India · Haryana

Cost of AI Automation
development in Haryana.

I know you want to build ai automation.

There are 10 lakh+ agencies, 5 crore+ vibe coders, and 1 crore+ developers out there right now. You found this page anyway. That's not an accident, we're still the best of all of them at what we do.

We're Sachin and Arjav. We started this studio together, and we still personally work on every project that comes in. When you reach out, it's one of us who replies, not a support team. And we'll say it straight: bring us your toughest deadline or the idea three other agencies said no to, that's exactly where we do our best work. We're Indian founders too, so don't stress about the budget upfront, tell us what you've got on a call and we'll figure out what fits.

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MVP₹30,000–80,000
Mid-Complexity₹1.5–4 lakh
Enterprise₹8–20 lakh+

Forget the price tag for a second.

Tell me your actual budget, not what you think you're supposed to say, and I'll tell you honestly what we can build in it. No stretch quote, no upsell.

Try me, I'll build it in your budget

If you are pricing out an AI Automation in Haryana, start with a range, not one number. ₹30,000–80,000 at the lean end, for something built to test one idea. ₹1.5–4 lakh once the product needs to work well every day for real users. ₹8–20 lakh+ when you need real compliance or scale. What surprises most people is how much this range depends on early decisions, like which platforms to support and how much to build now versus later. Get those decisions right early, and the quote you get back will actually mean something.

Local Market Context

Every region has its own quirks that a copy-paste estimate misses. The market in Haryana is no different. Haryana runs on two different economies, Gurugram's corporate GCC and fintech density, and the Faridabad/Panipat industrial belt digitizing manufacturing and trading operations for the first time. It sounds like a small detail, but it is exactly the kind of thing that separates a real, scoped number from a template number. If a studio's quote in Haryana looks identical to what they would quote someone building the same thing somewhere else, that is worth asking about. Ask how local realities shaped their number. The answer tells you a lot about how carefully they actually thought this through.

What Actually Drives The Price

The single biggest thing that decides what ai automation actually costs is how many systems the automation reads from and writes to, and whether it needs RAG grounding over your own data Not the number of screens, which is what most first-time buyers look at because it feels easy to count. Two apps can look almost identical on screen and still cost very differently underneath. A simple app with real-time sync, payments, and offline support will cost more than a bigger app that is mostly static content with a login screen. Screens are what you see in a demo. how many systems the automation reads from and writes to, and whether it needs RAG grounding over your own data is what actually takes the engineering team's time. Ask any studio to break down their number by what actually drives the cost, not what is visible in a mockup.

How We Scope And Build It

Good studios treat the first week as discovery, not development. That means a real founder workshop to pressure-test what an AI Automation actually needs to do, before anyone opens a design tool or writes code. That early investment pays off by catching scope problems early, when they are just a conversation, not a costly change later. Once building starts, you should see a working demo every week. Not a slide deck, not a status update. Real software. Short sprints, where the plan can shift as you learn things during the build, work far better than one long fixed plan.

How MojoStudios Delivers

From brief to live product.

A five-phase delivery system that ensures your product ships fast, right, and built to scale.

01
Scope map
StartBrief
01

Scope map

Frame

Define the goal, users, scope, constraints, and the one question we must answer before design or code begins.
02

Tech blueprint

Architect

Map the data flows, tech stack, API contracts, and system design before a single screen is built.
03

Working system

Build

Ship working slices with real data, frequent demos, and visible progress, no hidden sprints, no surprises.
04

Live release

Ship

Deploy to production, configure monitoring, run acceptance testing, and hand the team a system they can operate.
05

Next roadmap

Evolve

Use real usage data, crash signals, and user feedback to sharpen what matters most in the next cycle.
ReleaseOperate

Realistic Timeline

Timelines for ai automation follow roughly the same tiers as cost. A lean MVP usually takes 6 to 10 weeks from kickoff to a usable first version. A fuller build runs 3 to 5 months. An enterprise-grade product can take past 6 months once every requirement is in place. What actually stretches these timelines is rarely on the original feature list. Things like third-party integrations that turn out to be poorly documented, compliance sign-offs outside the team's control, and building for more than one platform at once. A studio that gives you one confident date without asking about any of this has probably not scoped the project properly yet.

Working With A Remote Team

Being in Haryana while your team works out of India does not mean working blind. It means the way you work together needs to be planned, not assumed. Start with weekly demos, so you get a regular, real look at progress instead of scattered updates. Add strong documentation, so decisions get written down, not just remembered. And build in clear async handoffs, where each side leaves a clear note for the other instead of waiting for a live call. Teams that work this way often communicate more clearly than teams sitting in the same room, simply because writing things down forces more precision than a quick hallway chat ever does.

The Risk Of Going Cheap

A much cheaper quote for ai automation is not automatically a red flag, but it is worth a direct question: what got cut to hit that number? Usually it is one of three things. QA shrinks from real testing on real devices down to the developer checking their own work. Post-launch support, where most real issues actually show up, either is not included at all or barely covers anything. And senior engineers, who catch problems before they get expensive, get replaced by a less experienced team. Any of these can be a fair trade if you know about it upfront. The problem is when you only find out after launch.

Somewhere between ₹30,000–80,000 and ₹8–20 lakh+ is a real number for your project. The fastest way to find it is not more reading, it is a conversation. Reach out, tell us what you are building, and we will give you a straight answer, free, no strings attached. If we are not the right fit, we will tell you that too, honestly, because a mismatched project helps nobody.

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Apps That Think Faster

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At MojoStudios,

We embed AI natively, not as a feature, but as the foundation your product is built on.

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AI is not a feature we add at the end, it's the foundation we build from. Every MojoStudios product is designed to be intelligent, adaptive, and faster than what your competitors can ship.

THIS MEANS

  • Smarter apps that learn from users
  • Reduced manual workflows by 80%+
  • Competitive moat that grows over time
Common Questions

An MVP typically costs ₹30,000–80,000, a mid-complexity build runs ₹1.5–4 lakh, and an enterprise-grade version costs ₹8–20 lakh+. Exact pricing depends on scope, we scope it for free before any commitment.

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Python
Next.js
PyTorch
TensorFlow
PostgreSQL
Oracle
Apache
Selenium
MongoDB
MySQL
Elasticsearch
Redis
Magento
Prometheus
Laravel
Svelte
Python
Next.js
PyTorch
TensorFlow
PostgreSQL
Oracle
Apache
Selenium
MongoDB
MySQL
Elasticsearch
Redis
Magento
Prometheus
Laravel
Svelte
GraphQL
Vite
Paperclip
Cypress
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Slack
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Framer
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HTML5
Angular
React
.NET
Java
FastAPI
MySQL
GraphQL
Vite
Paperclip
Cypress
GitHub
Slack
Grafana
Framer
CSS3
HTML5
Angular
React
.NET
Java
FastAPI
MySQL
GraphQL
Vite
Paperclip
Cypress
GitHub
Slack
Grafana
Framer
CSS3
HTML5
Angular
React
.NET
Java
FastAPI
MySQL
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