A custom app in 2026 typically costs between $15,000 and $150,000, and AI-accelerated development has compressed the low and middle of that range more than the top. A simple, well-scoped web app or MVP now lands at $15,000 to $40,000. A production app with accounts, payments, and a real backend lands at $40,000 to $90,000. A complex, multi-platform product with heavy custom logic still runs $90,000 and up. AI made the first draft faster. It did not remove the parts that make software actually work in production.
Here is the honest breakdown, and where the AI-speed story is true versus oversold.
Web app, mobile app, or both
The single biggest fork in the cost is what you are building.
A web app runs in the browser and is usually the fastest and cheapest path to a working product. If your users do not strictly need to be in an app store, start here.
A mobile app (iOS, Android, or both) adds native build pipelines, app-store review, device testing, and push infrastructure. A cross-platform framework lets one codebase serve both, which is how most teams keep mobile affordable in 2026, but "one codebase" still means two stores, two review processes, and device-specific testing.
Both is the most expensive, and often you do not need it on day one. A common, cost-smart path is a web app first, then a mobile wrapper once the product has proven demand.
The three price bands
Simple app or MVP: $15,000 to $40,000. One core workflow, a handful of screens, basic accounts, a straightforward backend. The goal is to get a real, usable product in front of users fast. This is the band AI-accelerated development compressed the most.
Production app: $40,000 to $90,000. Multiple workflows, real user accounts and permissions, payments, integrations, an admin surface, and the reliability work that a paying-customer product requires. Most serious business apps land here.
Complex or multi-platform product: $90,000 and up. Heavy custom logic, real-time features, multiple integrations, iOS and Android and web, compliance requirements, and the observability a product at scale needs.
What AI-accelerated development actually changes
This is where most quotes and most expectations go wrong, so here is the honest version.
What AI genuinely speeds up: the first draft. Scaffolding, standard patterns like authentication and CRUD screens, boilerplate, and a lot of the "typing" of software. On the right project, AI writes a large share of the first-pass code, which is why the MVP and simple bands got cheaper and faster. This is real, and we build this way every day.
What AI does not remove:
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- Architecture decisions. What should the data model be? How will this scale? These are human engineering calls, and getting them wrong is expensive to undo later.
- The hard 20 percent. Complex business logic, edge cases, and the integrations that make an app useful are where the time still goes. A demo that looks done is usually 60 percent done.
- Security and correctness review. Anything touching payments, personal data, or accounts gets human review before it ships. AI-generated code is a starting point, not a shipped product.
- Testing and production hardening. The gap between "works on my machine" and "works for every user, every time" is the same gap it has always been.
The result: AI-accelerated development means faster timelines and lower cost on the parts that were always mechanical, and roughly the same rigor on the parts that were always hard. An agency that quotes you a complex product at MVP prices skipped the second list.
What drives the cost
- Number of screens and workflows. More surface means more to design, build, and test.
- Backend complexity. A simple app with a light backend is cheap. Real accounts, permissions, payments, and integrations are where the engineering lives.
- Integrations. Every external system you connect to is work to build and maintain.
- Design fidelity. A clean, standard UI is efficient. A heavily custom, animation-rich experience costs more.
- Platforms. Web is cheapest, one mobile platform is more, both plus web is the most.
What cheap quotes leave out
- Real testing across devices and edge cases, not just the happy path
- Security and correctness review for anything sensitive
- The admin and operational tooling you need to actually run the app
- Ongoing maintenance: OS updates, dependency updates, and fixes. Budget 15 to 20 percent of the build per year
- App-store submission and the review back-and-forth for mobile
How we keep app cost honest
We scope the smallest version that proves the idea, ship it in phases, and use AI where it genuinely speeds the work without cutting the review that keeps software safe. You see a real product early, and you decide what to build next based on what users actually do, not a spec written before anyone used it.
FAQ
Is it really cheaper to build an app now because of AI? For simple and mid-size apps, yes, meaningfully. AI compressed the mechanical part of the work. For complex products, the savings are smaller because the cost was never in the boilerplate, it was in the hard logic, integrations, and testing.
Web or mobile first? If your users do not strictly need to be in an app store, build the web app first. It is faster and cheaper to validate, and you can add mobile once demand is proven.
How long does it take? A simple app or MVP: four to eight weeks. A production app: two to four months. Complex products: longer, and always shipped in phases.
Why are two quotes so far apart? Usually because one included the hard 20 percent, security review, testing, and maintenance, and the other quoted the demo. Ask each what happens after the first version works.
The honest version
Tell us what the app needs to do and we will give you a real range and a recommendation, including whether you need mobile at all yet. Start with the Find My AI Worker flow at /start and we will scope it with you before you spend a dollar.