About Gulmohar

Every ₹2 crore decision deserves the rigour of a boardroom analysis.

Institutional investors run detailed financial models before they commit capital. Developers have data teams, legal advisors, and market intelligence built into every pricing decision. For decades, the individual buyer — the person making the single largest financial decision of their life — has had none of that. A brochure. A broker. And the pressure of a closing timeline.

Gulmohar exists to change that. Not with opinions or recommendations, but with the same structured analysis the other side of the table has always had.

The moment we knew

The first time one of us saw it clearly, it was a site visit in Sector 65.

The broker had sent the comparison sheet. The developer had a floor plan and a payment schedule. There was a banker on speed dial who would approve the loan in 72 hours. Everyone was helpful. Everyone stood to gain from the same outcome. And there was nothing — not a single piece of independent analysis — to tell the buyer whether this was a good decision or just a convenient one.

That gap is not an accident. It is how this market was designed. Gulmohar is our answer to it: a flat-fee tool that earns nothing from your transaction, built to ask the questions no one else in the room is paid to ask.

The information gap isn't a glitch. It's the business model.

Every platform, every broker, every portal in India has one commercial logic: the transaction. Their revenue depends on you buying. That's not an indictment — it's just how the market was built. But it means the advice you receive has never been neutral, and was never designed to be.

First-time buyers navigate this alone — armed with spreadsheets, WhatsApp forwards, and family members who last bought in a different market cycle. Gulmohar is the tool that should have existed already.

₹2Cr+
Average ticket size of a Gurgaon apartment
Most people's single largest financial decision — made with almost no independent analysis.
72%
Of buyers rely on the broker for primary advice
The same person who earns a commission only if the deal closes.
0
Independent, fixed-fee tools for Indian property buyers
Until now.
What we believe

Data is not a feature. It's the only honest foundation for a decision this size.

“We didn't build Gulmohar to tell you what to buy. We built it to make sure you can see clearly — every number, every risk, every reason — before you decide.”
The buyer deserves the same rigour as the seller.
The seller's team runs models. The developer prices from cost intelligence. The buyer has a PDF brochure. That asymmetry is not natural — it is designed. We built Gulmohar to put analytical parity on the buyer's side of the table for the first time.
Commissions corrupt advice.
We made a deliberate choice: flat fee, no brokerage, no transaction commission, ever. The moment your revenue depends on the deal closing, your advice bends — even unconsciously — toward yes. We removed that incentive entirely. It is the only structure under which honest analysis is possible.
We optimise for the 10-year outcome, not the transaction.
Most advice in this market optimises for the close. We ask different questions: How does this asset fit your income five years from now? What happens to your plan if a second EMI lands in your household? Where is this micro-market headed as the city's infrastructure evolves? The right question is never just 'can you afford it today.'
Data should speak plainly.
Every score we produce has a chain of reasoning you can read. If a property has a red flag, you will see it — named, quantified, and explained. We don't soften findings. We don't bury caveats. The whole point is that you can interrogate the result, not just accept it.
The Engine

Trust requires explainability. So we made it explainable.

When you are committing ₹2 crore, you should not have to accept a score on faith. That is why the Gulmohar engine is deterministic and rules-based — not a probabilistic AI model. Every input has a defined weight. Every weight has a published reason. Same data in, same score out. Always.

We chose this architecture specifically because trust requires explainability. When the engine tells you a property's entry price is 11% above the cluster median, you see exactly how that benchmark was constructed. When it flags your FOIR, it shows you the ceiling and why it matters. You are never asked to just trust the number.

See how the evaluation works →
01
Entry
Is the asking price fair relative to the market? Price per sqft, cluster benchmarks, premium/discount to comparable transactions.
02
Income
Can you comfortably service this commitment? EMI burden, FOIR, existing obligations, runway post-purchase.
03
Liquidity
How easily can you exit if you need to? Resale demand, rental yield potential, market depth in the micro-market.
04
Risk
What could go wrong? Builder track record, legal title flags, project stage risk, regulatory compliance.
Who built this

We keep the focus on the data, not on us.

Gulmohar was built by a small team: analysts who spent years reading market data for a living, engineers who've built financial tools, and people who — between us — have made or watched others make consequential property decisions without the right information. That experience is what the scoring engine is built on.

We don't lead with names and photos because the product isn't about who we are — it's about whether the analysis is correct. The methodology is published. The scoring weights are visible. The results are auditable. Those are the credentials that matter here.

We read every email.

If you have a question about a report, a city we don't cover yet, a data point that seems wrong, or a feature that would change how you use the tool — write to us.

mail.aishwarya.in@gmail.com →
B-143, Alok Smriti, Buddha Colony Main Road, GPO, Patna, Bihar – 800001

The boardroom analysis, at the buyer's price.

Entry price analysis. Income fit. Liquidity. Risk. A deterministic score with every number explained. From ₹499 — because good analysis shouldn't cost what brokers charge for bad advice.

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