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Scope map
India · Punjab
Cost of AI Automation
development in Punjab.
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.
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.
ai automation pricing in Punjab breaks into three simple tiers. ₹30,000–80,000 for a basic version that proves your idea works. ₹1.5–4 lakh for the fuller product most businesses actually launch with. ₹8–20 lakh+ once compliance, integrations, or scale come into play. Most founders get surprised by the middle tier. They budget for an MVP, then slowly add features until it quietly becomes something bigger. That is not a vendor problem. It is a planning problem, and it is easy to avoid if you draw the line clearly before you start.
Local Market Context
Before you lock in a budget, it helps to know what makes the market in Punjab different from a global average. Punjab's economy is manufacturing- and export-heavy, hosiery, sports goods, and agri-trade businesses across Ludhiana, Jalandhar, and Amritsar increasingly need e-commerce and B2B platforms to reach buyers directly. That one fact affects hiring, vendor choice, and even how you price your own product. A good studio should be asking about this in your very first conversation, not treating it as an afterthought. Founders who skip this step often end up over budgeting out of caution, or under budgeting because they assumed rules from another market apply here too.
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
Projects that stay on budget usually share one thing: they start with real scoping, not just a quote. A founder workshop early on, where you map out user flows and priorities together instead of guessing from a brief, sets a strong foundation. Every sprint should end with something you can actually click through, not a status update summarizing what happened. Seeing working software every week means you catch a wrong turn in week two, not week twelve. This takes more discipline than working off a fixed spec, but it keeps the build aligned with what you actually need.
How MojoStudios Delivers
From brief to live product.
A five-phase delivery system that ensures your product ships fast, right, and built to scale.
Realistic Timeline
Timeline estimates for ai automation usually fall into three bands: 6 to 10 weeks for an MVP, 3 to 5 months for a fuller build, and 6-plus months once enterprise requirements come in. What pushes a project from one band to the next is rarely the core features. It is the dependencies around them. Integrations with outside systems add real uncertainty, since you are waiting on someone else's system to behave as promised. Compliance requirements add review cycles that sit outside your development team's control. And building for two platforms from day one roughly doubles the testing work, not just adds to it.
Working With A Remote Team
The real worry with remote teams is almost never the work itself. It is whether you will actually know what is happening day to day, especially across time zones. The fix is not forcing overlapping hours. It is building communication that does not need them. A working demo every week, so you always see real software, not a status update. Clear notes on decisions as they happen, so nothing depends on someone's memory weeks later. And async handoffs, so the team keeps moving your project forward while you are offline. This approach often beats same-timezone teams, because it forces clear writing that in-person teams often skip.
The Risk Of Going Cheap
It helps to be specific about what a much lower quote for ai automation usually means, because "you get what you pay for" is true but not very useful on its own. In practice, the cuts usually land in three places. QA becomes a quick final check instead of real testing across devices. Post-launch support, the time when real users find the issues testing missed, gets minimized or dropped. And the team writing the code shifts toward less experienced developers with less senior review. Any one of these can be an acceptable trade depending on your situation, but it should be a choice you make knowingly, not a surprise after launch.
You have read the ranges. Here is what actually matters. Your project is not ₹30,000–80,000 or ₹8–20 lakh+, it is a specific thing with specific needs. The only way to know where it lands is to tell us about it. That is really all a scoping call is. No pitch deck, no pressure, just us listening to what you are trying to build and giving you a real number back.
AI-Powered
Apps That Think Faster
At MojoStudios,
We embed AI natively, not as a feature, but as the foundation your product is built on.
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.
AI Automation Cost in Other Markets
Other Costs in Punjab
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