AI app development cost: a real breakdown.

01The short answer

Here is what building with us costs, with no asterisks:

Most first releases go live 2 to 4 weeks after kickoff. Every build gets a fixed quote at the end of discovery, so the number you sign is the number you pay. Prices in INR are available for Indian clients. The rest of this guide explains what moves a project above the starting price, and what it costs to run afterwards.

02The four things that drive the price

1. Integrations

This is the big one. Every system the app reads from or writes to, such as a CRM, a payment gateway, WhatsApp, telephony or a government API, needs authentication, error handling and testing. A standalone app is cheap; one that sits at the centre of your operations is where the work is.

2. Product surface

A web app, a mobile app, and an admin panel are three products. Launching on one surface first and adding the others once people use it is the most reliable way to keep a first release affordable.

3. Data readiness

If your data lives in clean databases, AI features are quick to build. If it lives in spreadsheets, PDFs and chat histories, part of the project is cleaning and structuring it. Discovery tells you which situation you are in.

4. Risk and compliance

Health records, payments, approvals and anything regulated need extra controls: audit logs, access rules, sometimes private model hosting. They are worth it, and they are part of the price.

Notice what is not on the list: the AI model itself. Model choice matters a lot for running costs and quality, but it rarely moves the build price much.

03Running costs nobody quotes

• Hosting and database, which grow slowly with users.
• Model usage, billed per request by most providers, which grows with every conversation, call or document.
• Channel fees, such as WhatsApp message charges, telephony minutes or SMS.
• Monitoring and maintenance, because models, APIs and libraries keep changing underneath you.

We size these per unit during discovery: cost per conversation, per call, per processed document. That turns a vague monthly worry into a number you can compare with what the same work costs today.

04Where AI budgets go wrong

1. Building everything at once. Ten features half-done cost more than three that work.
2. Skipping discovery. The hard questions surface in month three instead of week one.
3. No evaluation set. Without one, every change is a guess, and guesses cause rework.
4. The biggest model everywhere. Routing simple steps to a smaller, cheaper model often cuts running costs sharply without hurting quality.
5. Forgetting maintenance. An AI app with no owner after launch slowly gets worse.

05How to keep both costs under control

• Fix the scope of the first release and write it down.
• Automate one workflow end to end before adding the next.
• Use different models for different steps, and cache repeated work.
• Set budgets and alerts on model usage from day one.
• Own your code, data and evaluation set, so you can change vendors or models without starting over.

For how to choose what to build first, see AI MVP development.

06Questions people ask