How much does it cost to build an AI app?

1. What the app has to do

Scope drives cost more than anything else. Count three things:

• Screens and flows. A booking app with five screens is a very different job from a platform with dashboards for clients, staff and admins.
• Types of users. Each role, like customer, staff or admin, needs its own screens and permissions.
• Connections. Every tool the app talks to, like Stripe, HubSpot, Slack or your own database, adds work to build and to test.

The best way to lower the cost is to cut scope, not quality. A good first version does one job very well.

2. Web, mobile or both

• A web app runs in the browser. It's the quickest way to reach users and works well for portals, dashboards and SaaS products. See AI web app development.
• A mobile app goes on the App Store and Google Play. With React Native, one codebase covers both iPhone and Android, so you don't pay for two apps. See AI mobile app development.
• Both usually share one back end, so the second one costs less than the first.

Sentré is a good example: we rebuilt its no-code prototype as a native iOS and Android app with React Native and launched it on both stores in 8 weeks.

3. What kind of AI it needs

"AI app" covers very different things. From simplest to most involved:

• An AI feature. Chat, smart search, writing help or summaries, built on a model like Claude, GPT or Gemini. This is the most common need and the quickest to build.
• AI that answers from your own data. The app looks up your documents or records first, then answers and shows its sources. This is called retrieval, or RAG. It takes more work, because your data has to be prepared and kept up to date.
• An AI agent. It doesn't just answer, it acts: it plans steps, uses your tools and checks its work. Agents need clear limits, testing with real cases and a person in the loop where mistakes matter. See agentic AI development and AI agents.
• Training your own model. Almost no business app needs this. Today's models can do the job with the right setup, which is far quicker and costs much less.

For CoursePro, an AI lesson and quiz writer built into the platform cut the time to create a course by 60%. It's an AI feature grounded in the platform's own content, not a custom model.

4. Your data and the tools you already use

AI is only as good as the data behind it. If your data is spread across spreadsheets, inboxes and old systems, part of the work is bringing it together and cleaning it up.

That's often time well spent. A leading e-commerce buyback brand now makes one-click pricing calls because three data sources were joined into one place first. If your data is already tidy and your tools have good APIs, the build is quicker.

5. The quality bar

Two apps can look the same on day one and cost very differently, because of what's underneath:

• Security. Logins, permissions, payments and personal data need care, and identity checks or escrow payments add more.
• Testing. Automated tests on every change mean nothing breaks quietly when the app grows.
• AI checks. Testing answers with real questions, blocking unsafe output and showing sources.

Cutting these saves money at the start and costs much more later. They're what lets an app keep working when real users arrive.

6. Running costs after launch

Building the app is one cost. Running it is another, and it's easy to forget:

• Hosting for the app and its database.
• AI model usage. Most AI models charge per use, so the bill grows with traffic. Picking the right model for each task keeps this under control: a small, fast model is often enough, and the most powerful one is only used where it's needed.
• Care and improvement. Updates, monitoring, fixes and new features as you learn what users want.

Ask any team you talk to what the app will cost to run each month, not just to build.

How AI-assisted development changes the cost

Teams that build with AI coding agents, like Claude Code and Codex, can write and change code much faster. That shortens the build stage. It doesn't remove the need for experienced engineers: someone still has to plan the work, review every line and test it.

At HKS TechLabs a senior engineer reviews every change before it ships. The speed comes from AI; the quality still comes from people. See AI-assisted software development.

How to keep the cost under control

• Start with an MVP. Build the smallest version that proves the idea, then grow it with real feedback. See AI SaaS and MVP development.
• Use what already exists. Don't rebuild payments, logins or email. Connect proven tools.
• Match the model to the task. The most powerful AI model isn't always the right one.
• Own your code and accounts. You should never have to pay just to get your own work back.
• Ask for working software every week. You'll catch wrong turns early, when they're quick to fix.

How long does it take?

Most first releases of an AI web or mobile app take 8 to 12 weeks. A single AI feature or a first AI agent can be live in a few weeks. The timeline follows the scope, which is why both are agreed before any work starts.

Questions people ask

Can you give me a price without a call?

Not an honest one. Two apps with the same name can differ a lot in scope. A 30-minute call is enough for us to give you a clear scope and quote.

Should we start with a no-code tool?

Sometimes, for a first version. Tools like Bubble and FlutterFlow can get an idea in front of users fast. When the app needs to scale, a custom build is often the better long-term choice, which is what Sentré did.

Do AI apps cost more to maintain than normal apps?

A little, because of model usage and the need to keep checking AI answers. Good monitoring and the right model choice keep it predictable.

Can you add AI to an app we already have?

Yes, and it's often the quickest way to start. We add features like chat, smart search and suggestions to the software you already run.