Scope map

Cost of AI Chatbot
development in Australia.
I know you want to build ai chatbot.
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.
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.
If you are pricing out an AI Chatbot in Australia, start with a range, not one number. ₹25,000–60,000 at the lean end, for something built to test one idea. ₹1–2.5 lakh once the product needs to work well every day for real users. ₹5–12 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
It helps to ground any cost conversation in Australia in what is actually true about that market, not assumptions borrowed from somewhere else. Australia is one of the easiest Western markets to collaborate with in real time, Sydney and Melbourne run ahead of IST rather than behind, giving a genuine overlapping workday rather than an overnight handoff. This is not a small detail to skip past. A good studio should be weaving it into how they scope your build, from your timeline to which risks are worth planning for early. Bring this up directly in your first call. The answer you get is a good sign of how much homework the studio has actually done.
What Actually Drives The Price
It is tempting to estimate ai chatbot by counting screens, the way you might estimate a house by counting rooms. But that logic breaks down fast, just like a small room full of wiring can cost more than a big empty one. What really decides the price is whether it's grounded in your own docs/data via RAG or just answering from a fixed script And it is rarely visible in a wireframe. Picture two apps that look almost the same on paper. One just shows content and takes a form. The other talks to three outside systems and handles real users safely. Same number of screens, very different amount of work.
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 Chatbot 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.
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 chatbot: 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 Australia 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
When a quote for ai chatbot comes in far lower than everyone else's, that gap is rarely magic. It almost always means something got quietly cut from scope. The usual casualties do not show up in a demo. QA gets rushed instead of properly tested across real devices. Post-launch support shrinks to almost nothing, or disappears entirely. And the people actually writing the code skew junior, with little senior oversight. None of this is visible while you compare proposals. It shows up months later, as bugs, unanswered support requests, or code nobody wants to touch. A lower price is fine, as long as you know exactly what it is missing.
Somewhere between ₹25,000–60,000 and ₹5–12 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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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.
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An MVP typically costs ₹25,000–60,000, a mid-complexity build runs ₹1–2.5 lakh, and an enterprise-grade version costs ₹5–12 lakh+. Exact pricing depends on scope, we scope it for free before any commitment.
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