeks, before code is written.
The working MVP
A web or mobile app with sign-up, the core journeys and an admin screen, ready for real users and real data.
AI feature evaluation
Where AI is involved, a set of real test cases and a measured score, so you know how well it works before users do.
Usage measurement
The events that show whether users reach the value, captured in a way that respects their privacy.
Next-step plan
After launch, a short review of what users did and a recommendation: grow it, change it, or stop.
How an engagement runs
From first call to running software.
Five phases, each ending in something you can see and approve. The detail, and what we need from you at each step, is on how we work with you.
- 01
Discovery 1 week
What problem, for whom, and what the MVP must prove. We write a one-page definition and agree what is left out, which is usually most of the list.
- 02
Design 1–2 weeks
The core journeys as a clickable prototype, shown to five or so target users. Their reactions decide the build.
- 03
Build 4–8 weeks
Short cycles with a working build every two weeks. Scope is protected: new ideas go to a list for after launch unless they change what the MVP must prove.
- 04
Launch 1 week
Released to a first group of users you choose, with measurement in place and a quick way for them to give feedback.
- 05
Support 2–6 weeks after launch
Fixes and small changes while users try it, then a review of what was learned and a plan for the next stage, if there is one.
Technology approach
Plain, proven, and yours to keep.
Mostly the stack behind the Varynt products, chosen per project. Read how we build.
- React
- TypeScript
- React Native
- Node.js
- Spring Boot
- PostgreSQL
- LLM APIs
- Web or mobile
- React and TypeScript for web MVPs, React Native when it must be a phone app. Both carry straight into a full product.
- Back end
- Spring Boot or a lighter Node.js service, chosen by what the next stage will need, with PostgreSQL for data.
- AI, where relevant
- Hosted language-model APIs behind a small service of our own, with prompts, test cases and costs tracked, so the model can be changed later.
- Built to grow
- Proper sign-in, data separation and tests on the core, so a successful MVP becomes version one rather than a rewrite.
What you receive
Ownership, documentation, handover.
- The full source code in a repository you own, with its history, from the first week
- A written handover: architecture overview, how to run, build and release it, and the decisions taken and why
- Credentials, keys and accounts created in your name, never ours
- The automated test suites and the build pipeline, so anyone can keep shipping it
- The MVP definition, the prototype and the user feedback from testing it
- A post-launch review with the measurements and a recommendation
Typical timelines
Ranges, not promises.
- Prototype only
- 2–3 weeks
- Clickable screens tested with users, when you need evidence before building.
- Web MVP
- 6–10 weeks
- Sign-up, one or two core journeys, an admin screen and measurement.
- Mobile or AI MVP
- 8–12 weeks
- Adds store release, or an evaluated AI feature with its test set.
Every project is quoted for its own scope after discovery; prices are not published.
Security and quality
The practices we use on our own products.
Varynt runs four products for paying customers. Client work gets the same habits. See trust and security.
- Core journeys covered by automated tests, even in an MVP, so changes after feedback are safe
- Privacy basics from the first user: consent where needed, and only the data the MVP needs
- Access is checked on the server for every request; hiding a button is never the control
- Code review on every change, and automated tests that run before anything is released
- Test suites run in more than one order, so a test that only passes by luck is caught
- Before a release changes a database, it is backed up and the backup is restored and checked
- Secrets live outside the code, and dependencies are kept current
How long does an MVP take?
Usually six to twelve weeks from the start of discovery to first users, depending on whether it is web or mobile and whether AI is involved. A clickable prototype can be in front of users in two to three weeks.
What gets left out of an MVP?
Anything that does not help answer the question it exists to answer: secondary journeys, settings, most reports, edge-case automation. They are listed, not lost, and they become the roadmap if the MVP works.
Will we have to rebuild it if it succeeds?
That is what we design against. The scope is small, but the foundations are real: sign-in, data model, tests and a clean codebase, so the MVP becomes version one.
Can you build an MVP with AI in it?
Yes. We build the AI part as a small, measurable component: a set of real examples, a score for how well it does, and a cost per use, so you can judge it honestly before users depend on it.
Can we change the scope during the build?
Yes, when what you learn changes what the MVP must prove. Otherwise we hold the scope, because a growing MVP is the most common reason they launch late.
What happens after the MVP?
A review of what users did. Then you might grow it into a full product with us (see SaaS product development), change direction, or stop, and the code is yours whichever you choose.
Related
Services and products that fit alongside.
Other services: Custom software · AI chatbots · AI agents · Web applications · Workflow automation · Cloud and DevOps · Custom CRM
Get in touch
Tell us what your MVP needs to prove.
A short call about the idea, the users and the question you need answered. You get a one-page MVP definition and a timeline.