AI SaaS MVP: Fixed at $3,460 or Custom Quote? How to Decide

AI SaaS MVP: standard package or custom quote?

Here is how the two sides look on our site today. No grid on a blog can place your idea for you, because two ideas with the same name can need very different builds. What decides it is your answers to a handful of questions. The scope is confirmed on the call.

• The standard package. Our MVP development agency page lists what it covers: "Product scoping & feature prioritization", "UI/UX design (mobile-first)", "User authentication & onboarding", "Payment integration (Stripe / RevenueCat)", database setup and "2-week post-launch bug-fix support". You own 100% of the code, on your GitHub. Fixed at $3,460.
• The custom build. Our services page describes it as "Marketplaces, AI platforms, HIPAA-compliant health apps, multi-tenant SaaS, fintech with compliance: complex builds that go beyond the standard MVP package." Complex integrations such as Plaid, FHIR or Stripe Connect are listed there too.
• Your idea sits somewhere between the two.

What counts as an AI SaaS MVP

Our AI MVPs page gives a short definition: "An AI SaaS MVP is one workflow wrapped in auth, workspaces, Stripe, and usage metering." The key words are "one workflow". A demo shows that the AI can do something. A product lets a stranger sign up, pay and get that one result again and again. Every extra workflow, data source or permission rule pushes the build toward a custom quote.

Questions to settle before the call

Answer these before the call. You don't need perfect answers. Rough ones are enough for us to place your idea. Scope confirmed on the call. For each question, here is why it matters and what to bring:

• 1. What is the one job the AI does? Why it matters: one job keeps v1 narrow. Several jobs usually mean several products. What to bring: one sentence, "User gives X, gets Y."
• 2. How many AI steps sit behind that job? Why it matters: one step behind one button is easier to scope than an agent that chains many tools. What to bring: a rough sketch of the steps, even on paper.
• 3. Where does the input come from? Why it matters: an upload or pasted text is self-contained. Live syncs with outside systems add integration work. What to bring: the list of tools your users would connect.
• 4. Does the AI need to search your documents? Why it matters: a small, single-source set is a different build from large libraries with permissions per file. What to bring: how many documents, and who can see which.
• 5. Does a human check the output? Why it matters: a simple "approve before sending" step is not the same as review queues with roles and history. What to bring: who approves, and what happens if they reject.
• 6. How do customers pay? Why it matters: flat plans, usage limits, credits and reseller pricing are very different amounts of billing work. What to bring: your planned pricing, even if it's a guess.
• 7. Any compliance rules? Why it matters: HIPAA, PCI or fintech rules move a build into the custom range on our services page. What to bring: the rules your buyers ask about.
• 8. Web, iOS, Android, or all three? Why it matters: it changes what gets designed, tested and submitted. What to bring: where your first users will actually use it.
• 9. Do you already have a prototype? Why it matters: sometimes it can be hardened, sometimes a rebuild is faster. What to bring: access to the repo or builder project.

How to read your answers

If most of your answers sound like "one", "upload", "small" and "simple", your v1 is probably narrow enough to discuss as a standard build. If several sound like "many", "live sync" or "regulated", expect to talk about a custom build. Either way, the call is where it gets decided. Want to put a rough cost on each feature first? Try our free app feature cost estimator. Got your answers? Book a call and we'll go through them line by line.

How to scope an AI SaaS MVP for a fixed price: an example

Here is a typical idea, made up for this guide, and how it shrinks into a v1. The full vision: an "AI sales assistant" that joins sales calls, updates the CRM, writes follow-up emails, scores leads and coaches reps. Run it through the questions:

• One job? No. That's five.
• Input? Live call audio plus a CRM sync, so two integrations.
• Human check? Not planned, so emails would go out unreviewed.

The cut: what stays in v1 and what waits

Each line shows what is kept for v1 and what is moved to later.

• Kept for v1: upload a call transcript. Moved to later: a bot that joins live calls.
• Kept for v1: get CRM-ready notes and a draft follow-up. Moved to later: automatic CRM sync.
• Kept for v1: approve, edit and copy. Moved to later: lead scoring.
• Kept for v1: accounts and a paid plan. Moved to later: rep coaching dashboards.

Why the smaller v1 wins

One input, one AI step, one human check, one way to pay. That's a v1 a founder can sell, show to investors and learn from. The CRM sync and lead scoring wait until users have paid for the core job. They also tell you which of those extras they actually want. The founder still has the big idea. They just stop paying to build it all before anyone has used the first part.

What about the monthly LLM bill?

An AI product has a second cost that a build price doesn't cover. As our AI MVPs page puts it: "AI MVP cost is two bills: the product build (same ballpark as other web MVPs) and inference (tokens)." The page warns that founders underestimate the second one and should cap usage before they buy ads. We cover token estimates, evals and guardrails in a separate guide on our blog. For this decision, just have a rough answer to one question: roughly how often will one user trigger the AI each month?

If you already built a prototype

Many founders reach this point with something made in Lovable, Bolt or Cursor. That's useful. It shows the workflow and saves time on the call. Our AI prototype to production page explains when a prototype can be hardened and when a rebuild is faster. Our guides on Lovable and other AI builders cover the common problems in more detail.

What happens after the call

Our MVP development agency page sets out the schedule. You get the price before any code is written. You own 100% of the code, on your GitHub, and you get 2 weeks of bug fixes after launch.

• 1. Free Strategy Call: 30 minutes. We go through your answers and confirm the scope.
• 2. Design Sprint: days 1 to 5.
• 3. Build Sprint: days 6 to 18. You see progress every week.
• 4. Launch & Handoff: days 18 to 21.

Find out which side your idea is on

Bring your one-sentence job, your feature list and your answers to the questions above. In 30 minutes you'll know whether your AI SaaS MVP fits the standard build, Fixed at $3,460, or needs a custom quote. You'll also know what to cut so you can launch in around 20 days. Book a call.

Is $3,460 enough to build an AI SaaS MVP?

It can be, if v1 is narrow. The standard package is Fixed at $3,460 and covers scoping, design, auth and onboarding, payments and 2 weeks of bug fixes. AI platforms, multi-tenant SaaS and regulated builds go beyond it. Your scope is confirmed on the call.

How long does it take to build an AI SaaS MVP?

Around 20 days for a standard build: design on days 1 to 5, build on days 6 to 18, and launch and handoff on days 18 to 21. Custom builds get their own timeline.

What makes an AI SaaS MVP need a custom quote?

Our services page lists AI platforms, marketplaces, multi-tenant SaaS, HIPAA-compliant health apps and fintech with compliance as builds that go beyond the standard package. Complex integrations such as Plaid, FHIR or Stripe Connect fall in the same group.

Can my Lovable or Bolt prototype become a real AI SaaS?

Often, yes. Sometimes rebuilding is faster than fixing. Our AI prototype to production service helps you decide which.

Do I own the code?

Yes. You own 100% of the code, on your GitHub. Want to know if your AI SaaS MVP fits the standard build? Book a call.