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ai-strategy9 min read

Why I Built RupayWise — a No-Bias Financial Toolkit for India, Solo and AI-First

Ganesh Kompella
Ganesh Kompella

Founder, Kompella Technologies — Fractional CTO & CPO

Published June 10, 2026
Four screenshots of the RupayWise fintech platform — homepage, salary calculator, tax regime comparator, and home loan EMI tool — built solo with agentic AI and vibe coding
Vibe coding — where a founder defines intent and AI agents generate the implementation — is how RupayWise shipped 36 financial calculators, 230+ automated test cases, and zero affiliate bias as a solo build in weeks. This is the full story: why the product exists, how agentic AI development compressed a team-sized build into a one-person sprint, and what it proves about autonomous AI in production software.

A case study in agentic AI development — from frustration to a production fintech platform, built solo.


The problem that started it all

A while ago I sat down to answer a question that should have been simple: at my income, in my city, was I better off renting or buying? I did what everyone does — opened a few "rent vs buy" calculators. One asked for three inputs and spat out "buy." Another quietly assumed I'd put the difference under my mattress instead of investing it. None of them let me model the actual decision with my actual numbers.

That small frustration is the reason RupayWise exists.

Why most Indian finance tools fail — and why it matters

I've spent my career around money and technology. I'm NISM XIX-C certified — the certification for Alternative Investment Fund managers — and a partner at a SEBI-registered Category II AIF. So I look at the financial tools most Indians rely on and I see the same two failure modes, over and over.

The first is oversimplification. A flat EMI calculator with no prepayment modelling. A SIP calculator that ignores the expense ratio quietly eating a fifth of your returns over twenty years. Tools that give you a number, but not a decision.

The second, and the one that bothers me more, is bias. A huge share of India's finance content exists to sell you something — a demat account, a regular mutual fund plan, a loan. The "calculator" is a lead-capture form wearing a lab coat. A rent-vs-buy tool that always says "buy" isn't a tool; it's a funnel.

Indians make enormous decisions — a home, a child's education, retirement — on the back of these things. I wanted the opposite: tools that take your real inputs, show the actual math, cite where every number comes from, and have no opinion to sell. Calculators first, content second.

How vibe coding and agentic AI shipped a 36-calculator platform — solo

Here's the part that's relevant to anyone building products today, and the reason this article lives on a fractional CTO's website rather than a fintech blog.

A platform like RupayWise — dozens of distinct financial calculators, each with its own engine, edge cases, tax logic, and state-by-state data — is the kind of thing that traditionally needs a team of 3–5 engineers and several months. I built the first version on my own, in a matter of weeks, by working with autonomous AI agents from day one. This is what people now call vibe coding, and it's the most significant shift in how software gets built since the move from on-premise to cloud.

What vibe coding actually means in practice

Let me be specific about what "vibe coding" looked like for this build, because the term gets thrown around loosely.

I didn't use AI as a fancy autocomplete. I used autonomous AI agents as leverage across the entire product surface: turning the maths for each calculator into tested code, generating the variations (every common loan amount from 10 lakh to 2 crore, every tax slab for both regimes), building the data pipelines that keep rates current, and writing the companion guides.

My job shifted from typing every line to defining what correct looks like and verifying it relentlessly — which, when you're dealing with someone's tax liability, is exactly where a founder's attention should be. This is the core of agentic AI development: the human holds the spec and the verification bar; the AI agents do the implementation.

