01
Scope map
India · Delhi
Cost of AI Automation
development in Delhi NCR.
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.
There is no single price for an AI Automation in Delhi NCR. There are three. A lean MVP, built to test one core idea, usually costs ₹30,000–80,000. A fuller version, with the polish and features real users expect, costs closer to ₹1.5–4 lakh. A build made for scale, compliance, or heavy integrations moves into ₹8–20 lakh+. None of these is more "correct" than the others. They just answer different questions. Before you ask anyone for a quote, decide honestly which one you actually need first.
Local Market Context
Every region has its own quirks that a copy-paste estimate misses. The market in Delhi NCR is no different. Delhi NCR is Mojo Studio's home base, the capital region's mix of government/PSU tendering, media, retail, and a fast-growing D2C scene means in-person discovery and same-day meetings are genuinely on the table here, not just a sales line. 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 Delhi NCR 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
Most cost surprises during ai automation development trace back to one thing: the first estimate was built around screen count instead of how many systems the automation reads from and writes to, and whether it needs RAG grounding over your own data And that is what actually eats up engineering time. Picture a dashboard showing the same few charts, whether the data comes from one clean source or four messy old systems that do not talk to each other well. It looks like one simple screen either way. But the work behind it is nowhere close to the same. A good studio will ask sharp questions about how many systems the automation reads from and writes to, and whether it needs RAG grounding over your own data before they even open a design tool, because that is the real driver of cost.
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.
Realistic Timeline
A realistic range for ai automation: 6 to 10 weeks for an MVP focused on one core flow, 3 to 5 months for a version with the full set of features a real launch needs, and 6 months or more once you are building for enterprise scale. The gap between the estimate and the real delivery date usually comes down to a few common causes. Integrations with outside systems that turn out to have thin documentation. Compliance reviews that run on someone else's schedule. And the simple fact that building for two platforms takes more than double the work of building for one.
Working With A Remote Team
Working with an India-based team while you are in Delhi NCR raises an obvious question: how do you stay in sync across a time gap without everything slowing down? The real answer is structure, not being in the same room. Weekly demos give you a fixed, predictable check-in to see real progress and steer it if needed. Written notes on decisions and changes mean nothing important lives only in someone's memory. And handoffs at the end of each working day mean work keeps moving while you sleep. Done well, this setup is often more disciplined than teams sitting in the same office.
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.
Here is the honest truth. No article, including this one, can tell you exactly what your ai automation will cost. Only a real conversation about your actual idea can. So let's have that conversation. Message us or hop on a free call, and you will get a straight, specific answer from the people who would actually build it. Not a sales script, not a follow-up form, just a real answer. No pressure either way, and no obligation to ask.
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 Delhi NCR
Tech Capabilities Powering Our Solutions
Built on proven frameworks, modern stacks, and tools trusted by global teams