The workflow for each calculator followed a repeatable loop:

  • Spec the module: Define inputs, outputs, edge cases, and the authoritative source for every number (CBDT for tax slabs, RBI for repo rate, state government for stamp duty)
  • Prompt the agent: Hand the spec to an AI agent with clear constraints — the code it produces must match the test cases, not just "look right"
  • Review and verify: Run the generated code against automated test suites, compare outputs to government examples, fix edge cases
  • Ship and move on: Once verified, the module is production-ready; move to the next calculator
This loop compressed what would normally be a two-week sprint per calculator into hours.
RupayWise homepage — 36 free financial calculators with no ads, no sign-up walls, and no affiliate bias in the math
RupayWise homepage — 36 free financial calculators with no ads, no sign-up walls, and no affiliate bias in the math

What RupayWise looks like today

The result is RupayWise: 36 free calculators across salary, tax, investing, real estate, retirement, and loans — trusted by over 50,000 Indians every month.

A few examples of the philosophy in action:

A CTC-to-in-hand salary calculator that breaks down exactly why your take-home is lower than your offer letter — HRA exemption, EPF deductions, professional tax, Section 80C/80D savings, old vs new regime comparison — all in one view.

RupayWise salary calculator — CTC to in-hand breakdown with old vs new tax regime comparison, showing the full deduction chain
RupayWise salary calculator — CTC to in-hand breakdown with old vs new tax regime comparison, showing the full deduction chain

An old vs new tax regime comparator that finds your exact break-even with your real deductions, including non-salary income, capital gains, and Section 80 deductions.

RupayWise tax regime comparator — side-by-side old vs new regime comparison with break-even analysis
RupayWise tax regime comparator — side-by-side old vs new regime comparison with break-even analysis

A page that computes home-loan EMI by amount for every common loan size from 10 lakh to 2 crore, with tenure breakdowns and prepayment simulators.

RupayWise home loan EMI page — instant EMI amounts for every common loan size from 10 lakh to 1 crore
RupayWise home loan EMI page — instant EMI amounts for every common loan size from 10 lakh to 1 crore

No sign-up. No ads blocking the result. No "to see your answer, enter your phone number."

The non-negotiables: why AI-first doesn't mean AI-loose

Building fast with autonomous AI agents doesn't mean building loosely — especially in finance, where a wrong number isn't a typo, it's a person making a bad decision with their money. This is the point most "vibe coding" discourse misses: speed without verification is recklessness, not innovation.

I held three lines from the start, and these are the same lines I hold when building products for clients:

Every calculation is verified against authoritative sources

The engines are validated against 230+ automated test cases — EMI formulas checked against bank amortisation schedules, tax computations against the Income Tax Department's own examples, stamp duty against state rate cards. AI helped me write those tests as much as the features. Speed and correctness aren't a trade-off if you build the verification into the agentic workflow from the beginning.

Every number is sourced and dated

Tax slabs cite the CBDT. Repo rate cites the RBI. Stamp duty cites the state registration department, with the date it was last verified. If you can't check it, it doesn't belong on a finance site.

No affiliate bias in the math

RupayWise will eventually earn through ads and partner links — but the answer a calculator gives is never bent to earn a commission. The day a tool starts telling everyone to "buy" or "apply" because that pays, it stops being worth building.

None of this is glamorous. All of it is the reason a stranger can trust the output.

What agentic AI development actually teaches you about building products

The lesson I keep coming back to isn't "AI writes code now." It's that autonomous AI agents collapse the distance between an idea and a shipped, working product — if you bring the judgment.

A solo founder with a clear spec and a high bar for verification can now build, in weeks, what used to require a team and a runway. The bottleneck has moved. It's no longer "can we build it?" — it's "do we know exactly what we want, and can we tell when it's right?"

This is the same insight behind every engagement we run at Kompella Technologies. Whether it's a fractional CTO engagement, a fractional CPO sprint, or a build-and-ship project, the pattern is identical: define the spec precisely, set the verification bar high, use AI agents to compress the build, and ship production-quality software in a fraction of the traditional timeline.

The companies that win the next few years will be the ones whose leaders can hold that bar while moving at AI speed. Agents are the new mobile — and the founders who learn to work with them rather than around them will ship circles around teams still waiting for the next quarterly planning cycle.

RupayWise is the proof of work. Not a demo. Not a prototype. A production platform trusted by 50,000+ monthly users.

Need help thinking this through? Book a 30-min call — no pitch.

If you're trying to ship like this

This is exactly what I do for a living. As a fractional CTO and CPO, I help funded startups build and ship AI-first — turning a founder's vision into real, tested, production software without the traditional team-and-timeline tax. I've built products that scaled to nine figures of ARR, and I now work hands-on with a few companies at a time to do the same.

If you're a founder or operator trying to move faster than your headcount should allow — to compress months of build into weeks without lowering the bar — that's the problem I solve. Reach out at kompella.io and let's talk about what you're trying to build.

And if you just want to make a sharper money decision today, the tools are free and open at RupayWise. That's what they're there for.

— Ganesh Kompella

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FAQ

Frequently asked questions

What is vibe coding and how does it differ from traditional software development?
Vibe coding is a development approach where a human defines intent, constraints, and acceptance criteria while AI agents generate the implementation. Unlike traditional coding where a developer writes every line, vibe coding shifts the bottleneck from typing code to specifying what correct looks like. The founder's role becomes verification-first — defining specs, reviewing outputs, and running tests — rather than keystroke-first. This is distinct from using AI as autocomplete; in vibe coding, entire modules, test suites, and data pipelines are agent-generated from structured prompts.
Can you really build production-quality software with autonomous AI agents?
Yes — with the right methodology. RupayWise is a live example: 36 financial calculators, 230+ automated test cases, verified against government tax tables and bank amortisation schedules, serving 50,000+ monthly users. The key is that autonomous AI doesn't mean unverified AI. Every calculation engine was validated against authoritative sources (CBDT for tax, RBI for repo rates, state registration departments for stamp duty). AI generated the code and the tests; human judgment set the verification bar.
How long does it take to build a full product with agentic AI development?
RupayWise — 36 distinct calculator engines, each with its own tax logic, edge cases, and state-by-state data — was built in a matter of weeks by a single founder working AI-first. A comparable platform built traditionally would require a team of 3–5 engineers and 4–6 months. The compression factor is roughly 5–10x on calendar time, but only if the founder brings deep domain expertise and holds an uncompromising verification bar.
What does AI-first product development look like in practice?
In an AI-first build, AI agents handle code generation, test authoring, data pipeline construction, and content drafting. The human founder defines specifications, sets acceptance criteria, verifies outputs against authoritative sources, and makes architectural decisions. The workflow is: spec a module, prompt an agent, review the output, run automated tests, fix edge cases, move to the next module. The founder's attention shifts from typing to judgment — which, in domains like finance where a wrong number causes real harm, is exactly where it should be.
Is vibe coding suitable for fintech and regulated industries?
Yes, if you build verification into the workflow from day one. RupayWise handles tax liability, loan amortisation, and investment projections — areas where errors directly affect financial decisions. The build used 230+ automated test cases validated against Income Tax Department examples, bank schedules, and state rate cards. AI-generated code in regulated domains requires more rigorous testing, not less. The advantage of vibe coding is that AI can also generate the test cases alongside the features, making comprehensive verification faster to build.
How does Kompella Technologies help companies build AI-first products?
Kompella Technologies provides fractional CTO and CPO leadership for funded startups building AI-first. We embed with your team to set the AI architecture, define the verification methodology, and ship production software — turning a founder's vision into tested, deployed product without the traditional team-and-timeline overhead. We've built products that scaled to nine figures of ARR, and we now work hands-on with a few companies at a time to compress months of build into weeks.

About the Author

Ganesh Kompella

Ganesh Kompella

Founder, Kompella Technologies — Fractional CTO & CPO

Ganesh is the founder of Kompella Technologies, a fractional CTO and CPO firm working with healthcare, fintech, and SaaS startups from pre-seed through Series B. 15+ years and 75+ products shipped, $140M+ ARR built, one IPO guided. Operates across India, Singapore, and the United States.

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